Optimal trajectory planning meets network-level routing: Integrated control framework for emerging mobility systems

TL;DR

This paper presents an integrated control framework combining trajectory planning and network routing for connected and automated vehicles to optimize urban mobility by reducing travel time and energy consumption.

Contribution

It introduces a hierarchical decision-making framework with a novel route-recovery and energy-optimal trajectory planning method for CAVs, addressing practical feasibility in urban traffic.

Findings

Reduces total travel time in urban settings.

Decreases energy consumption of CAVs.

Enables rapid solution of constrained optimization problems.

Abstract

In this paper, we introduce a hierarchical decision-making framework for emerging mobility systems. Despite numerous studies focusing on optimizing vehicle flow, practical feasibility has often been overlooked. To address this gap, we present a route-recovery method and energy-optimal trajectory planning tailored for connected and automated vehicles (CAVs) to ensure the realization of optimal flow. Our approach identifies the optimal vehicle flow to minimize total travel time while considering consistent mobility demands in urban settings. We deploy a heuristic route-recovery algorithm that assigns routes to CAVs and departure/arrival time at each road segment. Furthermore, we propose an efficient coordination method that rapidly solves constrained optimization problems by flexibly piecing together unconstrained energy-optimal trajectories. The proposed method has the potential to effectively generate optimal vehicle flow, contributing to the reduction of travel time and energy consumption in urban areas.