Multi-objective optimization of electric automated bus trajectories based on the ε-constraint method

This paper deals with electric automated buses that have to follow a given route in inter-urban roads including stops, with a given timetable. Some stops are provided with a charging infrastructure allowing to charge the batteries while others are not. In order to control these buses, it is necessary to account for the traffic conditions along the road and to minimize two objectives, respectively related to the minimization of the deviations from the timetable and the minimization of the energy lack, at the end of the bus route, with respect to a desired final energy level. To address this problem and to investigate the conflicting nature of these objectives, two multi-objective methods based on the $\varepsilon$-constraint approach are applied in this paper, allowing to find different sets of efficient solutions for the problem. The results obtained in a real case study show that the two objective are in conflict, and compromise solutions can be found using the methods proposed in this paper.

I. Introduction

Mobility systems are the key issues for the design of smart cities [1]. In particular, electric mobility for public transport represents one of the most important innovations towards sustainability [2]. Besides electrification, another major technology progress involving transport systems regards the development of connected and automated vehicles. Public transport is also following this trend, as proven by the fast spread of autonomous buses worldwide [3]. Electric automated buses represent an interesting challenge for the control community, both in the design phase, in which paths, frequencies, stops must be defined, and in the real-time management, in which for example the speed and the charging phases must be controlled, as well as motion planning problems must be addressed [4].