TY  - JOUR
PY  - 2023//
TI  - Arterial signal offset optimization using crowdsourced speed data
JO  - Transportation research record
A1  - Xia, Liang
A1  - Li, Xiaofeng
A1  - Shaon, Mohammad Razaur Rahman
A1  - Wu, Yao-Jan
A1  - Jiang, Xinguo
SP  - 1633
EP  - 1642
VL  - 2677
IS  - 2
N2  - Signal offset for coordinated traffic signal control is traditionally optimized based on posted speed limit, free-flow speed, or average speed among intersections, without considering the variations of travel speed. Variation in travel speed caused by interference on arterials may lead to inaccurate offset estimation, reducing the efficiency of coordination control. Therefore, this study develops an arterial offset optimization method for traffic signal coordination control using real-time speed collected from high-resolution crowdsourced data. The objective of the proposed method is to minimize the average delay on the corridor. The optimization problem is formulated as integer programming, and a genetic algorithm (GA) is utilized to search for the best offset solution. The proposed method is evaluated on a major arterial (Speedway Boulevard) in Tucson, Arizona. In the numerical exercise, the effectiveness and performance of the proposed method are evaluated in various scenarios, including a scenario with non-recurring congestion. The results show that using high-resolution real-time speed data can reduce travel delay time in a coordinated direction by 32.5% and 17.6% when compared with methods using speed limit and free-flow speed, respectively, and the proposed method is more reliable and robust for handling traffic conditions with varying volume and speed.<p />  <p>Language: en</p>
LA  - en
SN  - 0361-1981
UR  - http://dx.doi.org/10.1177/03611981221109177
ID  - ref1
ER  -