Assessing the mobility benefits of proactive optimal variable speed limit control during recurrent and non-recurrent congestion

2015 ◽  
Vol 42 (7) ◽  
pp. 477-489 ◽  
Author(s):  
Ying Luo ◽  
M. Hadiuzzaman ◽  
Jie Fang ◽  
Tony Z. Qiu

Over the past few decades, several active traffic control methods have been proposed to improve freeway efficiency at bottleneck locations. Variable speed limit (VSL) is one of these effective controls. Previous studies have evaluated VSL control, but primarily during recurrent congestion only. This study focuses on evaluating the performance of VSL control for both recurrent and non-recurrent congestion. To assess the effectiveness of a previously proposed VSL control in a real-world situation, this study has three evaluation objectives: (1) examine the control performance when recurrent and (or) non-recurrent congestion occurs; (2) assess the effectiveness of the control when a queue encounters the VSL sign; and (3) consider the impact of system detection delay in VSL control. Comparative experiments for Whitemud Drive in Edmonton, Alberta, Canada, are simulated in the VISSIM platform, and traffic performance is compared among scenarios with and without control. The simulation results show that VSL improves mobility for both recurrent and non-recurrent congestion. The VSL control reduces total travel time, and improves total travel distance and total flow. Furthermore, it slows down the shockwave propagation speed, improves the average speed on most of the freeway segments, and reduces the duration of traffic recovery.

2021 ◽  
Vol 11 (6) ◽  
pp. 2574
Author(s):  
Filip Vrbanić ◽  
Edouard Ivanjko ◽  
Krešimir Kušić ◽  
Dino Čakija

The trend of increasing traffic demand is causing congestion on existing urban roads, including urban motorways, resulting in a decrease in Level of Service (LoS) and safety, and an increase in fuel consumption. Lack of space and non-compliance with cities’ sustainable urban plans prevent the expansion of new transport infrastructure in some urban areas. To alleviate the aforementioned problems, appropriate solutions come from the domain of Intelligent Transportation Systems by implementing traffic control services. Those services include Variable Speed Limit (VSL) and Ramp Metering (RM) for urban motorways. VSL reduces the speed of incoming vehicles to a bottleneck area, and RM limits the inflow through on-ramps. In addition, with the increasing development of Autonomous Vehicles (AVs) and Connected AVs (CAVs), new opportunities for traffic control are emerging. VSL and RM can reduce traffic congestion on urban motorways, especially so in the case of mixed traffic flows where AVs and CAVs can fully comply with the control system output. Currently, there is no existing overview of control algorithms and applications for VSL and RM in mixed traffic flows. Therefore, we present a comprehensive survey of VSL and RM control algorithms including the most recent reinforcement learning-based approaches. Best practices for mixed traffic flow control are summarized and new viewpoints and future research directions are presented, including an overview of the currently open research questions.


Author(s):  
Xiao-Yun Lu ◽  
Pravin Varaiya ◽  
Roberto Horowitz ◽  
Dongyan Su ◽  
Steven E. Shladover

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