Reduction Perspective Mdlin -Dorin in Pop op Autom omati tion - - PowerPoint PPT Presentation

▶
reduction perspective
SMART_READER_LITE
LIVE PREVIEW

Reduction Perspective Mdlin -Dorin in Pop op Autom omati tion - - PowerPoint PPT Presentation

Jan 18, 2024 187 likes •360 views

In International l Con onference Engin ineerin ing Technologie ies an and Com omputer Sci cience: In Innovation an and Appli lication (EnT-2020 2020), ), Jun June 24-27 (O (October 6-8) 8), Moscow - Sa Sain int-Petersburg, g, Ru

slide-1
SLIDE 1

Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective

In International l Con

  • nference Engin

ineerin ing Technologie ies an and Com

  • mputer Sci

cience: In Innovation an and Appli lication (EnT-2020 2020), ), Jun June 24-27 (O (October 6-8) 8), Moscow - Sa Sain int-Petersburg, g, Ru Russia

Mădălin-Dorin in Pop

  • p

Autom

  • mati

tion and Applied Infor

  • rmati

tics De Depart rtment t Poli

  • litehnica Univers

rsity of

  • f Timișoara

Timișoara, , Rom

  • mânia

mad adalinpop20@gmail.com

slide-2
SLIDE 2

2

Objectives

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

slide-3
SLIDE 3

3

In Intersections Confi figuration Meth thods → Uncontrolled In Intersections Configuration

  • characterized by the lack of traffic signals
  • r 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

  • verloaded.

Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020

slide-4
SLIDE 4

4

In Intersections Confi figuration Meth thods → Sig ignalized In Intersections Coordination - Traffic Li Lights

  • solves the problem of gridlock mentioned

as disadvantage of previous coordination method in case

  • f
  • verloaded

road networks;

  • the

reduction

  • f

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

slide-5
SLIDE 5

5

In Intersections Confi figuration Meth thods → Sig ignalized In Intersections Coordination - Traffic Li Lights

Base ased on

  • n stop lin

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

slide-6
SLIDE 6

6

In Intersections Confi figuration Meth thods → Sig ignalized In Intersections Coordination - Traffic Li Lights

Base ased on

  • n lan

lane connectors:

  • highlights the possible directions that can be reached, taking into account the current lane
  • f 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

slide-7
SLIDE 7

7

In Intersections Confi figuration Meth thods → 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

slide-8
SLIDE 8

8

In Intersections Confi figuration Meth thods → Agent-Based Modeling – AnyLogic Simulation Environment

Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020

Symbol Na Name Si Significance CarSource Creates the cars and attaches the coordinates according to a specified location. Car arrivals can be defined using the arrival rate, interarrival rate, etc. CarMoveTo Is used for car movement management. The destination can be a stop line, a road, parking place etc. If the movement to a specified destination is not possible, the car can be routed to a destination specified using port onWayNotFound. CarDispose Eliminates a car from the road network. TrafficLight Controls the movement of vehicles using the stop lines or lane connectors by associating the timing for each color signal. This block ensures the simulation of traffic light behavior.

slide-9
SLIDE 9

9

Four-Way In Intersection – A Case Stu tudy of f Circumvalațiunii In Intersection (Timișoara - Romania) )

  • Significance of represented four-way intersection components:
  • 𝑡𝑗, 𝑗 = 1,4 - stop lines;
  • 𝑃1… 𝑃4- origin nodes;
  • 𝐸1… 𝐸4- 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

slide-10
SLIDE 10

10

Traffic Sim imulation Model – A Case Stu tudy of f Circumvalațiunii In 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

slide-11
SLIDE 11

11

Traffic Sim imulation Model – A Case Stu tudy of f Circumvalațiunii In Intersection (Timișoara - Romania) )

  • Route choice probabilities:

Mădălin-Dorin Pop / Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective / EnT-2020

Ori rigin in nod

  • des

De Destin ination nod

  • des

Open Vill ille Cetății Bou

  • ule

levard Jiu Jiul Pas assage Gh Gheorghe Di Dima Str Street Open Vill ille 0.05 0.15 0.65 0.15 Cetății Bou

  • ule

levard 0.55 0.05 0.20 0.20 Jiu Jiul Pas assage 0.70 0.05 0.05 0.20 Gh Gheorghe Di Dima Str Street 0.60 0.05 0.25 0.10

slide-12
SLIDE 12

12

Traffic Sim imulation Results – A Case Stu tudy of f Circumvalațiunii In 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

Con

  • nfiguration typ

type Travel tim time Nu Number of

  • f

vehic icles Min in (s) (s) Max (s) (s) Mean (s) (s) Uncontroll lled in intersection 14.074 793.007 251.933 174 Traffic lig lights – stop lin lines 14.060 445.112 93.050 453 Traffic lig lights – lan lane connectors 19.240 339.611 89.113 460 Roundabout 14.017 298.157 82.078 476

slide-13
SLIDE 13

13

Conclusions

Purp rpose:

  • identify the most appropriate decision of intersection configuration method based on

specific intersection case study. Con

  • ntributions:
  • 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

slide-14
SLIDE 14

14

References

[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

slide-15
SLIDE 15

15

References

[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

  • n 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

slide-16
SLIDE 16

Decision Making in Road Traffic Coordination Methods: A Travel Time Reduction Perspective

In International l Con

  • nference Engin

ineerin ing Technologie ies an and Com

  • mputer Sci

cience: In Innovation an and Appli lication (EnT-2020 2020), ), Jun June 24-27 (O (October 6-8) 8), Moscow - Sa Sain int-Petersburg, g, Ru Russia

Mădălin-Dorin in Pop

  • p

Autom

  • mati

tion and Applied Infor

  • rmati

tics De Depart rtment t Poli

  • litehnica Univers

rsity of

  • f Timișoara

Timișoara, , Rom

  • mânia

mad adalinpop20@gmail.com

Questions?