Multi-attribute decision making on mitigating a collision of an autonomous vehicle on motorways

Autonomous vehicles have the potential to improve automotive safety, largely by removing human error as a possible cause of collisions. However, it cannot be guaranteed that autonomous will able eliminate all Therefore, safety continue necessity for design. This paper proposes decision making system which selects least severe collision an vehicle take, when facing multiple imminent and unavoidable collisions on motorway. The novel developed combines simulation results multi-attribute (MADM) methods. simulator includes models dynamics manoeuvre trajectory path. MADM methods are used decide vehicle(s) should collide with, based severity Severity is calculated in using following variables: impact velocity between ahead, behind vehicle, acceleration time-to-collision. Various investigated three selected including Technique Order Preference Similarity Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP), Network (ANP). scenarios defined tested order understand small changes parameters ahead made. analysed promising lead conclusion can successfully applied vehicles.