Dr. Essam almasri Traffic Management and Control (ENGC 6340) 9. Microscopic Traffic Modeling 9. Microscopic Traffic Modeling

Dr. Essam almasriTraffic Management and Control (ENGC 6340)

9. Microscopic Traffic Modeling9. Microscopic Traffic Modeling


Traffic model classification Traffic model classification (1)(1) StaticStatic

– Models average steady-state traffic situationModels average steady-state traffic situation

DynamicDynamic– Models Models changes over timechanges over time of the traffic situation of the traffic situation

7:00 10:00 15:00 18:00

Dynamic

Static


Traffic model classification (2)Traffic model classification (2)

Different levels of detail in Different levels of detail in simulation simulation models:models:– Macroscopic:Macroscopic:

» Like water flowing through a pipeLike water flowing through a pipe

– MesoscopicMesoscopic» Individual vehicles with aggregate behaviourIndividual vehicles with aggregate behaviour

– MicroscopicMicroscopic» Individual vehicles with detailed behaviourIndividual vehicles with detailed behaviour


Traffic model classification (3)Traffic model classification (3)

Other dimensions:Other dimensions:– Stochastic or DeterministicStochastic or Deterministic::

» stochasticstochastic modelling captures variation in e.g. modelling captures variation in e.g. reaction time, arrival processes, route choice. reaction time, arrival processes, route choice. But But every simulation run results in different outcome, so every simulation run results in different outcome, so you need to you need to replicate simulation runsreplicate simulation runs

– Time-stepped or event-based:Time-stepped or event-based:» Time steppedTime stepped: the model calculates the changes in : the model calculates the changes in

the system for finite steps (e.g. 1 second)the system for finite steps (e.g. 1 second)» event based:event based: the model calculates changes in the the model calculates changes in the

system when something ’happens’ (events)system when something ’happens’ (events)


Introduction to micro-simulationIntroduction to micro-simulation

““A numerical technique for A numerical technique for conducting experiments on a digital conducting experiments on a digital computer, which maycomputer, which may…… involve involve mathematical models that describe mathematical models that describe the behaviour of a transportation the behaviour of a transportation system over extended periods of system over extended periods of time.time.””


Keywords:Keywords:

System:System: the real-world process to imitate; the real-world process to imitate; Model:Model: the set of assumptions, in the the set of assumptions, in the

form of mathematical or logical form of mathematical or logical relationships, put forward to help relationships, put forward to help understand how the corresponding system understand how the corresponding system behaves;behaves;

Entities:Entities: people or vehicles that act in the people or vehicles that act in the system;system;

Time:Time: an explicit element of the system. an explicit element of the system.


Traffic micro-simulation entitiesTraffic micro-simulation entities

Driver and vehicle characteristics.Driver and vehicle characteristics.– Physical size: Physical size: length and widthlength and width

– Mechanical capacity: Mechanical capacity: maximum maximum acceleration or decelerationacceleration or deceleration

– Driving behaviour: Driving behaviour: desired speed, reaction desired speed, reaction time, gap acceptance, aggressiveness, etc.time, gap acceptance, aggressiveness, etc.


Traffic micro-simulation modelsTraffic micro-simulation models

Car-following modelCar-following model Lane-changing modelLane-changing model Gap-acceptance modelGap-acceptance model Lane-choice modelLane-choice model Models of intersection controlsModels of intersection controls


Microscopic models?Microscopic models?microscopic

Longitudinal:• choosing free speed • interacting with other

vehicles and obstacles

Lateral:

• lane-changing

• others, such as behaviour at discontinuities


Car-following modelsCar-following models

Models of individual vehicle following Models of individual vehicle following behaviourbehaviour

– In a single stream of traffic (lane disciplined)In a single stream of traffic (lane disciplined)– No overtakingNo overtaking

Three main types:Three main types:– Safety-distance modelSafety-distance model– ““Action-pointsAction-points””: different rules for different : different rules for different

driving statesdriving states– Psycho-physical: Psycho-physical:

Acceleration=Stimulus x SensitivityAcceleration=Stimulus x Sensitivity


Gap-acceptance modelsGap-acceptance models Models of individual drivers’ choice of safety Models of individual drivers’ choice of safety

gaps to merge into or to cross other traffic gaps to merge into or to cross other traffic streams streams

Two elements:Two elements:– Gaps acceptable to driversGaps acceptable to drivers– Gaps available to the driverGaps available to the driver


Lane-changing modelsLane-changing models

Models of individual driversModels of individual drivers ’’ ability and ability and propensity to change lanespropensity to change lanes

Lane-changing objectives, e.g.Lane-changing objectives, e.g.– To overtake a slower moving vehicleTo overtake a slower moving vehicle– To bypass an obstacleTo bypass an obstacle– To move off/into a reserved bus laneTo move off/into a reserved bus lane– To get-in-lane for next junction turningTo get-in-lane for next junction turning– To giveway to merging trafficTo giveway to merging traffic

Decision-making behaviour:Decision-making behaviour:– Is it possible to change lane? (physically & safely) Is it possible to change lane? (physically & safely) – Is it necessary to change lane? (for junction turning?)Is it necessary to change lane? (for junction turning?)– Is it desirable to change lane? (to overtake?)Is it desirable to change lane? (to overtake?)


Lane-choice modelsLane-choice models

Selection of the lateral position in Selection of the lateral position in entering or traversing a link.entering or traversing a link.

Pre-specified, orPre-specified, or

Instantaneous choice made in Instantaneous choice made in response to traffic condition and response to traffic condition and destinationdestination


Models of intersection traffic controlModels of intersection traffic control

Signal controlled: Signal controlled: fixed or responsivefixed or responsive Priority givewayPriority giveway Roundabout: Roundabout: partially signalisedpartially signalised Motorway merge Motorway merge Stop-and-go Stop-and-go Giveway to oncoming trafficGiveway to oncoming traffic


Network representationNetwork representation

Network topologyNetwork topology Junction type and priority rulesJunction type and priority rules Link (major/minor, speed limits, ..)Link (major/minor, speed limits, ..) Lanes (turning restriction, access restriction)Lanes (turning restriction, access restriction) Signal plans (stages, phases, responsive rules)Signal plans (stages, phases, responsive rules)


Car-following modelsCar-following models

Safety Distance model

Gipps ModelGipps Model


The Gipps car-following modelThe Gipps car-following model

Free flow modelFree flow model– Accelerate freely to desired Accelerate freely to desired

speedspeed

Safety-distance modelSafety-distance model– Driver maintains a speed Driver maintains a speed vv

which will just allow him to which will just allow him to stop in emergency without stop in emergency without hitting the obstacle at distance hitting the obstacle at distance SS ahead ahead

Ld

vTvS

2

2

Gipps' First Car Following Model (v(0)=0,Vn=20m/s, an=1.7m/s/s, T=1sec)

0

5

10

15

20

25

0 5 10 15 20 25 30 35

Time (second)

Sp

ee

d v

(t)

(m/s

)


- Free flow:

• Free flow model

This model states that the maximum speed to which a vehicle (n) can accelerate in free flow condition during a time period (t, t+T)


- Safety-distance:

• Safety-distance modelthe other hand, the maximum speed that the same vehicle (n) can reach during the same time interval (t, t+T) according to its own characteristics and the limitations imposed by the presence of the leader vehicle is:

n-1 n


• Desired speed

• Finding the desired speed of the vehicle (n) ( V*(n) )

( V*(n) ) = min (V(sect), V(max) )

Where:V(sect) = section speed limitV(max) = maximum vehicle speed


In any case, the definitive speed for vehicle n during time interval (t, t+T) is the minimum of those previously defined speeds:

• The modeled speed

T hen, the position of vehicle n inside the current lane is updated taking this speed into the movement equation:


Stimulus - response models

Psycho-physical:


Stimulus – response modelsStimulus response model:

response(t+T )=sensitivity(t)×stimulus(t)r

Acceleration follower (af)

• Speed difference (Δv)

• Distance between cars (Δx)

• Speed of the following car (vf)


Root models af (t+Tr) =Chandler,

Herman and Montroll

Gazis, Herman and Potts

Edie

1c Δv(t)

2

Δv(t)c

x(t)

3 f r

Δv(t)c v (t+T )

Δx(t)

Stimulus Response modelsGazis-Herman-Rothery (GHR) model

( )* ( )*

( )m rn l

r

v t Tc v t

x t T

GHR-model

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Dr. Essam almasri Traffic Management and Control (ENGC 6340) 9. Microscopic Traffic Modeling 9. Microscopic Traffic Modeling