A multi‐source data‐driven traffic control approach is developed to alleviate traffic overload at bottleneck road segments. In the proposed approach, the high‐penetration feature of mobile‐phone signalling data and the real‐time feature of taxi global‐positioning‐system data are combined to simulate traffic flows in the road network of Shenzhen, a major city of southern China. The road intersections for implementing traffic control schemes are selected by locating the major vehicle sources of the bottleneck road segments, and a genetic algorithm was used to solve the dynamic traffic control schemes. Two important bottleneck road segments in Shenzhen were used as case studies to test the effectiveness of the proposed approach. The authors also propose a method to calibrate the simulated traffic flows when traffic count data are available in the future.
Traffic control approach based on multi‐source data fusion
IET Intelligent Transport Systems ; 13 , 5 ; 764-772
2019-05-01
9 pages
Article (Journal)
Electronic Resource
English
traffic control , real‐time feature , genetic algorithms , traffic flows , multisource data‐driven traffic control approach , multisource data fusion , mobile‐phone signalling data , road traffic , simulated traffic , traffic overload , vehicle sources , taxi global‐positioning‐system data , traffic engineering computing , important bottleneck road segments , sensor fusion , high‐penetration feature , dynamic traffic control schemes , road intersections , road network , road vehicles , telecommunication traffic , traffic count data
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