Two-Stage Transit Signal Priority Control Method to Improve Reliability of Bus Operation Considering Stochastic Process
mode - bus, infrastructure - bus/tram priority, infrastructure - station, infrastructure - traffic signals, infrastructure - bus/tram lane, operations - reliability
bus, priority, signal control
When bus priority control is implemented, if there is a bus station between upstream detector and downstream signalized intersection, it will lead to the unpredictability of bus dwell time caused by the stochastic number of passengers waiting at the station. This uncertainty means that the bus’s arrival time at the intersection cannot be predicted quite accurately. Therefore, the signal priority control strategy made in advance may fail, which brings about a negative impact on the operation for both buses and cars at the intersection. To solve this problem, this paper proposes a two-stage transit signal priority (TTSP) control method. The first stage is robust optimal signal control (ROC) and aims to minimize bus delay expectation and variance. Bus delay expectation and variance calculation models considering the uncertainty of bus dwell time and the uncertainty of buses in line ahead in an exclusive bus lane are proposed based on mathematical statistics theory to formulate the stochastic process of bus operation. However, extreme situations cannot be avoided by the first-stage control completely. To make up for the deficiency of ROC, this paper adds the second-level real-time priority control, which is enabled in the case of the first-stage control failure to ensure the priority of public transit. The simulation test results show that the proposed TTSP method preforms better in reducing bus delay expectation, from 9.2 s to 3.2 s, reaching 65.2%. In addition, bus delay standard deviation decreases from 8.3 s to 3.9 s by 53.1%, improving the reliability of bus operation.
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Liang, S., Leng, R., Zhang, H., & Zhao, J. (2023). Two-stage transit signal priority control method to improve reliability of bus operation considering stochastic process. Transportation Research Record, 2677(2), 1713-1727.