Optimally combined headway and timetable reliable public transport system
Journal article, 2018

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. Four different weighting strategies are proposed to test (i) timetable only, (ii) headway only, (iii) balanced timetable - headway tracking and (iv) adaptive control with varying weights. 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.

MPC control

Multiobjective optimization

Timetable reliability

Autonomous vehicles

Bus bunching

Author

Balázs Varga

Budapest University of Technology and Economics

Tamas Tettamanti

Budapest University of Technology and Economics

Balázs Adam Kulcsár

Chalmers, Electrical Engineering, Systems and control

Transportation Research, Part C: Emerging Technologies

0968-090X (ISSN)

Vol. 92 1-26

Areas of Advance

Transport

Subject Categories

Computational Mathematics

Transport Systems and Logistics

Business Administration

DOI

10.1016/j.trc.2018.04.016

More information

Latest update

2/19/2021