Problem Setting for Trajectory Planning and Cruise Control of a Connected Autonomous Electric Bus in Intersection Scenarios with Human-Driven Vehicles to Optimize Energy, Comfort and Tracking

Journal article, 2025

This paper proposes a two-stage design approach to ensure reduced energy consumption, improved passenger comfort, and trajectory tracking in the context of an intersection crossing scenario involving a Connected Autonomous Electric Bus (CAEB) and a set of Human-Driven Vehicles (HDVs). The dynamic models of the CAEB and HDVs are defined considering that the movement is in a straight line and using three lanes of the road. In the first stage of the design approach, the discrete-time trajectory planning of the CAEB is performed, which involves the segmentation of the trip into road segments, and the trajectory planning is performed at the level of road segments in discrete time. A novel formula to calculate the length of a road segment is proposed. In this paper a new complete and transparent model is also proposed to compute the signal of traffic lights. An objective function is defined so that it can be minimized in an appropriate optimization problem, which aims to reduce the energy consumption of the CAEB and improve passenger comfort by forcing the CAEB to reduce the frequency of the increments of lane changing. The trajectory planning generates three reference inputs that are used by the cruise controllers designed in the second stage, where the original and simple trigonometric position and speed profiles are defined. In this stage of the design approach, the controllers are designed to ensure trajectory tracking in the framework of a continuous-time optimization problem that aims to reduce energy consumption and improve passenger comfort by minimizing an objective function that considers energy consumption and tracking performance of the CAEB cruise control system. Open-loop simulation results are presented, compared, and discussed for four simulation scenarios.