Abstract
Traffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low, thus V2X based TSC systems need to be supported by some other mechanisms. PR is the major factor that affects the quality of TSC process along with the evaluation interval. Quality of the TSC in each direction is a function of overall TSC quality of an intersection. Hence, quality evaluation of each direction should follow the evaluation of the overall intersection. Computational intelligence, more specifically swarm algorithm, has been recently used in this field in a European Framework Program FP7 supported project called COLOMBO. In this paper, using COLOMBO framework, further investigations have been done and two new methodologies using simple and fuzzy logic have been proposed. To evaluate the performance of our proposed methods, a comparison with COLOMBOs approach has been realized. The results reveal that TSC problem can be solved as a logical problem rather than an optimization problem. Performance of the proposed approaches is good enough to be suggested for future work under realistic scenarios even under low PR.
Highlights
Traffic signal control can be self-organizing and adaptable to traffic condition changes by using vehicular ad hoc network (VANET) technology and an intelligent control algorithm
In order to select a suitable policy, a large number of parameters need to be appropriately set by COLOMBO framework to achieve best possible performance
We propose to follow Partial Penetration Rate (PPR)-based approach for Traffic signal control (TSC) design with different strategy
Summary
Traffic signal control can be self-organizing and adaptable to traffic condition changes by using vehicular ad hoc network (VANET) technology and an intelligent control algorithm. VANET technology provides extensive information of approaching vehicles for an intersection. Vehicles frequently transmit specific messages (e.g., basic safety message (BSM) in United States (US), or cooperative awareness message (CAM) in European countries (EU)), containing all required relevant information A traditional method to acquire data from VANETs is to receive messages with a central infrastructure called roadside unit (RSU). RSU extract the most important information that is suitable for TSC. This extraction depends on the message’s information and what does it represent (i.e., traffic monitoring). Controlling an intersection through TSC required an algorithm that can deal with the RSU’s information sufficiently
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