IDEAS home Printed from https://ideas.repec.org/r/eee/transb/v24y1990i6p471-495.html

Dynamic modeling, assignment, and route guidance in traffic networks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Du, Lili & Han, Lanshan & Li, Xiang-Yang, 2014. "Distributed coordinated in-vehicle online routing using mixed-strategy congestion game," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 1-17.
  2. B. G. Heydecker & J. D. Addison, 2005. "Analysis of Dynamic Traffic Equilibrium with Departure Time Choice," Transportation Science, INFORMS, vol. 39(1), pages 39-57, February.
  3. Raphaël Lamotte & André de Palma & Nikolas Geroliminis, 2016. "Sharing the road: the economics of autonomous vehicles," Working Papers hal-01281425, HAL.
  4. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
  5. Yildirimoglu, Mehmet & Geroliminis, Nikolas, 2014. "Approximating dynamic equilibrium conditions with macroscopic fundamental diagrams," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 186-200.
  6. Wang, Jiawen & Zou, Linzhi & Zhao, Jing & Wang, Xinwei, 2024. "Dynamic capacity drop propagation in incident-affected networks: Traffic state modeling with SIS-CTM," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
  7. Zhou, Bo & Song, Qiankun & Zhao, Zhenjiang & Liu, Tangzhi, 2020. "A reinforcement learning scheme for the equilibrium of the in-vehicle route choice problem based on congestion game," Applied Mathematics and Computation, Elsevier, vol. 371(C).
  8. Jin, Wen-Long & Zhang, H. Michael, 2013. "An instantaneous kinematic wave theory of diverging traffic," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 1-16.
  9. Han, Sangjin, 2007. "A route-based solution algorithm for dynamic user equilibrium assignments," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1094-1113, December.
  10. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
  11. Alvarez, Luis & Horowitz, Roberto, 1997. "Safe Platooning In Automated Highway Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1v97t5w1, Institute of Transportation Studies, UC Berkeley.
  12. Li, Pengfei & Mirchandani, Pitu & Zhou, Xuesong, 2015. "Solving simultaneous route guidance and traffic signal optimization problem using space-phase-time hypernetwork," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 103-130.
  13. Yu, Hao & Ma, Rui & Zhang, H. Michael, 2018. "Optimal traffic signal control under dynamic user equilibrium and link constraints in a general network," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 302-325.
  14. Jin, Wen-Long, 2012. "A kinematic wave theory of multi-commodity network traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 1000-1022.
  15. Y. Ge & B. Sun & H. Zhang & W. Szeto & Xizhao Zhou, 2015. "A Comparison of Dynamic User Optimal States with Zero, Fixed and Variable Tolerances," Networks and Spatial Economics, Springer, vol. 15(3), pages 583-598, September.
  16. Sheu, Jiuh-Biing, 2006. "A composite traffic flow modeling approach for incident-responsive network traffic assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 461-478.
  17. Apostolos Kotsialos, 2010. "A hydrodynamic modelling framework for production networks," Computational Management Science, Springer, vol. 7(1), pages 61-83, January.
  18. Lam, William H. K. & Huang, Hai-Jun, 1995. "Dynamic user optimal traffic assignment model for many to one travel demand," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 243-259, August.
  19. Wen-Long Jin, 2015. "Analysis of Kinematic Waves Arising in Diverging Traffic Flow Models," Transportation Science, INFORMS, vol. 49(1), pages 28-45, February.
  20. Bellei, Giuseppe & Gentile, Guido & Papola, Natale, 2005. "A within-day dynamic traffic assignment model for urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 39(1), pages 1-29, January.
  21. Jin, Wen-Long, 2010. "Continuous kinematic wave models of merging traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1084-1103, September.
  22. Long, Jiancheng & Szeto, W.Y. & Gao, Ziyou & Huang, Hai-Jun & Shi, Qin, 2016. "The nonlinear equation system approach to solving dynamic user optimal simultaneous route and departure time choice problems," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 179-206.
  23. Kotsialos, Apostolos & Papageorgiou, Markos, 2004. "Motorway network traffic control systems," European Journal of Operational Research, Elsevier, vol. 152(2), pages 321-333, January.
  24. Kachroo, Pushkin & Özbay, Kaan, 1998. "Solution to the user equilibrium dynamic traffic routing problem using feedback linearization," Transportation Research Part B: Methodological, Elsevier, vol. 32(5), pages 343-360, June.
  25. Ozbay, Kaan & Bartin, Bekir, 2004. "Estimation Of Economic Impact Of Vms Route Guidance Using Microsimulation," Research in Transportation Economics, Elsevier, vol. 8(1), pages 215-241, January.
  26. Zhong, Shiquan & Zhou, Lizhen & Ma, Shoufeng & Jia, Ning, 2012. "Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1490-1505.
  27. Olaf Jahn & Rolf H. Möhring & Andreas S. Schulz & Nicolás E. Stier-Moses, 2005. "System-Optimal Routing of Traffic Flows with User Constraints in Networks with Congestion," Operations Research, INFORMS, vol. 53(4), pages 600-616, August.
  28. Angelelli, E. & Arsik, I. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2016. "Proactive route guidance to avoid congestion," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 1-21.
  29. S H Melouk & B B Keskin & C Armbrester & M Anderson, 2011. "A simulation optimization-based decision support tool for mitigating traffic congestion," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(11), pages 1971-1982, November.
  30. Jahn, Olaf & Möhring, Rolf & Schulz, Andreas & Stier Moses, Nicolás, 2004. "System-Optimal Routing of Traffic Flows with User Constraints in Networks with Congestion," Working papers 4394-02, Massachusetts Institute of Technology (MIT), Sloan School of Management.
  31. Angelelli, E. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2021. "System optimal routing of traffic flows with user constraints using linear programming," European Journal of Operational Research, Elsevier, vol. 293(3), pages 863-879.
  32. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2020. "Macroscopic fundamental diagram based perimeter control considering dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 87-109.
  33. Zhang, Siyao & Fu, Daocheng & Liang, Wenzhe & Zhang, Zhao & Yu, Bin & Cai, Pinlong & Yao, Baozhen, 2024. "TrafficGPT: Viewing, processing and interacting with traffic foundation models," Transport Policy, Elsevier, vol. 150(C), pages 95-105.
  34. Du, Lili & Han, Lanshan & Chen, Shuwei, 2015. "Coordinated online in-vehicle routing balancing user optimality and system optimality through information perturbation," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 121-133.
  35. Jin, Wen-Long, 2009. "Asymptotic traffic dynamics arising in diverge-merge networks with two intermediate links," Transportation Research Part B: Methodological, Elsevier, vol. 43(5), pages 575-595, June.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.