Joint Path Planning for Multiple Automated Vehicles in Lane-Free Traffic With Vehicle Nudging

Abstract

This article presents a joint trajectory optimization algorithm for a number of connected and automated vehicles in a lane-free traffic environment with vehicle nudging. A double double-integrator model is utilized for the longitudinal and lateral movements of each vehicle. The objective function consists of several sub-objectives that reflect corresponding, partially competing driving aspects and concerns, including passenger comfort, low fuel consumption, vehicle advancing at desired speed, collision avoidance, suppressing of infeasible maneuvers. Fixed and state-dependent control input bounds account for various technical limitations as well as for road boundary respect. The solution of the formulated joint Optimal Control Problem (OCP) is computed by use of a very efficient Feasible Direction Algorithm, which exploits the structure of the state equations to map the OCP into a reduced Nonlinear Programming Problem. To demonstrate the efficiency of the proposed approach, challenging scenarios are examined on a lane-free straight motorway stretch. The results of the centralized (joint) OCP are compared with a previously investigated decentralized approach where OCPs are employed separately for individual vehicles.