For a scenario of mixed traffic with human driven and with connected automated vehicles (CAV), in which the human driver will respond appropriately to a request to intervene (according to SAE-Level 3), a traffic management measure for automated vehicles in urban areas shall be developed.
wo challenges shall be considered. One primary issue that necessitates special attention is drivers' altitudes towards CAVs. Besides, how to imposing a significant positive impact on mixed traffic scenario by management of CAVs remains to be investigated.
A management strategy that platooning private CAVs with human leaders (HL) is proposed to cope with these challenges. By the HL strategy, CAVs are operated as a platoon, in which the first CAV is manually driven. In addition, the driver of each CAV can switch between automated mode and manual driving mode. This particular strategy allows automated vehicles to avoid conflicts with human driven vehicles, cyclists and pedestrians. To this end, each CAV shall be instructed whether to join or lead a certain platoon according to the driver’s preference and the traffic condition.
Tasks of this research work will be to develop a cooperative platooning approaches based on the HL strategy, by which each CAV will be instructed to stay at an appropriate position in a platoon and to switch to a corresponding driving mode, in order to improve the traffic condition and automatic driving experiences. In addition, the developed approach should be able to integrate with other different measures within a conclusive overall traffic management concept for mixed traffic in urban traffic. A multi-criteria evaluation by simulation with respect to traffic efficiency and automated driving experience will prove the feasibility of the concept.
The sketch intuitively indicates a typical study scenario in this research. In the sketch, a red vehicle represents a CAV in manual driving mode, whereas a black vehicle represents a CAV in automated mode. By the management measure, CAVs are operated as platoons (composed by following CAVs in automated mode and one leading CAV in manual driving mode) with some constraints (e.g. maximum number of CAVs in one platoon). In addition, CAVs are instructed to form new platoons or split from their original platoons accordingly to achieve different objectives.
Researcher: Shengyue Yao, M.Sc.