Low communication delay is crucial for the effectiveness of connected-autonomous-vehicle-based (CAV-based) intersection control strategies. To achieve low vehicle-to-road-side-unit (V2R) communication delay and support the implementation of CAV-based intersection control strategies, this study addresses the problem of road side unit (RSU) location optimization at a single intersection. Considering the uncertainty of the selection of intersection control strategies, the problem is formulated as a two-stage stochastic mixed-integer nonlinear program. The model aims to minimize the sum of the cost associated with RSU investment and the expectation of the penalty cost associated with V2R communication delay exceeding a pre-determined threshold. The first stage of the program determines the number and location of RSUs, when the intersection control strategy to be implemented is unknown. Given the first stage decision and the implemented intersection control strategy, the second stage model optimizes the detection area allocation among RSUs to minimize the penalty cost. The model is linearized using the piecewise linearization technique. Then an integer L-Shaped algorithm is proposed to find a global optimal solution to the linearized program. In the numerical example, the proposed model is compared with a deterministic model. The results demonstrate that the V2R communication reduction per cost obtained by the proposed model is 28.95 larger than that obtained by the deterministic model, in the scenario that a CAV-based control strategy is implemented in the second stage. This indicates that the proposed model provides cost-effective low V2R communication delay for intersection control in CAV environment.

低通信延迟对于基于联网自动驾驶车辆（基于 CAV）的交叉路口控制策略的有效性至关重要。为了实现低车对路侧单元 (V2R) 通信延迟并支持基于 CAV 的交叉口控制策略的实施，本研究解决了单个交叉口的路侧单元 (RSU) 位置优化问题。考虑交叉口控制策略选择的不确定性，将问题表述为两阶段随机混合整数非线性规划。该模型旨在最小化与 RSU 投资相关的成本和与超过预定阈值的 V2R 通信延迟相关的惩罚成本的预期之和。该计划的第一阶段确定 RSU 的数量和位置，当要实施的交叉路口控制策略未知时。给定第一阶段决策和实施的交叉口控制策略，第二阶段模型优化 RSU 之间的检测区域分配，以最小化惩罚成本。该模型使用分段线性化技术进行线性化。然后提出整数L-Shaped算法来寻找线性化程序的全局最优解。在数值示例中，将提出的模型与确定性模型进行了比较。结果表明，在基于 CAV 的控制策略在第二阶段实施的场景中，所提出的模型获得的 V2R 通信每成本降低比确定性模型获得的大 28.95。