ITSC 2024 Paper Abstract

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Paper ThBT16.2

Naderi, Mehdi (Technical University of Crete), Dabestani, Niloufar (Technical University of Crete), Papageorgiou, Markos (Technical Univ. of Crete)

Joint Optimal Control of CAV Platoons Crossing Lane-Free Signal-Free Intersections

Scheduled for presentation during the Poster Session "Automated vehicle platoons" (ThBT16), Thursday, September 26, 2024, 14:30−16:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Keywords Automated Vehicle Operation, Motion Planning, Navigation, Theory and Models for Optimization and Control, Multi-autonomous Vehicle Studies, Models, Techniques and Simulations

Abstract

The operation of signal-free intersections, where connected automated vehicles (CAVs) with different origin-destination (OD) can cross simultaneously, has the potential to greatly increase throughput and decrease fuel consumption. Since the intersection crossing area naturally includes no lanes, it can be considered as a lane-free infrastructure so as to enable further improved exploitation due to increased crossing flexibility. In addition, handling CAV platoons may further increase the intersection throughput due to shorter gaps between vehicles. This paper presents a joint optimal control method for both individual CAVs and CAV platoons crossing signal-free and lane-free intersections. The control inputs of all vehicles, both individual ones and platoon members, are optimized jointly over a time-horizon by solving a single optimal control problem (OCP). The cost function includes proper terms to ensure smooth and collision-free motion, while also considering fuel consumption and desired-speed tracking, when possible. In particular, a platooning term is considered to regulate the inter-vehicle distance, which is highly flexible and allows a crossing platoon to split when it faces collision risk. Proper constraints are formulated to keep vehicles within the intersection boundaries, satisfy practical limits, and ensure passenger comfort. An efficient Feasible Direction Algorithm (FDA) is used to numerically solve the defined OCP, ensuring acceptable computation times. The efficacy of the proposed method is confirmed by two demonstration examples.

 

 

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