Roadside Unit Deployment Optimization Based on Mixed Traffic Stochastic Equilibrium

Existing studies on roadside unit (RSU) deployment insufficiently consider mixed traffic scenarios involving autonomous vehicles (AVs) and human-driven vehicles (HVs), making it difficult to ensure the connectivity and coverage of vehicular ad hoc networks (VANETs). To enhance VANET performance, research on RSU deployment under the impact of stochastic route choice of mixed traffic is conducted. To depict the route choice behavior of AVs, an improved path-size logit model is proposed based on communication probability, and a stochastic user equilibrium (SUE) mathematical programming model is established for mixed HV and AV traffic. Considering the impact of the mixed traffic with AVs and HVs on the RSUs deployment, a weighted objective function is designed to comprehensively considering both communication probability and coverage and establish a bi-level programming model for RSUs layout optimization with the aforementioned SUE mathematical programming as the lower-level model. An improved binary particle swarm optimization algorithm incorporating a speed monitoring strategy is designed to solve the bi-level model. Numerical experiments yield the following finds. ①The proposed model and algorithm are feasible and effective and can achieve, for different traffic demands, optimal deployment schemes with network connectivity and coverage greater than 90% and with balanced number of RSUs and communication radius. ②When AVs modal share exceeds 5%, optimized RSU deployment enables VANETs to achieve relatively high connectivity and coverage. ③With a large communication radius of 0.8 km, connectivity and coverage decrease slowly as the number of RSUs varies within the range of 19 to 34 but remain at a high level. With a communication radius of 0.6 km (0.4 km), connectivity and coverage decline slowly at first and then significantly (significantly at first and then slowly) and finally approach a low value of 0.4. ④A lower AV modal share incidates a greater marginal impact of total demand of mixed AV and HV traffic on connectivity and coverage.