Traffic congestions and associated collisionswebfiles.ita.chalmers.se/~mys/ActiveSafety05/ProjectReports05/Group1.pdfProject Group 1: Traffic congestions MMF320 Active Safety 4 2

MMF320 Active Safety Department of Machine and Vehicle Systems

Chalmers University of Technology Gothenburg, Sweden

Traffic congestions and

associated collisions

May 2005

Group 1: Alejandro Martinez Bojan Stojanovic Johannes Pohl Pedro Alves Pedro Dias Joao Tiago Cardosa

Project Group 1: Traffic congestions MMF320 Active Safety

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1. Content 1. Content ................................................................................................................... 2 2. Introduction ............................................................................................................. 4

2.1. Traffic congestion and Active Safety ................................................................ 4 3. Accident data analysis ............................................................................................ 6 4. GPS ........................................................................................................................ 8

4.1. Introduction....................................................................................................... 8 4.2. Technology Description .................................................................................... 8 4.3. GPS and Traffic Congestions ........................................................................... 8

4.3.1. Traffic density management....................................................................... 8 4.3.2. Post-crash management using GPS.......................................................... 9 4.3.3. Pre-crash system for collision warning in intersection using DGPS........... 9 4.3.4. A GPS-based slowdown warning system for automotive safety ................ 9 4.3.5. Future perspectives of GPS..................................................................... 10

4.4. GPS III............................................................................................................ 11 4.5. Conclusions.................................................................................................... 12

5. Anti-Sleeping System............................................................................................ 12 5.1. Introduction..................................................................................................... 12 5.2. Counter measures of driver sleepiness .......................................................... 13 5.3. Driver Sleepiness Warning Systems .............................................................. 14

5.3.1. The Awake Project in the European Union .............................................. 14 5.3.2. PERCLOS Technology in the United States ............................................ 15

5.4. Conclusions.................................................................................................... 16 6. Changing Lane...................................................................................................... 16

6.1. Introduction..................................................................................................... 16 6.2. Eliminating Blind Spot..................................................................................... 17 6.3. Lane Detection Sensor ................................................................................... 19 6.4. Lane Departure Warning System (LDW)........................................................ 19 6.5. Active steering System................................................................................... 20 6.6. Problems ........................................................................................................ 20

7. Sensors................................................................................................................. 21 7.1. Raining Sensor............................................................................................... 21 7.2. Light Sensor ................................................................................................... 21 7.3. Tire Monitoring Pressure ................................................................................ 21 7.4. Steering Angle Sensor.................................................................................... 21 7.5. Speed and acceleration sensors .................................................................... 22 7.6. Brake sensor .................................................................................................. 22 7.7. Closing Velocity Sensor.................................................................................. 22 7.8. Force Feedback Pedal (FFP) ......................................................................... 23

7.8.1. Possibilities .............................................................................................. 23 8. Adaptive Cruise Control ........................................................................................ 23

8.1. Range sensor units......................................................................................... 25 8.2. Actuators ........................................................................................................ 26 8.3. Availability and price....................................................................................... 26 8.4. Man-Machine interface................................................................................... 26 8.5. Technical Limitations ...................................................................................... 26 8.6. Future development of ACC........................................................................... 27 8.7. Conclusion...................................................................................................... 27

9. Brake Assist System ............................................................................................. 28 9.1. Conclusion...................................................................................................... 28


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10. Radio Communication......................................................................................... 29 10.1. Introduction................................................................................................... 29 10.2. Intelligent Transportation Systems (ITS) ...................................................... 29 10.3. Advances in Navigations Systems ............................................................... 30

10.3.1. Vehicle Information Positioning System (VICS) ..................................... 30 10.4. Information Sharing ...................................................................................... 31

10.4.1. Radio Beacons....................................................................................... 31 10.4.2. Optical beacons ..................................................................................... 31 10.4.3. FM multiplex broadcast .......................................................................... 31

10.5. Types of information ..................................................................................... 32 10.6. Dedicated Short Range Communication systems (DSRC)........................... 32 10.7. Road to Vehicle Communication (RVC) ....................................................... 33 10.8. Inter Vehicle Communication (IVC) .............................................................. 33 10.9. Electronic Toll Collection (ETC).................................................................... 34 10.10. Research and development........................................................................ 35 10.11. Conclusions................................................................................................ 35

11. Computer Vision for Driving Assistance.............................................................. 36 11.1. Introduction................................................................................................... 36 11.2. Principles...................................................................................................... 37 11.3. Applications .................................................................................................. 38

11.3.1. Lane detection ....................................................................................... 38 11.3.2. Pedestrian detection .............................................................................. 38 11.3.3. Night vision ............................................................................................ 39 11.3.4. Driver monitoring.................................................................................... 39

12. Conclusion .......................................................................................................... 40 13. References.......................................................................................................... 41


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2. Introduction Our group’s task is to address the problem of traffic congestion and associated collisions of varying severity. First we will define traffic congestions and identify what types of accidents are of particular interest. The primary aim is to find solutions to reduce the number of injured and killed people in these accidents. To do that we try to summarise the state of the art in technical solutions that have been, or are being, developed to deal with this problem.

2.1. Traffic congestion and Active Safety Congestion is a serious problem, localised in specific places and times, especially in cities and peak hours. The European Conference of Ministers of Transport adopted the following definition of traffic congestion: “Congestion is the impedance vehicles impose on each other, due to speed-flow relationship, in conditions where the use of a transport system approaches its capacity.” Congestion is the “resistance” slowing traffic as the number of vehicles increases towards saturation. Lower speeds, sometimes (but not always) with stop-go traffic, is the result of congestion. From this definition roads are almost always congested, but the level of congestion can vary from slight to gridlock. Congestion leads to a decrease in speed resulting in lost time. Stop-go conditions increase energy use and worsen pollution. It harms the quality of life, community and security of others. Furthermore congestion increases crashes. [1] It is a quite complex system between traffic congestions and these crashes, because they are influenced by a variety of different factors, for example:

• human factor • vehicle technology • road infrastructure, • public and private costs • weather • …

To get a little overview about how to prevent crashes and reduce road crash injuries we use the Haddon Matrix (Figure 1) [2]. William Haddon Jr. defined three phases of the time sequence of a crash event – pre-crash, crash and post-crash – as well as the epidemiological triad of human, machine and environment that can interact during each phase of a crash. The resulting nine-cell Haddon Matrix models a dynamic system, with each cell of the matrix allowing opportunities for intervention to reduce road crash injury. This figure led to substantial advances in the understanding of the behavioural, road-related and vehicle-related factors that affect the number and severity of casualties in road traffic. Building on Haddon’s insights, a wide range of strategies and techniques for casualty reduction have since been tested internationally, through scientific research and empirical observation. The strategies include interventions:

• to reduce exposure to risk; • to prevent road traffic crashes from occurring; • to reduce the severity of injury in the event of a crash; • to reduce the consequences of injury through improved post-collision care.


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To differentiate which tasks belong to “Active Safety” and which to “Passive Safety”, we look at the safety model of EUCAR ADASE II (Figure 2) [3]. In that safety model we can see that “active safety” systems are concerned with the prevention of crashes by assisting, warning or actively controlling. Therefore “passive safety” systems are mostly concerned with post-crash systems. Where are the collisions related to traffic congestions situated in that model? Due to the fact that the characteristic of traffic congestions and related collisions is that they are not caused by a single car nor do the consequences in general affect only one car, it leads to the conclusion that traffic congestions are not directly addressed by this model. Also other safety models do not address this problem directly, because of its complexity. The problem of traffic congestions and related collisions has to be broken down into different tasks to find a solution for that problem. Next to “active safety” systems and “passive safety” systems also ideas concerning the road and the road infrastructure have to be developed.

Figure 1: The Haddon Matrix [2]

Figure 2: EUCAR ADASE II [3]


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3. Accident data analysis Road traffic accidents in the Member States of the European Union annually claim about 39.000 lives and leave more than 1.7 million people injured, representing estimated costs of 160 million euro [4].

The main crash types causing death and serious injury are [5]:

• head-on crashes • brutal side impacts at junctions • run-off accidents (e.g. vehicles leaving the road and striking objects close to

the roadside) • accidents involving pedestrians and cyclists

Based on these facts it can be stated that accidents which occur in dense traffic situations are not mainly among the ones that cause fatalities. The primary crash types that are involved in accidents due to traffic congestion are back-to-back or chain collisions, lane interception collisions, and intersection crashes. The primary factors are inadequate distance between vehicles, driver inattention or disturbance, inappropriate speed and monotony [6]. Most of the accidents related to traffic congestion only lead to injuries and property damage. Therefore they are very costly for the society. For example a case study in New Jersey came to $11,5 billion annual costs for employers, because of 325000 injured people in car crashes on the job and 5000000 more away from the job [7].

Figure 3: Annual number of fatalities, injury accidents and injured people (EU-15*) [4]


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Another interesting factor is the location where accidents happen. Figures 4 and 5 show the distribution of fatalities and injuries based on the location. The paradox thing is that motorways are on average four times safer than single carriageway roads and twice as safe as ordinary dual carriageways. It is not rare for important single carriageway roads to carry risk levels 10 times those prevailing on motorways. In Europe, over 60% of deaths happen outside built-up areas mainly on single carriageway roads. Just 5% of deaths occur on Europe’s motorways [4].

single vehicle accidents

animal chain or

rear frontal lateral other parked vehicle

no distinction

no obstacle

with obstacle

not defined Total

BE* 0 76 163 147 0 0 - 21 492 0 899 DK* - - - - - - - - - 246 246 EL* 2 49 176 189 10 25 - 203 146 0 800 ES 7 241 631 715 57 26 - 820 617 0 3114 FR 0 208 1093 745 639 0 2178 - - 0 4863 IE 0 5 81 16 9 0 88 - - 0 199 IT** 0 279 755 973 1031 23 - - 440 0 3501 LU 0 0 0 0 22 0 - 0 30 0 52 NL 0 25 72 101 0 5 - 31 245 0 479 AT 1 36 145 21 65 2 - 254 0 0 524 PT 1 26 236 104 0 0 - 190 150 0 707 FI - - - - - - - - - 267 267 SE 6 13 128 68 17 0 - 146 1 0 379 UK - - - - - - - - - 1832 1832 Date of query: October 2004 * Data 2001 ** Data 1998

Table 1: Number of car and taxi occupant fatalities per country, by type of collision, 2002 [4]

Figure 5: Number of fatalities within 30 days, 2002 [4] Figure 4: Number of injury accidents, 2002 [4]


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4. GPS

4.1. Introduction One of the alternatives that has already been discussed as an interesting way to solve the problem of traffic congestion and the associated types of collision is to use the Global Positioning System (GPS). Throughout this part of the project information regarding the description of this technology (GPS), positioning techniques, current applications of GPS technology and its relation with the traffic congestion problems, as well as the current limitations and future expectations of the GPS will be presented. In the last decade there has been a widespread use of roadside assistance for disabled vehicles. This service is made possible by GPS because it provides the responder with the location’s accuracy previously unavailable. Without GPS, drivers often do not know the exact location of their vehicle resulting in lengthy, often aborted searches for the requesting vehicle. As a consequence, automatic collision notification, now deployed on several million vehicles and saving many lives a year, is only possible with GPS. [8]

4.2. Technology Description The system is made up of 3 essential parts: the orbital part composed by the satellites, the control part used to pilot the system and which is composed of five American ground stations and finally the user part which only receives information from navigation messages from satellites. [9] The orbital part is composed of 28 satellites that are deployed in six orbital planes, each of them spaced 60° apart and inclined 55° relative to the equatorial plane. These satellites evolve at an altitude of 20000 Km and need 12 hours to complete a rotation on their orbital plane. The system design ensures that users all over the world would be able to observe a minimum of five satellites, and more likely to visualize from six to eight satellites, just if they have a clear view of the sky. This is an important fact because we need at least a minimum of 4 satellites to accurately determine a PVT (Position-Velocity-Time) solution that consists of latitude, longitude, altitude, velocity and corrections to the GPS receiver clock. The GPS satellites continuously broadcast information on two frequencies, and one of these frequencies is equal to 1575.42 MHz. The later is used for non-military applications whereas the first one is used for military application. The information given by the satellites are carried by navigation messages that contain time of signal transmission, clock correlation, and health information on all of the satellites in the GPS.

4.3. GPS and Traffic Congestions

4.3.1. Traffic density management GPS technology is a powerful tool to take into account in real-time traffic conditions when the heading direction of a vehicle is to be known. One approach is to periodically provide the user’s position information to a central server, which uses the


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whereabouts information of all the cars equipped with GPS, to map the traffic flow. The information available from satellites and radio which deal with traffic congestion can be also used to determine the flow of vehicles at a determine location. The analysis of these data carried out by the call centre can be sent back to the user and provide him or her with the real-time traffic movement updates [10]. Therefore, firstly this system can help the user to avoid traffic congested locations or areas. Secondly it represents a helpful aid to enhance and maintain the appropriate number of vehicles in a certain road or highway to ensure fluid traffic conditions avoiding traffic jams with all its consequences like anxiety, stress, pollution and unnecessary wear of the vehicle. This technology has a direct impact on the number of traffic accidents caused by traffic congestions since it warns the driver about congested areas where it is likely to have an accident.

4.3.2. Post-crash management using GPS In the event of an accident with airbag deployment, for example in a crash when a lead vehicle slowed or stopped because of congestion, and then the following vehicle in the same travel lane did not slow down fast enough to avoid the collision against the vehicle in front of it. The navigation system can display the exact location of the vehicle and then transmit it via a special modem protocol to the police or emergency corps. [10] For instance, this protocol will allow automatic transmission of the car’s information about whether the airbag was deployed or not, in that case the emergency corps will have an idea of the severity of the collision and the likelihood of injuries among the occupants.

4.3.3. Pre-crash system for collision warning in intersection using DGPS In order to eliminate traffic accidents at intersections in congested conditions, many detection systems have been developed like the DGPS. Using DGPS for preventing collisions at intersections is one of the possibilities considered. The system consists of a base station (master site) that sends information to vehicles via modem for inter-vehicle communication. In that case, the vehicle position can be accurately measured. The base station and the automobile receive the signals from GPS satellites. The coordination and accuracy of the signal is then improved by the base station and then sent it at the same time to two cars approaching to an intersection. The position of each vehicle is sent to each other by IVC to let them know the vehicle position in real time. Based on the velocity and the direction of each vehicle, the intersection position and the possibility of vehicle collision at the intersection can be predicted in advance [11]. Since the vehicles have a very irregular speed at traffic congested situations, the prediction of a collision is also irregular with time, so the frequency of the calculation to predict the real-time conditions of the vehicle has to be very high. Unfortunately, in current systems there is always a time delay between acquisition of signal, calculation of position and reacquisition. This time delay is directly related with inaccuracy of positioning and hence prediction by the GPS technology. [11]

4.3.4. A GPS-based slowdown warning system for automotive safety A brand new concept of a slow-down warning system in automobiles was recently proposed. Concerning one of the most common accidents caused by traffic


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congestions, if a driver on a highway decelerates suddenly or progresses abnormally slowly (thereby posing a hazard to the vehicles behind him), then, with the GPS system, all the cars behind him are provided with information that he or she is slowing down because of the traffic jam ahead. This advance information gives the drivers additional time to react in preparation of the impending slow-down. Simulations demonstrate that this additional time is sufficient to alleviate collisions. Furthermore, it is seen that even if only a fraction of the cars in a platoon are equipped with such a system, this can still be sufficient to alleviate crashes even in the unequipped cars. [12]

4.3.5. Future perspectives of GPS Over the next 15 years as we move into the deployment of GPS III the major changes in GPS, from the user’s perspective, will be an increase in accuracy and reliability. For road vehicles there are three rough levels of accuracy that are relevant, road level, lane level, and control level as shown in the figure below. Road level is adequate to identify the road that a vehicle is on; this is the current status of GPS (10+1 m). The next level of accuracy, lane level, allows a vehicle to identify a specific lane on a road, this accuracy is about 1 meter. Finally, a vehicle may be located to a level sufficient for collision avoidance and control applications, on 10-1meters. [8]

Figure 6: Vehicle interaction possibilities vs. position accuracy [8]

In the near term, with existing positioning systems we will see applications such as curve warning and headlight steering like in BMW models. Both of these will likely be on the market in the next few years from several manufacturers. These systems provide the vehicle a preview of the road ahead based on a digital map in the vehicle [8]. Throughout the market many cutting-edge technologically advanced positioning systems are been developed. One example which is considered to be the next step of the GPS systems is the Onboard Real-time System for 3D Urban Environment Reconstruction. The 3D Urban Environment Reconstruction will help to increase the driver’s awareness about the accidents that may happen while they are using the road along with many other motorists in a traffic congested situation. Using this system, the driver can be more prepared to avoid an accident in the dense traffic. The goal of this system is to develop a system able to generate and reconstruct 3D model for urban environments (especially roads) in real time. In general, there are two kinds of techniques for measuring three-dimensional geometrical data. One is based on intensity image. Another is based on range data. Several researches using


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photographs or CCD/video cameras have demonstrated that 3D information can be extracted using motion and stereoscopic techniques. The difficulties in reliable stereo matching, distortion from limited resolution and unstable geometry of CCD cameras are the major obstacles to reconstruct a 3D model of complicated environment with necessary accuracy and robustness. On the other hand, reconstructing 3D objects using range sensors has concentrated on reconstructing small objects such as teeth, bust, mechanical parts, etc. With the development of eye-safe laser range scanner, reconstructing relatively large objects in urban environment using range data becomes technically feasible [13].

4.4. GPS III The GPS III is considered to be another technological advance towards a wider application of the GPS technologies to prevent traffic accidents. GPS III includes a review of the entire GPS and USG augmentation system architecture to achieve long-term system performance goals while reducing long term total ownership costs. GPS III will address a balance of civil and military needs/capabilities and possible augmentation system integration opportunities; to ensure the best system for the next 30 years. GPS III is intended to be a “clean slate” to address the position, velocity and time requirements of all civil GPS users including improved integrity and higher signal power civil applications (based on already developed L1, L2C and L5 signals). The resulting performance improvements may enable intelligent highway systems and precision farming; and provide significantly increased integrity to enable precision navigation systems considered crucial for anticipated civil aviation uses (although- military users will also likely benefit). It could also become the foundation for an innovative revolution in transportation system applications. The GPS III program is a unique opportunity for the civil GPS community to come together to shape the future of navigation services. In particular the automotive industry can help influence the civil GPS III requirements for position, velocity and timing information to help lay the groundwork for innovation for future GPS automotive applications that enhance the safety, efficiency and pleasure of driving an automobile. The figure below provides some insight into the raw GPS signal in space (SIS) pseudo range error reductions resulting from GPS modernization. The significance of the chart is in the relative performance from 1996 through GPS III, which improves by an order of magnitude. [8]

Figure 7: GPS Pseudo Range Error Projections [8]


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4.5. Conclusions The GPS technology – widely developed by automotive manufacturers and their suppliers – can make significant contributions towards the prevention of traffic accidents in dense traffic conditions. The GPS has proven to be very helpful by letting the driver know the prevailing conditions of the road, their level of awareness increase and the driver can be better prepared to face and to handle the situations along the road preventing accidents. The improvement of the GPS technology will allow a better description of road conditions, a continual decrease of error projection to help the driver to get a better idea of threading traffic situations and a diminish of the likelihood of an accident.

5. Anti-Sleeping System

5.1. Introduction The amount of people using the same road at the same time contributes to a sudden increase in the vehicles density in a determine road creating traffic congestions. Sleepiness and doziness are one of most common characteristics among the drivers immersed in heavy traffic conditions. It is more likely during rush hours for the drivers to feel tired and sleepy, hence decreasing their abilities to handle different traffic situations. In most of cities of the world, the congested traffic situations take place during the morning while most of the people go to work, to the school, or some other activities. The same phenomena can be observed during the evening while many people go back home. Driving is a skilled task which is to a large extent self-paced. However, it is a task which requires sustained awareness if accidents are to be avoided. It seems reasonable to hypothesise that sleepiness for those drivers affected is likely to result in impaired performance, so resulting in an increase in the risk of becoming involved in an accident. Since the circumstances giving rise to sleepiness and reactions to it will vary widely from person to person, it is likely that there will be large individual differences in both the experience of being sleepy and in the effect sleepiness has on the individual driver’s accident liability. The contribution of sleepiness to accident causation is difficult to establish, and studies which give reliable estimates are rare. Horne and Reyner (1995), report two accident studies in which they found that sleep was likely to be a contributory factor in between 16 and 23% of all accidents; they also found that the number of sleep related accidents was higher during the night and in the mid-afternoon than at other times of day. [15] One growing area of concern is fatigue-related crashes. In the United States, police have cited driver drowsiness/fatigue in an estimated 56,000 crashes annually, resulting in roughly 40,000 nonfatal injuries and 1,550 deaths, according to Drowsy Driving and Automobile Crashes, a report by NHTSA and the National Center on Sleep Disorders Research, National Heart, Lung, and Blood Institute. Young drivers – especially males – are overrepresented in fatigue-related crashes. Drivers younger than 30 make up one-fourth of licensed drivers but account for almost two-thirds of drowsy-driving crashes. These drivers are four times more likely to have such a crash than are drivers ages 30 years or older. NHTSA has found that males are five times more likely than females to be involved in drowsy driving crashes. [16]


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The Global Burden of Disease study estimated traffic injury to be the ninth leading cause of death and disability in the world in 1990, and projected it would be the third leading cause by 2020 [14]. In many countries, motor vehicle injury is the single biggest threat to life among young people. Several major reviews and commentaries have suggested that fatigue or sleepiness in car drivers increases the risk of crashing (American Thoracic Society, 1994; Dinges, 1995; Expert Panel on Driver Fatigue and Sleepiness, 1997), but none have systematically reviewed the epidemiological evidence. Estimates of the proportion of all crashes attributable to fatigue vary 10-fold, from 1-3% for the United States (American Medical Association, 1998), to 25% in Victoria, Australia (Naughton and Pierce, 1991) [14].

5.2. Counter measures of driver sleepiness Most of the people when they feel that they are following to sleep behind the steering wheel tend to do the following to counter the effects. The most popular countermeasures found in a study conducted in the United Kingdom were singing, eating, smoking, taking caffeine tablets, stopping and sleeping, washing one’s face, letting someone else drive, and putting the seat upright (and less comfortable). Clearly it is a popular conception that fresh air, taking a break and listening to the radio are effective in countering the consequences of sleepiness. [15] From the study described above, the following table showing the results can be drawn:

Remedial measures Percentage of those

responding to the question Opening the window for fresh air 68 Stopping and taking a walk 57 Listening to the radio 30 Talking to a passenger 25 Drinking coffee 14 Other 15

Table 2: Measures found helpful by drivers in countering the effects of sleepiness whilst driving [15]

Another helpful behaviours proposed in the United States for preventing drowsy driving include:

• planning to get sufficient sleep; • not drinking even small amounts of alcohol when sleepy; and • limiting driving between midnight and 6 a.m.

As soon as a driver becomes sleepy, the key behavioural step is to stop driving – for example, letting a passenger drive or stopping to sleep before continuing a trip. Two remedial actions can make a short-term difference in driving alertness: taking a short nap (about 15 to 20 minutes) and consuming caffeine equivalent to two cups of coffee. But, again, the best thing to do is to prevent drowsy driving in the first place. [16]


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5.3. Driver Sleepiness Warning Systems

5.3.1. The Awake Project in the European Union An European Union project focusing more particularly on the issue of how to utilize in-car information technology to help drivers maintain high vigilance while driving, is the AWAKE project. The AWAKE is a part of the IST programme of the European Commission. It started in September 2001, with a budget of over 6 million euros. The partners are major automotive system developers, research institutes, university institutes, and also immediate users, car manufacturers, and end users. The automotive system developers include Siemens VDO, Actia, Autoliv, and Navigation Technologies. The European research institutes include the Hellenic Institute of Transport HIT, TNO in the Netherlands, the Swedish Road and Transport Research Institute in Linköping, and ICCS, which is in Greece, the French institutes CNRS LAAS and CNRS-CEPA, CARA-BIVV in Brussels, and the Netherlands' Research School for Transport, Infrastructure and Logistics TRAIL. Then there are two universities, the University of Stuttgart and COAT Basel in Switzerland, and the car manufacturers Fiat in Italy and Daimler-Chrysler in Germany. The end users are the FIA (Fédération Internationale de l’Automobile) and the AIT (Alliance Internationale de Tourisme). The background of AWAKE is the large number of crashes that are due to driver drowsiness or fatigue. The target goals for the usability of the system are: - Reliability level over 90 % - False alarm rate below 1 % - User acceptance over 70 % - HMI perception rate over 90 %. The project has several specific aims regarding system development:

• To develop a multi-sensor system (eyelid camera, steering grip sensor, lane tracker, and other vehicle-related parameter monitoring sensors).

• To develop parallel stochastic and deterministic (knowledge-based) approaches.

• Extension of current diagnostic methods to take into account continuous diagnostic capabilities (incremental learning).

• On-line personalisation of the diagnostic algorithm. • Introduction of ambient intelligence to the diagnostic module according to the

traffic environment and the driver's attention to it (through gaze analysis). • Development of a warning strategy that combines acoustic, visual and haptic

elements and is parametric to drivers' vigilance state as well as to the estimated traffic situation. So it should take into account both the driving environment and the capacities of the driver.

• Parametric specifications (to match the particular preferences of the target user cohorts, i.e. young drivers, professional heavy vehicle drivers, shift workers and people suffering from sleep disorders).


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The following system components are supposed to achieve the goals of AWAKE:

• Hypo vigilance diagnosis module (HDM) • Traffic risk estimation module (TRE) • Driver warning system (DWS), using acoustic, visual and haptic means in

various levels of warnings according to inputs from the monitoring modules. • Hierarchical manager (HM) to perform self-diagnosis and co-ordinate the other

system components. The system includes environmental sensors (to detect rain, night, and fog and so on), vehicle sensors, and then the hypo vigilance sensors for the driver. There are connections between the traffic risk estimation module, the driving identification system, the hierarchical manager, and the hypo vigilance diagnosis module, and from these modules to the driver warning system, which is turned on if necessary to alert the driver. The HDM is a very important module because it has to detect and diagnose driver hypo vigilance in real time, based on an artificial intelligence algorithm. It fuses data from on-board driver monitoring sensors (eyelid and steering grip data) and data regarding the driver's behaviour (lane tracking, accelerator/brake and steering position data). It will be adapted to the specific driving characteristics of the user by continuous driver monitoring and expert-based adaptation. The traffic risk estimation module will assess the traffic situation and the involved risks. It matches, following a deterministic approach, data from an enhanced digital navigational map, a positioning system, anti-collision radar, an odometer, and a driver's gaze direction sensor. Its output is used by the HDM to re-assess the state of the driver, and by the driver warning system to determine the adequate level of warning. Then, finally, the driver warning system is to warn the driver safely and in time about his or her reduced vigilance according to the traffic situation, his or her hypo vigilance state, and the driver's type (for specific driver cohorts), and to effectively support the driver regarding the appropriate course of action and minimise the risk of information overflow in a critical situation. [17]

5.3.2. PERCLOS Technology in the United States The National Highway Traffic and Safety Administration (NHTSA) has been working for years toward developing an effective, validated drowsy-driver detection and warning system for use by commercial motor vehicle drivers (CMVs). Considerable progress has been made in measuring drowsiness and understanding its effects upon human performance in the laboratory and in simulated and operational driving conditions. A measure of drowsiness, PERCLOS, was generated and associated with degradation in driving performance in a simulated roadway environment. Studies of overnight commercial trucking operations resulted in a proof-of-concept prototype containing an infrared camera system and software capable of detecting drowsiness and issuing a warning real time in an operational setting. The challenge is to translate these findings into a fully functional prototype whose system design minimizes false alarms, addresses issues of effectiveness (accuracy, reliability,


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behavioural change), and reflects a user-centred approach to the interaction and interface. The interaction and interface design incorporates the drivers’ desire for a stimulating and alerting response with the researchers’ desire to encourage safe discussions between design and engineering team members. A secondary display shows time lapses between warnings, and total warnings received during a drive. Both are preceded by an auditory alert. [18]

Figure 8: PERCLOS prototype (Attention Technology Inc.)

5.4. Conclusions Even though falling to sleep behind the wheel in congested traffic conditions have not been considered as a top priority by technology developers, the accidents caused by the lack or a considerable decrease of driver’s alertness has very serious consequences, even fatal. Currently, the existent technologies are on early stages of development. The technologies explained above are big attempts to gather technological and scientific knowledge to achieve the development and eventual implementation of technologies that can monitor the physical symptoms of sleepiness, tiredness or drowsiness while driving. All these efforts are made to alert the driver and to prevent a potential accident with all its undesirable consequences.

6. Changing Lane

6.1. Introduction Changing lane is a manoeuvre that requires full attention from the driver, especially if done in a congestioned highway. He must be aware of the cars following in front of him as well as behind him, and this, in two lanes. Also the vehicles usually travel at different speeds in each lane, so the driver also needs to be aware of different speeds. The driver should look through the left rear view mirror or through the right rear view mirror to make sure no other vehicle is in the desired lane, make sure that the indicator light is on and then make the change. This apparently simple processes can be quite complex especially if made at high speeds.


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Problems may occur because of several reasons, one of the most common is the driver that can not see the other vehicle coming behind in the other lane, is in the blind spot! The rear view mirrors show a limited area. The mean horizontal limits of the fields of view for the driver-side, interior, and passenger-side mirrors are shown Fig.9. There is a large amount of overlap in the angles covered by the mirrors, with virtually the entire field of view of the interior mirror being represented in one of the exterior mirrors as well. The driver-side and interior mirrors are displaced almost symmetrically about 45 degrees from the driver’s forward line of sight, to the lower left and upper right, respectively. The passenger-side mirror is considerably further out, at about 65 degrees from the forward line of sight [19].

Figure 9: Rear Mirrors View Angle

The picture shows, that especially on rear sides, there is a considerable area that the driver can not see.

6.2. Eliminating Blind Spot A digital camera is fitted on each door mirror and takes a large number of frames a second. By comparing the picture frames, the system can register when a vehicle is moving into the monitored zone, which is 9.5 metres long and 3 metres wide. If another vehicle enters the monitored zone, a warning lamp lights up near the door mirror. So that the driver can have a clear indication that another vehicle is just by his side. Therefore he can not change lane now, see Fig. 10. The system alerts the driver both to vehicles approaching from behind and vehicles in front as they are overtaken, on both sides. The system is programmed to monitor cars as well as motorbikes, in both day and night conditions. It is also dimensioned not to react to parked cars, roadside fences, crash barriers, lampposts and so on. The system becomes active for speeds above 10 km/h. It is designed to alert the driver to vehicles that are moving a maximum of 20 km/h slower and a maximum of 70 km/h faster than the driver’s own vehicle [20].


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Figure 10: Blind Spot Detection

Another risk is due to the driver seeing the vehicle coming from behind but doesn’t evaluate the vehicle’s position and speed correctly. Or the vehicle following in front can break suddenly, and because the driver is “busy” looking to the other lane and the mirror may not react in time to avoid crash. If a vehicle in front (VIF) suddenly slows, a driver following a VIF at a constant and relatively short distance will see brake lights illuminate in conjunction with an immediate change in following distance and the pitch of the lead vehicle. However, when approaching a stopped or very slow vehicle on a high-speed road, brake lights may be visible, but they are not associated with other cues such as an immediate change in following distance or the pitch of the lead vehicle and the VIF may be too far away to be perceived as an immediate hazard in many circumstances [21], When there is a large difference in speed between the lead vehicle and following vehicle (greater than 15 mph), the potential danger and severity increases [21]. So the driver may not be able to safely judge the relative speed of a vehicle moving in the same direction. All this situations show that changing lane is a complex manoeuvre. However there are several systems that can diminish the risk. For example we suggest the combined use of ACC and blind spot detection (BSD). While The ACC makes sure that the driver does not collide with the vehicle following in front and the BSD makes sure that the driver will not run into the vehicle following at his side. Some drawbacks of this combination can be due to the fact that BSD only gives a warning. These type of warnings are likely to have previously unforeseen nuisance effects because drivers often start lane changes when there is another vehicle in the adjacent proximity area as they seem to anticipate longitudinal gap opening and closing [23]. If this is combined with the fact that when that gap comes, the driver will tend to accelerate to take the available space, The ACC can create a problem if breaks the car because of the vehicle following in front. So it is hard to predict the global performance of a system that will always have interaction and depend on human decision. The system has to be useful. Several drivers can interpret and use the information in different ways and sometimes not in best possible way.


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“None desired” lane changing, the driver accidentally enters the other lane. This can happen manly due to several reasons that can distract the driver. Any thing that requires the driver attention can interfere with the driving. The driving performance is better when performing tasks with the hands-free phone than with the Ventilation or AC and radio systems. There is approximately 55% less lateral position variability with the hands-free phone than when performing the Ventilation, AC and radio tasks [24]. Or severe lateral winds can also “push” the car out of its lane. Several systems are being developed to prevent this situation.

6.3. Lane Detection Sensor This sensor detects the brightness value of the ground and compares it to the left and right neighbors to understand whether the car goes out of the lane, the first phase of detection is to sense black and white. Citroen Is currently mass producing vehicles with a similar system AFIL, the system works only above 70 km/h. This system warns the driver when the bright lines are crossed by producing a vibration in the seat. One of the disadvantages is that the warning is given when part of the vehicle is already in the other lane, because the sensor is below the front bumper.

6.4. Lane Departure Warning System (LDW) The idea of LDW is to warn the driver if he or she is on the verge of inadvertently drifting out of the lane. Using a CMOS Camera and an image processing algorithm, this driver assistance system registers the course of the lane in relation to the vehicle. The system "sees", as it were, the course of the road and where the car is going. If the warning algorithm detects an imminent leaving of the current driving lane, the system warns the driver with haptic, kinestatic, or acoustical feedback. Possible warning alerts can be a trembling in the steering wheel, a vibrating seat or a virtual washboard sound (a noise people recognize as generated by driving over a lane marker at highway construction sites). Series production is planned for 2005 [26].

Figure 11: Rear Mirrors View Angle


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6.5. Active steering System Keeping the car in the lane without driver effort is one of the aims of the active steering system. A similar system is currently in use by BMW but nowadays the system only helps to keep the vehicle in a strait line avoiding constant steering wheel corrections on windy days for example. As a next step, the system becomes an active lane keeping assistant, combining the active steering with the lane keeping system. The system measures the vehicle position relative to the lane, but offers active support in keeping the vehicle to the lane. However, the driver always retains the driving initiative, meaning that although he can feel the recommended steering reaction as a gentle movement of the steering wheel, his own decision takes priority at all times [22].

6.6. Problems Some questions that can come for the future of this technology are:

• How much should or can the system “take decisions” on the direction? • Some drivers simply won’t accept to ”be corrected” especially in southern

Europe. Others may not like the way that the system actuates in case of irritating noises or vibrations.

• Because there are no perfect systems, legal issues can arise because if the system can actively take decisions than in case of accident could it be blamed? Could the driver it self blame the system?

• How should the system actuate? • Should the driver always have the last decision or in eminent collision should

the system take over? All these questions should be answered before have a full active steering system operating in mass production vehicles. Another system that can help to increase to safety to trucks when they intend to change lane is Lane Departure Warning [22]. The truck driver sometimes can not see what is on the right side of the truck so this kind of system would be a great help, because it would inform the driver when lane is clearly.

Figure 12: Lane Departure Warning


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7. Sensors Every active system in the vehicle needs Sensors, Controllers and Actuators. But sensors are also used in passive systems in this case the system only gives a warning to the driver. He will have to decide what to do, and how, according to each situation. The following section will focus on some of the modern sensors. They can be as simple as switches or as complex as active radar or sonar system.

7.1. Raining Sensor This sensor basically used to detect when rain starts to fall. When this happens the wipers are turned on without any driver interference. This can be particularly useful for congestioned highway. When travelling on a wet paved road the vehicle in front will produce a spray of water and dirty that will hit the front window of the car following behind. The amount of water will on speed and distance of the vehicles. With this kind of sensor the window will be clean without any concerns or distractions of the driver to adjust the wipers.

7.2. Light Sensor This is another simple but very useful sensor it can detect when the natural light conditions are not enough, and then the vehicle lights are turned on. This sensor can be particularly important for tunnels. In some tunnels the speed of circulation is quite high, in sunny days, the vehicle ahead can completely “disappear” to the vehicle coming from behind. It the sensor works properly the lights are immediately turned on. Making the car ”visible again” to the incoming vehicle.

7.3. Tire Monitoring Pressure The most frequent cause of a flat tire is a very gradual loss of air that goes unnoticed by the driver. With DDS (Deflation Detection System), a indirect measuring sensor, gives a warning signal when there is a decrease in tire pressure. DDS requires no extra sensor of its own but evaluates the data gathered via the wheel speed sensors. Any loss of pressure changes the radius of the tires, and results in a specific alteration of the speed signal. Another way of detecting Deflation is to use a small pressure sensor in the tire valve, this transmits to the receiver and the driver can constantly know the pressure of each wheel. This system is used for example by Renault.

7.4. Steering Angle Sensor Steering angle sensor is very simple, but is becoming more and more important. Several systems rely on this sensor like (ESP, suspension control, active steering etc.). The sensor consists of an encoder and a photo emitter, photo receiver and an optic disc (having opaque and transparent parts) between them. The receiver counts the signals it receives during turning and measures the turning angle. It is usually installed with other sensors such as steering torque, steering angle velocity sensor, steering wheel switches etc.


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7.5. Speed and acceleration sensors The fast and precise measuring of speed both longitudinal and rotational is very important because many systems rely on this information such as ESP, BAS, ASR, etc. The determination of speed is based upon anisotropic magneto-resistance (AMR) effect. It is found that for proper functioning the ESP (Electronic Stability Program) requires measures of the vehicle acceleration. So sensors to measure acceleration are needed, like Yaw rate sensor and Lateral Acceleration Sensor as well as longitudinal acceleration sensor. Some of these sensors are produced by different companies [25] a) Piezoelectric principle: A piezoelectric material is sandwiched between a mounting plate and a mass. When the mass is affected by a force generated by the acceleration, it transmits the force to the piezoelectric material. Piezoelectric materials generate an electric charge proportional to the force applied on it. [25] b) Capacitance principle: In capacitive sensing systems, a mass is inserted between two capacitive plates and voltage is applied to hold the mass in balance. When there is disturbance on the mass between the capacitive plates, a corresponding voltage change.

7.6. Brake sensor This system requires a simple but very useful sensor to measure the speed and the acceleration of the braking pedal. When the pedal is pressed with certain acceleration the system simply uses the maximum brake capacity this for some drivers can be the difference between crashing or not.

7.7. Closing Velocity Sensor Continental is developing new technologies for a future pre-crash sensor system based on a micro optical laser sensor Fig. 13. This involves the dynamic determination of the distance to an emerging obstacle as well as calculating the differential velocity with which the vehicle and obstacle are approaching each other. The detection and evaluation of the obstacle are both based on a highly precise laser runtime measurement. The scene is illuminated by a very short laser pulse. The pulses reflected by the object are recorded over PIN diodes [26]. The adaptive cruise control system can work based on two types of sensor [26]:

• Radar Technology Properties of one radar system: 77 GHz radar according to the pulse modulated Doppler principle for independent measurement of speed and distance Sharp beam focusing to separate objects

• Infrared signal Infrared technology is cheaper than radar so it is possible to use it also in middle class vehicles. And it also offers the possibility to improve safety in bad weather conditions. Allowing to estimate the actual visibility and suggesting the appropriate speed to the driver.

Figure 13


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7.8. Force Feedback Pedal (FFP) An interesting sensor system that is being developed by continental is the Force Feedback Pedal (FFP). The main idea is to provide information to the driver via the accelerator pedal. The information can be related to distance, speed limitations, cruise control and warnings. The FFP Fig. 14 consists of a common accelerator pedal (passive function), an electro-mechanical actuator and a control unit to generate an additional force at the pedal plate (active function). The passive function is to generate a counterforce to the driver's foot und transmit the position of the accelerator pedal to the engine control. It is represented by springs, hysteresis elements as well as a redundant sensor system and it exists always. The active function is the increase of the counterforce to the driver's foot and is realised by an electro-mechanical actuator, one sensor and a control unit. It is possible to perform a variable counterforce [26].

7.8.1. Possibilities The counterforce of FFP can be associated with the longitudinal guidance of the vehicle. The driver can have feedback about the current distance and speed situation without having to take the eyes of the road. Counterforce at the accelerator pedal when driver falls below the safety distance to ahead driving vehicle. Driver receives a feeling for the "virtual bumper" through the feedback of the accelerator pedal. The driver must have always the possibility to ignore the warnings [26].

8. Adaptive Cruise Control Adaptive cruise control was build on the functionalities of the cruise control system and, within certain system limits, maintains automatically the correct distance from the vehicle in front and enables the driver to automatically follow a slower preceding vehicle. The vehicle can automatically flow with other cars in a dense traffic while keeping a safe distance. The system uses a special radar sensor to measure the distance from the vehicle ahead. It allows the driver to set a following distance, or time interval, between the vehicle and the vehicle ahead, as well as a maximum speed (Figure 15). All ACC functions are operated with a multifunctional steering wheel with buttons dedicated to the ACC settings.

Figure 15: ACC specific instrument cluster

Figure 14


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Features of the ACC system [34]:

• Ability to track a car in the lane ahead using forward looking radar. If the distance to a vehicle in front is below a pre-set value, the ACC system is designed to slow the car down, using brakes if required, to track the speed of the vehicle in front,

• Then returning the car to its pre-set speed once the lane ahead is clear. • Intelligent lane prediction using steering angle and yaw rate sensors predict

curves in the road, and to ensure that any vehicle ahead being tracked is in the same lane as the car itself

• Links into the braking system through special actuator values to provide up to 20% of maximum vehicle braking force.

• Maintains consistent performance in poor visibility conditions (radar based ACC).

Adaptive cruise control is especially useful in dense highway traffic situations where the driver gets a new kind of support, making the task of fine tuning of both velocity and distance easier. It also reduces the driver’s workload and allows greater concentration on other driving tasks. The current ACC generation operates in a speed range from 30 km/h to 200 km/h and it is suited for use on highways and country roads.

1. Radar sensor control unit 2. ECU 3. Active brake control via ASR/ESP 4. Sensors 5. Control handles and display (HMI) 6. Engine interaction 7. Gearbox interaction

The main part of the ACC System is the Sensor Control Unit, a compact unit which houses the radar sensor and the control unit. It is located in the front part of the vehicle, usually under or behind the front bumper or just behind the grille (Figure 17).

Figure 17: Position of the sensor control unit [32]

Figure 16: Components of the ACC system [30]


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The radar sensor detects vehicles driving in front up to a distance of 150 meters, using three overlapping radar beams. These beams reflect off the vehicles ahead. The control unit calculates their speed and their distance from the owner's vehicle. The sensors of the Electronic Stability Program (ESP) supply information on the direction of travel, in order to select the relevant vehicles for the ACC. By controlling the engine and braking system, the ACC matches speed to the other vehicles. Once the road ahead is clear, the vehicle is allowed to accelerate up to the speed pre-selected by the driver. A sample block diagram for an adaptive system is shown on the figure 18.

Figure 18: A sample block diagram of ACC [33]

8.1. Range sensor units The detection of the vehicle ahead is done by the usage of either radar or lidar (laser-based analog to radar) sensor unit. Radar-based systems can see at least 150 meters ahead in fog or rain heavy enough to cut the driver's ability to see down to 10 meters or less. There is only a small degradation by fog and rain. Lidar, on the other hand, is less expensive to produce and easier to package but performs poorly in rain or snow. The light beams are narrower than water droplets or snowflakes, pushing down the signal-to-noise ratio thus restricting the usage of lidar in bad weather conditions, which is precisely when you need it most. Another problem is that, since the location is behind the grill, the accumulations of mud, dirt, dust, or snow on the car can block lidar beams. At present, only one manufacturer, Lexus, uses a laser-based ACC system, in its LS430 model. System engineers have acknowledged lidar's shortcomings and taken steps to make the system unavailable in situations where the weather may limit its effectiveness. The choice of radar or lidar depends on the manufacturers’ philosophy. Supporters of the laser-based systems insist that a collision-warning system should not work far beyond what the driver can see. They think it would encourage people to drive too fast in conditions of poor visibility and lead to crashes when the collision-warning system failed to detect an obstacle. Conversely, supporters of radar-based systems think that the driver needs the most help in conditions of poor visibility [29].


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8.2. Actuators Vehicle speed can be controlled by three different ways:

• Engine Control: it can be done by separate or integrated electronic throttle control (EGAS), combined throttle control with engine management, pneumatic or electric cruise control actuators or EDC systems for diesel engines.

• Transmission control: electronic transmission control in vehicles with automatic transmission. It is possible for the ACC to shift down to decelerate with the engine.

• Brake control: active brake control is based on the hydraulic systems for standard traction control or VDC and does not require a smart booster. It allows a quiet and comfortable deceleration control.

The ability to accelerate or decelerate, respectively, is limited to about ± 2 m/s2 (~0.2 g) for safety reasons and customer convenience [29].

8.3. Availability and price Current vehicle manufacturers that are offering adaptive cruise control systems are: Audi (2005 A8), BMW (2003–2005 7 Series and 2005 5 Series), General Motors (2003–2005 Cadillac XLR), Infiniti (2003–2005 Q45 and FX), Jaguar (2003–2005 XKR), Lexus (2001–2005 LS430), and Mercedes-Benz (2000–2005 S-Class and CL-Class, 2003–2005 E-Class and SL-Class). Radar sensors units cost in a range of 400 € till 550 € for OEMs to install near the front bumper, while the integrated package of warning features costs approximately 1500 € to 1900€.

8.4. Man-Machine interface In spite of all the technical aspects of ACC the driver will remain the master of the system retaining the full responsibility for driving the car. The driver has to activate, operate, supervise and, if necessary, intervene or switch off the ACC. He also selects the major control parameters set speed and set time gap.

8.5. Technical Limitations Technical limits for different radar sensor units are already explained. Limitations due to geometrical obstructions are characteristics for all autonomous ranging sensors today. Tops of the hills and bottoms of valleys naturally limit the longitudinal range. Other limitations arise from the difficulties in predicting the course far in front of the ACC equipped car. It is shown on figure 19.


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Figure 19: Lane prediction

This is mainly due to two reasons: 1) error in determining the actual value of the road curvature and 2) parts of the road with non-constant curvature. This problem is the most restrictive system limit to any ACC and matter of current research [28].

8.6. Future development of ACC In future, ACC will also be suited for use at speeds below 30 km/h and right down to standstill. This means it will be able to observe the preset distance from the car ahead even at very low speeds. In stop-and-go traffic it can then brake automatically right down to stopping and drive off again afterwards. Main limitation to achieve stop and go function is limitation of sensors and actuators. A potential advantage of ACC is the foundation that it provides for next generation advancements in lane detection systems that are expected to include cameras. The use of cameras in the vehicle is predicted to help provide for better lane following and collision avoidance by controlling the steering mechanism of the vehicle. Bosch is planning to extend ACC into a safety system as a part of a wider "Predictive Safety System". It means if ACC identifies a critical traffic situation, the brake pads will be made to lightly touch the brake discs and the brake servo unit set to respond to a possible emergency braking maneuver. If the driver does have to apply the brakes, vital fractions of second are won before the full braking force comes into effect. Further developmental stages of the Predictive Safety System will contain functions to warn the driver of the threat of collisions and even to undertake automatic emergency braking action [35].

8.7. Conclusion ACC is meant to be a comfort system, i.e. it aims to reduce the driver’s work load, with other words to increase comfort. It is not an active work load management system, which distributes work load to the driver according to the actual traffic situation. It must also be mentioned that ACC is not a safety system in the first place. This is due to the fact that the ACC’s operational range is limited both in velocity and acceleration/deceleration. Benefits of ACC [34]:

• Reduction in driver fatigue • Minimizes speed differentials between vehicles. • Reduces throttle and brake management. • Reduction in accident rate for vehicles fitted with collision avoidance type

systems


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• Increase in fuel efficiency due to very gradual speed increase / decrease in traffic

• Integrates easily with other vehicle systems. • Interconnection to more advanced future systems.

It is expected that the price of ACC systems will be reduced significantly, meaning that more people will be able to afford it and further opportunities for future extensions resulting in more safety and comfort. Further research in stop and go extension of ACC will benefit drivers in traffic jams on highways and in urban areas.

9. Brake Assist System Crash research studies by Mercedes and Toyota, found that although drivers reacted quickly in critical situations, they did not apply the brakes with sufficient force. More than 90 percent of the drivers who participated in the tests either could not make up their minds to brake with full force until it was too late, or simply reacted incorrectly. During an emergency, driver’s foot comes off the throttle and on to the brake pedal faster than normal, which you then depress with more urgency than usual. This is registered by on-board sensors. Next, a brake pedal load-sensing switch and speed sensor determine if you have braked hard enough. If not, the system instantly determines how much extra braking force is required and increases the hydraulic pressure in the braking system. Then the brake actuator distributes the extra braking force to all four wheels that will decrease the stopping distance. Brake force with and without brake assist is shown on figure 20. If the driver successfully avoids the danger and removes or reduces the force on the pedal then the system will also reduce its involvement.

Figure 20: Brake force vs. Brake pedal force [31]

9.1. Conclusion Brake Assist is based on the ABS technology of a vehicle and will not be found on a vehicle without ABS. It should not change how drivers respond to an emergency meaning that the driver should still brake as hard as possible. Brake assist system can significantly decrease the stopping distance thus helping the driver in the traffic congestion to stop the vehicle at the safe distance from the preceding car.


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10. Radio Communication

10.1. Introduction One of the newest techniques used, as Active Safety tool, is the radio communication between an on going car and the surrounding environment. This idea it is not new but only now, with the development of the computers and materials, is possible to implement this kind of devices in cars and at roadsides. The principle of this technique is to exchange information with surroundings in order to warn the vehicle’s driver of possible risk situations or possible traffic congestions on the road. This exchange of information can be done between the on board installed equipment in the vehicle and a fixed road’s equipment or a traffic information centers and, between the surrounding cars as well [44]. This communication it is possible having recourse to a fiber optical “IP” unit. This unit allows the exchange of several different data with high speed and joint of communication [39]. One of the most important worldwide projects, which are developing the radio communication on the ambit of the road transport concept, is the “Intelligent Transportations Systems” (ITS) that will be developed on the next section.

10.2. Intelligent Transportation Systems (ITS) ITS project started in Japan but it is spread to the entire world. The objective of this project is, using cutting edge communication technologies, to improve the road transport concept by developing the intelligent devices to help the driver on the hard job that is driving a car on an urban environment. In other words, ITS has been working on communication systems in order to provide the driver with as many as possible information about roads environment. ITS it is a project that consists of nine development areas with different areas. The areas, which are presented below, are only the areas that are related with radio communication [36], [37]:

• Advances in Navigations Systems • Electronic Tool Collection System

Figure 21: Improving safety Increasing(Improving) traffic efficiency Improving

comfortableness(convenience) Contributing to the preservation of enviroment Creating new industries/business; What is ITS? [36]


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10.3. Advances in Navigations Systems One of the most well known navigation systems is “Global Positioning System” (GPS). This system has incorporated also a “Vehicle Information and Communication System” (VICS). With this last system the driver can get road and traffic information, including information on traffic congestion. VICS can provide the driver with the expected time of a trip based on the traffic congestion or it can be also used to avoid traffic congestions, if the car is equipped with navigation system sufficiently powerful to determine routes to the driver destination [36].

10.3.1. Vehicle Information Positioning System (VICS) The principle of this system can be shown by figure 22. The way of VICS operate is quite simple for the users. It works with the collaboration of several traffic information centres (Highway administrators and police). The information from these “organizations” is gathered by the national road traffic road centre, which then transmits the information for the VICS centre. Although, the information on parking availability is transmitted directly to the VICS centre. On this centre, the information is processed, edited and provided to fixed roadside communication points (Radio beacons, Optical beacons and FM multiplex broadcasting). After this long process the information is finally transmitted to the cars on board devices. This information can be provided in three different levels [36]:

• Level 1: Character display type • Level 2: simple diagram display type • Level 3: map display type

Figure 22: VICS description [36]


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10.4. Information Sharing The information sharing has important role on the Vehicles Information and Communication Systems. As has been mentioned previously, there are three ways of sharing information:

• Radio beacons • Optical beacons • FM multiplex broadcasting

10.4.1. Radio Beacons On this method the information is transmitted by radio waves to the beacons and then this information is transmitted to the cars on radius of approximately 70 meters with a capacity of 64 Kbps, as is shown on figure 23 [38].

Figure 23: Information sharing through radio beacons [39]

10.4.2. Optical beacons It is method very similar to the Radio Beacons except on the way of transmitted the information to cars. These beacons are mainly installed before road interceptions and the information is transmitted by the cars sensors. These devices have a capacity of 1 Mbps and a range of 3,5 meters [38].

Figure 24: Information sharing through optical beacons [42]

10.4.3. FM multiplex broadcast This information sharing method is restricted by area of range of the broadcast. This means that the information it is only available on a determined area. However, the information can be shared through the FM broadcasts areas. So, in this model the information is sent by the local FM broadcasts [38].


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10.5. Types of information Depending of the type of the equipment installed in the vehicle, the information can be provided from three different types:

• Character display: the information is transmitted in text format. • Simple diagram display: the information transmitted is concerning the traffic

congestion. • Map display: the most informative of the three types. It provides to the drivers

with information about traffic congestions and allows them to choose the best route.

Notice that, these types of information are strongly dependent of the capabilities of the cars devices [36]. In the next section will be explained one of the most common techniques that allow the communication between the vehicle and its environment.

10.6. Dedicated Short Range Communication systems (DSRC) This technique is designated as a tool for the “Intelligent Transportation Systems”. These devices allow the bi-directional communication between the roads and the vehicles and also between the surroundings cars. DSRC is a communication service of short range. It is also called transceiver system [38].

Figure 25: DSRC in IST [38]

The “DSRC” system it is not a new system, but it has been improved and now it is an important tool for the “ITS”. The firsts “DSRC” systems used a frequency of 915 MHz. Nowadays, they use a 5,8 GHz frequency. There are important differences between the older and the newest systems. The table 3 summarizes these differences.


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Characteristics 915 MHz 5,8 GHz Range Less than 30 meters Up to 1000 meters Data rate 0,5 MBps 6 to 27 MBps Intended use ETC, but can be used for

other applications Internet access, can be used for ETC.

Channels Single unlicensed channel 7 licensed channels

Implementation Requires special (custom) chip set & software

Uses open off-the-shelf chip sets and software

Table 3: Differences between the different types of DSRC [41]

Depending of the communication, “DSRC” can be divided in two types that will be developed on the next section.

10.7. Road to Vehicle Communication (RVC) As been said before the road to vehicle communication is done it by wireless systems situated a long the road and the vehicle. There are four types of RVC systems, depending of the area and direction of communication [38]:

1. Broadcasting type: It is a widespread supply of the different information through FM transmission.

2. Localized simulcasting: The information is supplied through an on-way communication in a limited area.

3. Wide-area individual communications: Two-way communications system that use of wide-area (e.g. car phones) for collection of road transport information.

4. Localized individual communications: Two-way communications in a localized zone; two types: intermittent and continuous (cf. figure 25).

10.8. Inter Vehicle Communication (IVC) This system uses the radio communication in order to communicate with the surrounding vehicles. It allows the sharing of control data as speed, acceleration, etc., as well as the information that other vehicles receive. Due to its characteristics it allow also what is called “Platooning”, which allows a specific group of vehicles to keep in touch with each other constantly [38], [44]. On figure 26 it is shown an example of the two applications of this system.

Figure 25: Intermittent and continuous communication [40]


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Figure 26: Inter Vehicle Communication [40]

Adding a camera to the inter vehicle systems, it is possible to provide a better communication between a specific group of vehicles. Therefore, it can receive incident information and traffic jam information by picture [40]. Moreover, the IVC can be used to warn the drivers of hazards at intersections and curves with poor visibility [43]. The “DSRC” can be combined with other devices in order to avoid traffic congestions. On the next section an example of one system that uses one of the possible combinations between systems, the “Electronic Toll Collection” will be presented.

10.9. Electronic Toll Collection (ETC) The worldwide spread traffic congestion problem is also due to the tollgates situated near the big cities. This became a problem mainly on cities where the drivers have to stop to pay a certain amount of money. In order to avoid these kind of congestions, the ETC it’s a permit the automatic payment of drivers without stopping. Therefore, this system is used in order to reduce the traffic congestion on the tollgates. This system requires an on board device that transmit and receive information to the roadside unit. Within this device has to be incorporated a card, which has to be valid for the correct transaction. Automatically, the money is removed from the on board card. This system has a frequency of 5,8 GHz [38], [44]. Other reason why this system is becoming so popular it’s the save of money in costs of operation.


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Figure 27: ETC [40]

ETC systems and DSRC together are also used on the parking lots. This combination avoids the long cues that are created by users of the, for example, the subterraneous parking lots. This system is already in use on one of the countries with more problems of traffic congestions: Japan [36].

10.10. Research and development All of these systems are capable of offering the driver many information about roads environment and it is more and more necessary to have some help from the car itself to driver for instance in a urban environment. But, the recent systems are becoming more complex due to fusion of the different technologies (systems). Several developments have been done to combine the IVC and the “Adaptive Cruise Control” (ACC) systems [44]. This fusion produces a more autonomous vehicle, which can take decisions itself. However, the merging procedure must be done in order to provide as many as possible information to driver. But one of the main concerns is how the driver will react to the information that he gets. This must be a research subject to be sure that the information is well used or if instead of avoid accidents we are increasing them. This problem can be very hard to solve because it is complicate to guess the reactions of a human being. Moreover, all the systems have to be implemented in corporation of states, which can delay even more all procedure.

10.11. Conclusions The different communication systems of ITS are already being used in Japan with very good results. They are becoming an essential instrument to avoid congestions and accidents. Recent studies show that the number of VICS sold in Japan until December of 2004 has reached 11.1 million units, which shows that is a good investment area, at least in Japan [36]. However, the implementation of these systems needs a careful analysis, planning and monitoring [39] and, as been mentioned before, the driver reactions to the several information has to be taken into consideration.


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11. Computer Vision for Driving Assistance

11.1. Introduction Modern vehicles will not just recover information of their internal driving state but also from their environment surroundings. The idea that future will pass through intelligent vehicles capable of autonomous driving, where drivers just have to choose if the car will assume or not the control is becoming stronger and there is a lot of research going on this direction. The active safety field has having a fast development over the last years and the tendency is to continue this progress, there for is of primary importance that the systems in use today will be possible to update in order to keep them useful in the future. The system presented in this section, computer vision seems to be promising once does not require extra facilities on the road and the idea that cars will have their own eyes is becoming a reality and no any other sensor can provide so much information about the vehicle environment. Cameras can be used for several different purposes in cars. They can be mounted in strategic points to improve the driver visibility and to eliminate blind spots.

Figure 27: Warning for pedestrians

Once enhancement vision is strongly dependent on the computational power available to process the video data in an efficient way, computer vision technique as a complement of intelligent cruise control is just giving the first steps. Lane detection, frontal and side obstacle detection, pedestrian detection, vehicle recognition, parking manoeuvres, night vision and driver monitoring are some of the applications of this system, and its capacities will grow with computers evolution. Most of these applications can be very attractive to develop an Intelligent Stop and Go system for traffic congestion situations, collecting information like [45]:

• Detect the leading vehicle and estimate its distance, speed and accelerations; • Detect stationary obstacles that limit the available free space, such as parked

cars; • Detect and classify different additional traffic participants, such as

pedestrians; • Detect and recognize small traffic signs and traffic lights in a complex

environment;


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• Extract the lane course, even if it lacks well-painted markings and does not show a well defined geometry.

Due to traffic congestion characteristics, the driver is subjected to high levels of stress and noise, and the amount of information is also higher for such conditions. So the human-machine interface is of major importance, because this interface will affect the way how the driver will react to the information received. A display combined with a sonorous signal for very high risk situations seems to be the most appropriated human-machine interface for a computer vision system. The evaluation of such systems is made considering the following criteria [46]:

• Salience in low ambient illumination; • Salience in high ambient illumination; • Salience in high ambient noise; • Attention getting properties; • Visibility from multiple locations; • Usability if eyes are busy; • Ability to display graphics; • Ability to display same object in multiple colours; • Space required; • Operability over desired temperature range; • Flexibility of formatting.

Another requisite is to avoid repetitive warnings when there is no effective risk and to make sure that this interface will not be annoying and irritant for the driver, otherwise the driver will just turn it off and the system will not have acceptance and this is an important advantage of vision based systems, to avoid false alarms.

11.2. Principles The vision based driver assistance system receive its environment information by camera, this data is processed and displayed to the driver. The system includes a stereo vision a framework and side and backwards cameras to give a complete description of the vehicle surroundings. The stereo vision is a system for driver assistance that requires a 3D map of the environment in front of the car tat include position, and motion of other traffic participants and mainly potential obstacles.

Figure 28: Stereo vision


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The framework is used for monocular detection and recognition of relevant object, roughly this system consists in a camera that captures the image, then these images are processed in a central processing unit and finally the information is presented to the driver in a certain format. The vision based systems are defined as passive sensors and have an advantage over laser and radar sensors, the data acquisition is a none invasive way, thus not changing the environment. One of the most important parameter for a successful system is the way how to identify the objects. Two kind of objects are distinguished, infrastructure elements and traffic participants. Normally there are applied three steps when recognizing these objects, detection, tracking and classification. The first step, detection, is mainly to obtain a region of interest (ROI), where the computer detects a region in the image that is a potential object. The methods to detect and select a ROI are based on depth from stereo, shape and colour. The following step after the region of interest selection is the tracking step, at this stage, the objects are tracked and analysed in the different frames to estimate their motion and to improve the system. The last step is the object recognition, here the object classification is made, based on training procedure (it learns from examples, instead of relying on programmed models).

11.3. Applications

11.3.1. Lane detection For lane detection, the system has to perform a lane marking recognition, then a mathematical estimation of the lane is computed and the system estimate the vehicle position relatively to the lane and automatically is kept in the lane [45] [47]. Usually two basic problems are faced when doing the lane marking detection;

• The presence of shadows and road texture changed. This problems use to be solved using a highly sophisticated image filtering algorithms.

• Other vehicles covers partially the path and lane markings. To face this problem some systems just investigate a small part of the road ahead of the vehicle where the absence of other vehicle can be assumed Limitations The system does not fit large features, the ROI choice is decisive, does not match roads with variable lane width, and requires high computational power and fails if the road does not match the model.

11.3.2. Pedestrian detection Pedestrian detection [49] is big challenge, once people have unpredictable behaviours. Stereo vision, shape detection and tracking have been combined in different ways trying to make pedestrian detection possible. The common approach is to divide the


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process in two steps. First, the image is divided in foreground and background regions, then the system detects if the foreground region is a pedestrian or not, warning the driver in case of collision risk

Limitations Does not recognize standing pedestrians, limited to pedestrians crossing the path of the vehicle and needs analysis of image sequence.

11.3.3. Night vision This application is to improve the driver vision in poor visibility and dark conditions. Three systems were developed, the Ultraviolet, the Near Infra-Red [48] and the Thermal Imaging or Far Infra-Red. Full beams UV headlamps beside ordinary headlamps are used in this system and to work properly the road users and infrastructures has to have fluorescent materials under UV light. The Near Infra-Red system like the UV system, requires a full beam infra-red headlamp beside the normal headlights this infra-read headlamps are mounted with 45 degree angle to avoid dazzling the cameras of the oncoming vehicles. The infra-red light is reflected and received by an infra-red sensitive camera, the signal obtained is then processed and presented to the driver The Thermal Imaging or Far Infra-red is a passive system that does not require any extra headlamps, just an infra-red camera in the front to receive the infra-red energy emitted by objects of different temperatures. Limitations The UV system installation on vehicles is relatively cheap, but requires a very expensive infrastructure investment. The Near Infra-Red system is sensitive to the weather conditions.

11.3.4. Driver monitoring A significant number of accidents are caused sleepy, inattentive and fatigued drivers because of their reduced attention, and most of these accidents are very severe resulting in fatality. Active risk management system [50] for occupant safety as the purpose of developing a robust, economic and non-intrusive driver vigilance monitoring system with other safety systems.

Figure 29: Pedestrian detection


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A computer vision and other non-intrusive sensors will be used to understand the state of the driver and warning him in case of unvigilant state detected giving to the driver enough time to recover and take control of the vehicle. In the future the driver monitoring system will assume a partial control (as lane following) in case in case of unvigilant state. This system will relate the driver state with the vehicle dynamics to design a closed loop control when the risk arises.

12. Conclusion Look at this project, the team has been able to collect and present some of the most important information and technologies regarding the accidents that may happen in congested traffic situations. It is important to notice that the technologies presented in this paper are only some examples of the existent devices or technologies. In other cases, the descriptions presented above are referring to technologies that their development is still going on. During the research we have found that there are many areas regarding the accident avoidance that can still be fully developed. We have encountered as well some limitations and restrictions about these technologies. One of them is the likeliness of having all this technologies and warning to the driver without annoy him or her. The problem of traffic congestion and associated collisions of varying severity was addressed throughout this paper. First we defined traffic congestions and identified what types of accidents are of particular interest. The primary aim was to find solutions to reduce the number of injured and killed people in these accidents. To do that we tried to summarise the state of the art in technical solutions that have been, or are being, developed to deal with this problem. The technologies discussed were GPS (Global Positioning System), Anti Sleeping System, Changing Lane, Brake Assistance, Adaptive Cruise Control, Sensors, Radio Communication, Computer Vision for Driving Assistance. Each of them was explained in terms of the technology involved, the current limitations, what it is should be expected for the future and certain facts represent the usefulness of all these technologies.

Figure 2: Active risk management system


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[32] www.i-car.com [33] www.bmwworld.com [34] www.visteon.com [35] www.bosch.com [36] Japanese Ministry of Land, Infrastructure and transport: Intelligent transportation System, http://www.mlit.go.jp/road/ITS/ [37] Munaka, T; Yamamoto, T; Kuroda, M.; Watanabe, T.: Location dependent data multicasting in intelligent transportation system and its evaluation; Transportation Research Part C 11 (2003), p. 355–373, 2003 [38] Faculty of Science and Technology, Keio University ITS lectures: http://www.its-lectures.ae.keio.ac.jp/english/05_1020/1020Be.html [39] European Transport Safety Council: Intelligent Transportation Systems and Road Safety, 1999, http://www.etsc.be/documents/systems.pdf [40] Oki Electric: ITS, http://www.oki.com/jp/SSC/ITS/eng/OKI_activity_all.pdf [41] Institute of Electrical and Electronics Engineers, Inc., http://grouper.ieee.org/groups/scc32/dsrc/faq/index.html [42] The Asahi Shimbum: Optical beacons, http://www.asahi-net.or.jp/~CG7Y-OONS/hikari.jpg [43] Daihatsu Co : Technologies, http://www.daihatsu.com/technology/its/intelligence/07/index.html [44] Bergqvist, Marcus ; Cerci, Tekin ; Feghali, Jean-Louis ; Godefroy, Guillaume F. H. ; Keller, Alexander ; Mohd, Rehan : Traffic congestion and associated collisions, p.6-10, 2004 [45] Uwe Franke, Dariu Gavrila, Axel Gern, Steffen Görzig, Reinhard Janssen, Frank Paetzol and Christian Wöhler: Intelligent vehicle technologies, Principles and applications of computer vision for driver assistant systems [46] Yilin Zhao: Vehicle Location and Navigation Systems, 1997 [47] Massimo Bertozzi, Alberto Broggi, MassimoCellario, Alessandra Fascioli, Paolo Lombardi, Marco Porta: Artificial Vision in Road Vehicles [48] U. Franke, D. Gavrila, Autonomous Driving approaches Downtown, IEEE Intelligent Systems, vol .13, nr. 6, 1999. [49] Universidad Carlos III De Madrid: http://www.uc3m.es/uc3m/dpto/IN/dpin04/ISL/Asistentur_eng.html


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[50] Pinar Boyraz: Active Risk Management System for Occupant Safety, 2004

Documents

Traffic congestions and associated collisionswebfiles.ita.chalmers.se/~mys/ActiveSafety05/ProjectReports05/Group1.pdfProject Group 1: Traffic congestions MMF320 Active Safety 4 2