Optimal headway and schedule control of public transport buses
Paper in proceeding, 2017

This paper presents a model-based multiobjective control strategy to reduce bus bunching and hence improve public transport reliability. Our goal is twofold. First, we define a proper model, consisting of multiple static and dynamic components. Bus-following model captures the longitudinal dynamics taking into account the interaction with the surrounding traffic. Furthermore, bus stop operations are modeled to estimate dwell time. Second, a shrinking horizon model predictive controller (MPC) is proposed for solving bus bunching problems. The model is able to predict short time-space behavior of public transport buses enabling constrained, finite horizon, optimal control solution to ensure homogeneity of service both in time and space. In this line, the goal with the selected rolling horizon control scheme is to choose a proper velocity profile for the public transport bus such that it keeps both timetable schedule and a desired headway from the bus in front of it (leading bus). The control strategy predicts the arrival time at a bus stop using a passenger arrival and dwell time model. In this vein, the receding horizon model predictive controller calculates an optimal velocity profile based on its current position and desired arrival time. Three different weighting strategies are proposed to test (i) timetable only, (ii) headway only or (iii) balanced timetable - headway tracking. The controller is tested in a high fidelity traffic simulator with realistic scenarios. The behavior of the system is analyzed by considering extreme disturbances. Finally, the existence of a Pareto front between these two objectives is also demonstrated.

Author

Balazs Varga

Tamas Tettamanti

Balázs Adam Kulcsár

Chalmers, Signals and Systems, Systems and control

Proceedings of Swedish transportation research conference Stockholm 17-18 October 2017

Areas of Advance

Transport

Subject Categories

Transport Systems and Logistics

Control Engineering

More information

Created

1/17/2018