Optimal internal boundary control of lane-free automated vehicle traffic

TL;DR

This paper introduces a convex quadratic programming approach for real-time internal boundary control in lane-free automated vehicle traffic, aiming to optimize bidirectional road capacity sharing based on demand and traffic conditions.

Contribution

It formulates a novel convex QP model for internal boundary control in lane-free traffic, enabling flexible capacity sharing and improved flow efficiency.

Findings

The control method effectively adapts to traffic demand fluctuations.

Case studies demonstrate increased traffic flow efficiency.

The approach is computationally efficient for real-time implementation.

Abstract

A recently proposed paradigm for vehicular traffic in the era of CAV (connected and automated vehicles), called TrafficFluid, involves lane-free vehicle movement. Lane-free traffic implies that incremental road widening (narrowing) leads to corresponding incremental increase (decrease) of capacity; and this opens the way for consideration of real-time internal boundary control on highways and arterials, in order to flexibly share the total (both directions) road width and capacity among the two directions in dependence of the bi-directional demand and traffic conditions, so as to maximize the total (two directions) flow efficiency. The problem is formulated as a convex QP (Quadratic Programming) problem that may be solved efficiently, and representative case studies shed light on and demonstrate the features, capabilities and potential of the novel control action.