Automated and Cooperative Vehicle Merging at Highway On-Ramps

Rios-Torres, Jackeline; Malikopoulos, Andreas A. · 2016 · OpenAlex-citations

DOI: 10.1109/tits.2016.2587582

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Summary

This paper addresses the challenge of traffic congestion and safety hazards at highway merging zones, which are primary sources of bottlenecks causing stop-and-go driving and excessive fuel consumption. The authors propose an optimization framework for coordinating Connected and Automated Vehicles (CAVs) at merging roadways to achieve smooth traffic flow. The study focuses on deriving an analytical, closed-form solution for vehicle coordination that minimizes fuel consumption while strictly adhering to collision avoidance constraints. The methodology employs a centralized control approach where a controller manages vehicles entering a defined control zone before the merging area. Each vehicle is modeled using second-order dynamics, with state variables for position and speed, and control inputs for acceleration. The objective function minimizes fuel consumption, utilizing a polynomial metamodel that accounts for cruise and acceleration fuel usage, alongside a term to minimize gaps between vehicles to maximize road capacity. Hard safety constraints are imposed to prevent rear-end collisions on the same lane and lateral collisions in the merging zone. The authors apply Hamiltonian analysis to solve the optimal control problem, deriving explicit time-dependent functions for optimal acceleration, speed, and position. This allows for online computation of control inputs as vehicles enter the control zone, ensuring they exit the merging zone at specific times that satisfy safety distances. Simulation results conducted in Matlab validate the effectiveness of the proposed analytical solution. The study considers scenarios with multiple vehicles entering the control zone at a constant initial speed of 13.4 m/s, with a control zone length of 400 meters and a merging zone of 30 meters. The simulations demonstrate that the coordinated control strategy successfully avoids collisions and eliminates stop-and-go behavior. Specifically, the results indicate that the proposed coordination significantly reduces both fuel consumption and travel time compared to uncoordinated driving. The closed-form nature of the solution ensures computational efficiency, making it suitable for real-time implementation in automated vehicle systems. The significance of this work lies in providing a mathematically rigorous and computationally efficient method for cooperative merging control. By offering an analytical solution rather than relying on iterative numerical optimization, the approach facilitates real-time coordination of CAVs. The findings suggest that centralized coordination at merging zones can substantially improve transportation network efficiency and safety by reducing fuel waste and congestion. This contributes to the broader field of automated driving by addressing a critical bottleneck in highway infrastructure with a scalable and provably safe control strategy.

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• v2x connected vehicle