A shared strategy of dedicated autonomous truck lanes for enhancing sustainability and efficiency in mixed freeway traffic

This paper presents the shared dedicated lane (SDL) strategy, designed to optimize dedicated lane utilization and enhance traffic flow in mixed environments with connected automated trucks (CATs) and human-driven vehicles (HDVs). The strategy consists of two components: the Platoon Optimal Formation (POF) model, which minimizes fuel consumption for CATs by determining the most efficient platoon formations, and the Two-Lane Cellular Automaton (TCA) model, which simulates vehicle movements, introduces lane-changing rules, and establishes CAT priority conditions to ensure efficient SDL utilization by HDVs. Numerical experiments were conducted on a multi-lane freeway to evaluate the SDL strategy under various traffic scenarios with different CAT demand ratios. The results show that the SDL strategy outperforms traditional approaches by improving traffic flow, fuel efficiency, and overall performance in mixed conditions. Specifically, it reduces fuel consumption by up to 10% under high CAT demand ratios and alleviates congestion while increasing HDV speeds during low CAT demand ratios.