| Autor: |
Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Journal of Advanced Transportation, Vol 2022 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2042-3195 |
| DOI: |
10.1155/2022/1550015 |
| Popis: |
Multiaccess edge computing (MEC) and connected vehicle (CV) technologies have shown great potential and strength for traffic perception and real-time computing, which can be applied to enhance the efficiency of connected transit bus operations under their lower penetration conditions. Moreover, for the transit signal priority system, how to establish a model to measure traffic demand for conflicting priority request resolution and improve system response time has been widely researched for the last few decades. This paper proposes a dynamic priority weight (DPW) model for connected transit buses and a traffic signal control approach to coordinate multidirectional conflicting priority requests at a signalized intersection. The proposed model takes advantage of vehicle location, speed, and signal timing data to build time to change (TTOC) correlation functions to measure priority weights of both single-vehicle and directionality accumulation with consideration of vehicles arriving during the current green phase and conflict phase conditions; then, the aggregated priority weight value of each movement can be calculated in real-time. Once the maximum aggregated priority weight value among all movements is determined, the corresponding phase switch strategy is presented for the conflicting request resolution control problem. Homologous algorithm software for distributed deployment can be subsequently used for swift response. Simulation results show that the proposed DPW model-based traffic signal control method shows significant performance advancement, where the queueing vehicle number decrease exceeds 1 pcu/s and the throughput rate of major movements increases by approximately 2% without sacrificing the performance of minor movements in a large amount. What is more, it shows better delay optimization for social vehicles than the algorithm with delay as the objective while declining bus delay appreciable quantity with 43.4 s in average. Field test results also show that this method has excellent abilities to improve intersectional traffic capacity, for which queueing vehicle number and throughput rate indicators of all phases dramatically improved with 1.92 pcu/s and 6.68% on average, except for a slight degradation of individual minor traffic movements with 0.99 pcu/s and 0.11%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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