Information interaction test on cooperative vehicle infrastructure system based on fuzzy comprehensive evaluation

ObjectiveThe study aims to evaluate the implementation effectiveness of cooperative vehicle infrastructure system (CVIS) information interaction, guide the upgrading of on-board unit and roadside unit, and establish a quantitative evaluation basis.MethodAn evaluation indicator system for CVIS information interaction was constructed, covering reliability, real-time performance, stability, and economy. The definition and calculation method for each indicator were clarified. The analytic hierarchy process was used to determine the weight of each indicator. Combined with expert surveys about requirements that CVIS should meet, the membership degree for each evaluation indicator was established; the trapezoidal membership functions were constructed; and a multi-level fuzzy comprehensive evaluation model was built. CVIS information interaction test system, consisting of connected vehicles, on-board units, roadside units, and wireless communication modules, was set up on a closed road. Data for evaluation indicators of information interaction were collected in real-time. CVIS information interaction evaluation indicators were calculated. A multi-level comprehensive averaging model was used to compute a comprehensive evaluation value to assess the implementation effectiveness of CVIS information interaction.ResultThe recognition rate and recognition distance of CVIS information are key indicators affecting the effectiveness of system information interaction. They can serve as important bases for equipment comparison and performance optimization. Vehicle speed and its distance from roadside units have significant influences on the effectiveness of information interaction.ConclusionThe proposed evaluation method can effectively achieve dynamic performance assessment of CVIS information interaction, providing support for system optimization and equipment selection. Meanwhile, improving the recognition rate and recognition distance is the key focus for future technological development.