Implementation of Driving Cycles Based on Driving Style Characteristics of Autonomous Vehicles

The standardized driving cycles, which are used around the globe for the development and homologation of automobiles, consist of a series of speed points versus time, to represent typical driving conditions and to exclude the influence of a human driver. However, with respect to autonomous vehicles (AVs), the driving style is defined in driving algorithms as a characteristic of the vehicle. Therefore, driving style should be considered in driving cycles. In this research, using MATLAB/Simulink (R) we developed the AVDC (Autonomous Vehicle Driving Cycle) Tool, which is capable of generating driving cycles based on driving style characteristics. The autonomous vehicles being investigated drive in a simulated environment along a straight road amongst other traffic vehicles, applying standard cycles to ensure the representativeness of generated autonomous cycles. The autonomous vehicle is piloted by adaptive cruise control (ACC) for car-following and free driving. Overtake logic decides whether passing will be attempted. Driving style is defined by four aspects-comfort, safety, swiftness, and economy-and determines the control parameters in the driving algorithm. The driving cycles generated by the AVDC Tool for a variety of driving styles show diverse characteristics, thus indicating the effective representation of various driving styles.