Abstract
Setting independent lanes for passenger vehicles and trucks respectively could reduce traffic accidents. But most management strategies for separating trucks from passenger vehicles are concentrated on fixed exclusive lanes, which couldn't be adjusted when the running state of traffic flow changes. This study proposed a modified model predictive control (MPC) method used for dynamic adjustment of lane division schemes, to improve traffic efficiency. An extended METANET model that considered vehicle types was established for predicting traffic status. A theory for searching for the optimal lane division scheme was constructed using a modified BRP road resistance function as the objective function. Through simulation of the urban mobility (SUMO) platform, the performance of the method was compared with the static lane division scheme and feedback control method. Simulation results reveal that the modified MPC method improves the traffic efficiency by 5.3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> and more than 14.9% respectively compared with the static lane division scheme and feedback control method. The compared results illustrate that the proposed MPC method has better performance when the proportion of vehicle types changes drastically.
Published Version
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