Investment and Financing of Roadway Digital Infrastructure for Automated Driving

Connected automated vehicles (CAVs) rely on sensors to scan their environment, enabling efficient decision-making, though their limited range poses challenges. Enhancing CAV operations by leveraging cooperative sensing via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications offers ways to improve autonomy. This study examines optimal investments in vehicular connectivity and stationary sensor deployment under different traffic conditions. Our results highlight the trade-off between roadside stationary sensors and CAV-mounted sensors. Results show that for low traffic flow and constrained budgets, infrastructure investment is preferable, while higher traffic flow favors connectivity among CAVs. Additionally, the analysis shows that an optimal toll cannot fully cover digital infrastructure costs, though if safety benefits are factored in, covering the costs of constructing such infrastructure becomes feasible. The self-financing theorem also holds for the case of digitalization of existing roads if their flow-capacity ratio exceeds a certain threshold.