Coordination of Mixed Platoons and Eco-Driving Strategy for a Signal-Free Intersection - Jiang, Simin; Pan, Tianlu; Zhong, Renxin; Chen, Can; Li, Xin-an; Wang, Shimin (IEEE transactions on intelligent transportation systems, 2023)
This paper investigates the collaborative control of vehicular traffic for a signal-free intersection. The traffic under consideration is mixed with connected autonomous vehicles (CAVs) and human-piloted vehicles with advanced driver assistance systems (ADAS). The proposed collaborative control is of two levels. At the upper level, the objective is to minimize total delay via platoon control and dynamic priority control of conflicting movements. We formulate the platoon coordination of mixed traffic as a mixed-integer linear programming problem (MILP). This MILP determines whether adjacent vehicles will form a platoon and prioritize any two conflicting movements subject to lateral safety and rear-end safety constraints. At the lower level, we propose an eco-driving strategy to minimize the energy consumption by optimizing the speed profile of the platoon leading vehicles subject to the dynamic priority control from the upper level, i.e., the entry time to the merging zone. We deduce an analytical solution to the eco-driving problem using optimal control theory. Compared with existing benchmarks, such as the first-come-first-served policy, the proposed method outperforms the state-of-the-art controllers in reducing the total delay. Sensitivity analysis regarding the penetration rate of CAVs shows that substantial improvements can be achieved even at low to medium penetration rates of CAVs.