Infrastructure Assisted Constrained Connected Automated Vehicle Trajectory Optimization on Curved Roads: A Spatial Formulation on a Curvilinear Coordinate

TL;DR

This paper introduces a novel infrastructure-assisted trajectory optimization method for connected automated vehicles on curved roads, utilizing a spatial formulation on a curvilinear coordinate system to enhance safety and efficiency.

Contribution

It presents a new spatial formulation based on curvilinear coordinates for trajectory optimization of CAVs on curved roads, incorporating infrastructure data and a multi-objective MPC approach.

Findings

Smooth vehicle trajectories achieved in simulations

Effective obstacle avoidance and regulation compliance

Robust performance across complex road geometries

Abstract

Vehicle trajectory optimization is essential to ensure vehicles travel efficiently and safely. This paper presents an infrastructure assisted constrained connected automated vehicles (CAVs) trajectory optimization method on curved roads. This paper systematically formulates the problem based on a curvilinear coordinate which is flexible to model complex road geometries. Further, to deal with the spatial varying road obstacles, traffic regulations, and geometric characteristics, two-dimensional vehicle kinematics is given in a spatial formulation with exact road information provided by the infrastructure. Consequently, we applied a multi-objective model predictive control (MPC) approach to optimize the trajectories in a rolling horizon while satisfying the collision avoidances and vehicle kinematics constraints. To verify the efficiency of our method, a numerical simulation is conducted. As the results suggest, the proposed method can provide smooth vehicular trajectories, avoid road obstacles, and simultaneously follow traffic regulations, which is robust to road geometries and disturbances.