Upload
others
View
2
Download
0
Embed Size (px)
Citation preview
Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective
International Conference Engineering Technologies and Computer Science: Innovation and Application (EnT-2020), June 24-27 (October 6-8), Moscow - Saint-Petersburg, Russia
Mădălin-Dorin Pop Automation and Applied Informatics
Department Politehnica University of Timișoara
Timișoara, Româ[email protected]
2Objectives
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
Overview of related works
Overview of intersections
configuration methods
Analysis of a real intersection
properties
Study of travel time and number of
vehicles for different intersection
configuration methods
Identify the most
appropriate intersection
configuration method
3Intersections Configuration Methods → Uncontrolled Intersections Configuration
• characterized by the lack of traffic signals
or signs for traffic flow control;
• vehicles flow through these intersections
done by applying the priority-to-the-right
rule;
• this type of configuration method can lead
to gridlock if the road network becomes
overloaded.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
4Intersections Configuration Methods → Signalized Intersections Coordination - Traffic Lights
• solves the problem of gridlock mentioned
as disadvantage of previous coordination
method in case of overloaded road
networks;
• the reduction of traffic congestion
depends on the green intervals setting;
• two modes of traffic lights configuration:
• based on stop lines;
• based on lane connectors.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
5Intersections Configuration Methods → Signalized Intersections Coordination - Traffic Lights
Based on stop lines:
• all vehicles from the lanes affected by the red traffic light shall wait for the green light,
independent of the direction chosen to leave the intersection;
• priority-to-the-right rule applies for left turn.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
6Intersections Configuration Methods → Signalized Intersections Coordination - Traffic Lights
Based on lane connectors:
• highlights the possible directions that can be reached, taking into account the current lane
of the studied vehicle;
• advantage - the additional
green time that can be
given to the vehicles that
are turning right.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
7Intersections Configuration Methods → Roundabouts
• one-way circular lanes that have entry
points for vehicles coming from several
directions;
• the movement of vehicles entering a
roundabout is conditioned by giving
priority to the vehicles already present in
the roundabout.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
8Intersections Configuration Methods → Agent-Based Modeling – AnyLogic Simulation Environment
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
Symbol Name Significance
CarSourceCreates the cars and attaches the coordinates according to aspecified location. Car arrivals can be defined using the arrivalrate, interarrival rate, etc.
CarMoveTo
Is used for car movement management. The destination can bea stop line, a road, parking place etc. If the movement to aspecified destination is not possible, the car can be routed to adestination specified using port onWayNotFound.
CarDispose Eliminates a car from the road network.
TrafficLightControls the movement of vehicles using the stop lines or laneconnectors by associating the timing for each color signal. Thisblock ensures the simulation of traffic light behavior.
9Four-Way Intersection – A Case Study of Circumvalațiunii Intersection (Timișoara - Romania)
• Significance of represented four-way intersection components:
• 𝑠𝑖 , 𝑖 = 1,4 - stop lines;
• 𝑂1… 𝑂4- origin nodes;
• 𝐷1… 𝐷4- destination nodes
• The nodes from the simulated road network are:
• Open Ville (top);
• Cetății Boulevard (left);
• Jiul Passage (bottom);
• Gheorghe Dima Street (right).
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
10Traffic Simulation Model – A Case Study of Circumvalațiunii Intersection (Timișoara - Romania)
• Traffic Model for the vehicles starting from Open Ville):
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
11Traffic Simulation Model – A Case Study of Circumvalațiunii Intersection (Timișoara - Romania)
• Route choice probabilities:
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
Origin nodesDestination nodes
Open VilleCetății
BoulevardJiul Passage
Gheorghe Dima Street
Open Ville 0.05 0.15 0.65 0.15
CetățiiBoulevard
0.55 0.05 0.20 0.20
Jiul Passage 0.70 0.05 0.05 0.20
Gheorghe Dima Street
0.60 0.05 0.25 0.10
12Traffic Simulation Results – A Case Study of Circumvalațiunii Intersection (Timișoara - Romania)
• Travel time and number of vehicles for different intersection configuration methods:
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
Configuration typeTravel time Number of
vehiclesMin (s) Max (s) Mean (s)
Uncontrolled intersection
14.074 793.007 251.933 174
Traffic lights – stop lines
14.060 445.112 93.050 453
Traffic lights – lane connectors
19.240 339.611 89.113 460
Roundabout 14.017 298.157 82.078 476
13Conclusions
Purpose:
• identify the most appropriate decision of intersection configuration method based on
specific intersection case study.
Contributions:
• overview of related works regarding the intersections configuration methods;
• present a case study of real intersection;
• show the impact of intersections configuration methods on reducing the travel time,
increasing the number of vehicles crossing the road network and, implicitly, reducing
traffic congestion.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
14References[1] M.-D. Pop, “Traffic Lights Management Using Optimization Tool,” Procedia - Social and Behavioral Sciences, vol. 238, pp. 323–330, 2018, doi: 10.1016/j.sbspro.2018.04.008.
[2] E. Budreyko and V. Joklova, “Innovative Digital Tools for Ecological Approaches in Urban Design in Slovak Context”, in 2018 International Conference on
Engineering Technologies and Computer Science (EnT), Moscow, Russia, Mar. 2018, pp. 101–105, doi: 10.1109/EnT.2018.00029.
[3] O. Dib, M.-A. Manier, and L. Moalic, “Advanced modeling approach for computing multicriteria shortest paths in multimodal transportation networks,” in 2016
IEEE International Conference on Intelligent Transportation Engineering (ICITE), Singapore, Singapore, Aug. 2016, pp. 40–44, doi: 10.1109/ICITE.2016.7581304.
[4] B. Khelifa, M. R. Laouar, and S. Eom, “Towards an Intelligent Integrated System for Urban Planning Using GIS and Cloud Computing,” in Decision Support Systems VIII: Sustainable Data-Driven and Evidence-Based Decision Support, vol. 313, F. Dargam, P. Delias, I. Linden, and B. Mareschal, Eds. Cham: Springer International Publishing, 2018, pp. 26–37.
[5] G. Myrovali, T. Karakasidis, A. Charakopoulos, P. Tzenos, M. Morfoulaki, and G. Aifadopoulou, “Exploiting the Knowledge of Dynamics, Correlations and Causalities
in the Performance of Different Road Paths for Enhancing Urban Transport Management,” in Decision Support Systems IX: Main Developments and Future Trends,
vol. 348, P. S. A. Freitas, F. Dargam, and J. M. Moreno, Eds. Cham: Springer International Publishing, 2019, pp. 28–40.
[6] N. M. Abid and S. S. Hussain, “Transportation network planning using simulation: Case study\ Al Mansour city,” in 2017 2nd IEEE International Conference on
Intelligent Transportation Engineering (ICITE), Singapore, Singapore, Sep. 2017, pp. 272–279, doi: 10.1109/ICITE.2017.8056923.
[7] G. Merkuryeva and V. Bolshakovs, “Vehicle Schedule Simulation with AnyLogic,” in 2010 12th International Conference on Computer Modelling and Simulation,
Mar. 2010, pp. 169–174, doi: 10.1109/UKSIM.2010.38.
[8] Xiaobing Li, A. J. Khattak, and A. G. Kohls, “Signal phase timing impact on traffic delay and queue length-a intersection case study,” in 2016 Winter Simulation
Conference (WSC), Washington, DC, USA, Dec. 2016, pp. 3722–3723, doi: 10.1109/WSC.2016.7822418.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
15References[9] T. Yu and J. Ma, “A review of the link traffic time estimation of urban traffic,” in 2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE), Singapore, Singapore, Aug. 2016, pp. 123–127, doi: 10.1109/ICITE.2016.7581319.
[10] Grigoryev, I.: AnyLogic 7 in three days: a quick course in simulation modeling. (2016), pp. 3.
[11] Online resource: Road traffic library, https://help.anylogic.com/index.jsp , last accessed 2020/05/03.
[12] Surjandy, F. Anindra, H. Soeparno, and T. A. Napitupulu, “CCTV traffic congestion analysis at Pejompongan using case based reasoning,” in 2018 International
Conference on Information and Communications Technology (ICOIACT), Yogyakarta, Mar. 2018, pp. 861–865, doi: 10.1109/ICOIACT.2018.8350807.
[13] Y. Liu and H. Wu, “Prediction of Road Traffic Congestion Based on Random Forest,” in 2017 10th International Symposium on Computational Intelligence and
Design (ISCID), Hangzhou, Dec. 2017, pp. 361–364, doi: 10.1109/ISCID.2017.216.
[14] M. Khalil, J. Li, A. Sharif, and J. Khan, “Traffic congestion detection by use of satellites view,” in 2017 14th International Computer Conference on Wavelet Active
Media Technology and Information Processing (ICCWAMTIP), Chengdu, Dec. 2017, pp. 278–280, doi: 10.1109/ICCWAMTIP.2017.8301495.
[15] D. Fiedler, M. Cap, and M. Certicky, “Impact of mobility-on-demand on traffic congestion: Simulation-based study,” in 2017 IEEE 20th International Conference
on Intelligent Transportation Systems (ITSC), Yokohama, Oct. 2017, pp. 1–6, doi: 10.1109/ITSC.2017.8317830.
[16] H.-J. Bungartz, S. Zimmer, M. Buchholz, and D. Pflüger, “Stochastic Traffic Simulation,” in Modeling and Simulation, Berlin, Heidelberg: Springer Berlin
Heidelberg, 2014, pp. 203–238.
[17] W. Bernhard and P. Portmann, “Traffic simulation of roundabouts in Switzerland,” in 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165),
Orlando, FL, USA, 2000, vol. 2, pp. 1148–1153, doi: 10.1109/WSC.2000.899078.
Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020
Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective
International Conference Engineering Technologies and Computer Science: Innovation and Application (EnT-2020), June 24-27 (October 6-8), Moscow - Saint-Petersburg, Russia
Mădălin-Dorin Pop Automation and Applied Informatics
Department Politehnica University of Timișoara
Timișoara, Româ[email protected]
Questions?