Integrated route guidance and ramp metering consistent with drivers' en-route diversion behaviour

2011 ◽  
Vol 5 (4) ◽  
pp. 267-276 ◽  
Author(s):  
T.D. Xu ◽  
L.J. Sun ◽  
Z.R. Peng ◽  
Y. Hao
2014 ◽  
Vol 111 ◽  
pp. 1102-1111 ◽  
Author(s):  
A. Spiliopoulou ◽  
M. Kontorinaki ◽  
I. Papamichail ◽  
M. Papageorgiou

Author(s):  
Tiandong Xu ◽  
Yuan Hao

This work aims to provide effective and reliable traffic guidance strategies for improving the system performance and travel reliability, wherein the drivers’ route diversion behavior is the key determinant in these strategies. This study presents a novel modeling framework that can incorporate the dynamic driver behavior into a real-time group route guidance model based on dynamic origin–destination demand estimation and prediction (DODE) for information-based active traffic management. Experiments are conducted to test the effectiveness of the proposed model on the basis of the traffic dataset of the Route Guidance Pilot Project. Experimental results show that the effect of route diversion on DODE under information provision, which can improve the accuracy of DODE, must be considered. Compared with the traditional guidance model, the proposed model considers the system objective and the actual route diversion behavior and can provide better performance and ensure system sustainability.


2020 ◽  
Author(s):  
Fatemeh Alimardani ◽  
Nilesh Suriyarachchi ◽  
Faizan M. Tariq ◽  
John S. Baras

Connected and automated vehicles (CAVs) have seen a rapid surge in interest over the past few years. A lot of focus is being placed on improving the efficiency and robustness of transportation systems by leveraging the sensors and capabilities of CAVs. However, the integration of CAVs into existing traffic infrastructure would give rise to certain issues that must be addressed before the CAVs can be seen ubiquitously on public roads. Since the highway networks are considered permanent investments that are expensive to build and maintain, the priority is to improve the efficiency of the current traffic system. This chapter explores the integration of two of the most common traffic management strategies, namely, ramp metering (RM) and route guidance (RG), into existing highway networks with human-driven vehicles (HDVs). The introduction of CAVs to public roads will engender issues pertaining to safe interactions between CAVs and HDVs. The later part of the chapter addresses the specific problems of improving highway on-ramp merging efficiency by optimally coordinating CAVs. The chapter concludes by presenting a scenario that requires an explicit consideration of interactions between HDVs and CAVs.


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