Optimization of signal coordination for closely spaced intersections

Shu, Aibing; Fu, Qiang; Liu, Dongbo; Dai, Leilei

doi:10.1109/ictis.2017.8047713

Cited by 4 publications

(2 citation statements)

References 1 publication

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“…Spillbacks can also be observed when the separation between Chapter 1. Introduction densely packed intersections is small (< 170 m [50]) and when the lights are locally managed without considering the flow of traffic at upstream intersections. Hence, controlling traffic flow in accordance to changing traffic conditions and queue lengths is key to avoid spillbacks, reduce congestion, and improve the overall trip time of the vehicles.…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Server Based Approach for Safe and Timely Intersection Crossings

Oza

Chantem

2019

2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

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Safe and efficient traffic control remains a challenging task with the continued increase in the number of vehicles, especially in urban areas. This manuscript focuses on traffic control at intersections, since urban roads with closely spaced intersections are often prone to queue spillbacks, which disrupt traffic flows across the entire network and increase congestion.While various intelligent traffic control solutions exist for autonomous systems, they are not applicable to or ineffective against human-operated vehicles or mixed traffic. On the other hand, existing approaches to manage intersections with human-operated vehicles, cannot adequately adjust to dynamic traffic conditions. This manuscript presents a technologyagnostic adaptive real-time server based approach to dynamically determine signal timings at an intersection based on changing traffic conditions and queue lengths (i.e., wait times) to minimize, if not eliminate, spillbacks without unnecessarily increasing delays associated with intersection crossings. We also provide timeliness guarantee bounds by analyzing the travel time delays, hence making our approach more dependable and predictable. The proposed approach was validated in simulations and on a realistic hardware testbed with robots mimicking human driving behaviors. Compared to the pre-timed traffic control and an adaptive scheduling based traffic control, our algorithm is able to avoid spillbacks under highly dynamic traffic conditions and improve the average crossing delay in most cases by 10-50%. (GENERAL AUDIENCE ABSTRACT)Safe and efficient traffic control remains a challenging task with the continued increase in the number of vehicles, especially in urban areas. This manuscript focuses on traffic control at intersections, since urban roads with closely spaced intersections are often prone to congestion that blocks other intersection upstream, which disrupt traffic flows across the entire network. While various intelligent traffic control solutions exist for autonomous systems, they are not applicable to or ineffective against human-operated vehicles or mixed traffic. On the other hand, existing approaches to manage intersections with human-operated vehicles, cannot adequately adjust to dynamic traffic conditions. This work presents a technologyagnostic adaptive approach to dynamically determine signal timings at an intersection based on changing traffic conditions and queue lengths (i.e., wait times) to minimize, if not eliminate, spillbacks without unnecessarily increasing delays associated with intersection crossings. We also provide theoretical bounds to guarantee the performance of our approach in terms of the travel delays that may incur on the vehicles in the system, hence making our approach more dependable and predictable. The proposed approach was validated in simulations and on a realistic hardware testbed which uses robots to mimic human driving behaviour in an urban environment. Comparisons with widely deployed and state-of-the-art traffic control techniques show that our ...

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Section: Introductionmentioning

confidence: 99%

A Real-Time Server Based Approach for Safe and Timely Intersection Crossings

Oza

Chantem

2019

2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

View full text Add to dashboard Cite

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“…For recurrent congestion, many existing studies have assumed that the bottleneck capacity is given (e.g., for closely spaced intersections, corridors, and networks). Shu et al ( 16 ) proposed an effective synchronous control strategy for vehicles turning left from an upstream intersection and for those that are stopped between two closely spaced intersections. Li et al ( 17 ) formulated the signal coordination control problem as a general two-stage stochastic program and proposed a reliability-based gradient solution algorithm.…”

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confidence: 99%

Adaptive Signal Control for Overflow Prevention at Isolated Intersections Based on Fuzzy Control

Yao

Zhang

Zhao

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Nonrecurrent congestion on urban roads may cause overflow, possibly leading to gridlock at intersections. Signal control is one of the most important measures to prevent such phenomena. For nonrecurrent congestion with uncertain bottleneck capacity, however, existing signal control methods have mainly adopted the strategy of cutting off the green signal of the overflow movement while the release priority of green time has not been considered. Consequently, the green time allocated to overflow movements is too long, aggravating overflow and congestion. Therefore, a signal control method is proposed to prevent overflow caused by uncertain bottleneck capacity. The proposed method extends existing real-time adaptive signal control to explicitly consider the risk of queue spillover. When an overflow risk is detected, the green times of overflow movements will be reassigned using fuzzy control to determine the release priority depending on the queue length and red time. Numerical studies were conducted for two scenarios with different downstream bottleneck capacities. The results demonstrate that the proposed method not only outperforms existing methods in respect of intersection efficiency but also reduces the risk of overflow. The proposed method achieves a 27.7% to 33.8% reduction in the maximum queue length of overflow movements compared with a traditional adaptive signal control method and a 10.9% to 11.0% decrease compared with a modified signal control method with a cutting-off strategy. The sensitivity analysis indicates that the average delay resulting from the proposed method is 51.1% and 18.0% less than the delays resulting from the traditional and modified methods, respectively.

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