Integrated Robust Optimization of Scheduling and Signal Timing for Bus Rapid Transit

Abstract

The unbalanced nature of passenger demand and the uncertainty of delay at intersections are considered critical factors in the efficiency of public transportation operations. Considering the controllable characteristics of the bus rapid transit system (BRT), an integrated optimization model that includes multi-mode transit scheduling and signal timing is proposed. The robust optimization model copes with the fluctuations in passenger demand and bus operation. A non-linear programming is developed to minimize the total passenger travel time and optimize the transit departure time, dwelling strategies at stations, and signal timings at intersections. The constraints on the signal control, degree of saturation, transit scheduling, and passenger waiting time at stations are intended to reflect real traffic conditions. A case study and extensive sensitivity analyses were conducted to evaluate the performance of the proposed model. The results show that the proposed integrated model can adjust the BRT dwelling strategies based on different passenger demands and coordinate transit departure time and signal timing adjustment to mitigate the passenger delay. Furthermore, experimental results demonstrate improvements of 5.3% and 8.1% in the mean and maximum values of passenger travel time, respectively, using the proposed model, compared to those obtained using the conventional operation strategy.

Simulation and Analysis of Line 1 of Mexico City’s Metrobus: Evaluating System Performance through Passenger Satisfaction

“…Another approach was proposed by Xue et al [18] in which they used uncertainty theory and a bilevel programming model to optimize the frequency and time between departures of the 207 bus routes of Nanchang city, China; they demonstrated that this is an effective approach for reducing passengers' travel times, but it has some limitations. Wang et al [19] proposed a mixed integer nonlinear programming model in which they sought to optimize bus schedules and traffic signaling. To analyze the model, they considered the Fengpu BTR line in Shanghai, China and showed that the passengers' traveling times could be decreased compared to a more traditional approach.…”