Cooperative parking search strategy through V2X communications: an agent-based decision

Finding parking spots in urban areas poses significant challenges due to the ever increasing complexities of the transportation endeavor, resulting in issues like traffic jams, higher fuel consumption, and environmental pollution. In this regard, this paper introduces an innovative Cooperative parking search strategy that relies on agent decision-making and Vehicle-to-Everything (V2X) communication. This approach allows vehicles to share real-time information regarding their parking intentions and available spots, enabling agents (representing vehicles) to collectively make informed decisions and optimize the parking search process. The proposed strategy aims to enhance the efficiency of parking searches by facilitating real-time information exchange through V2X communication. To demonstrate its effectiveness, we conducted a proof-of-concept implementation using OMNeT++ simulator and SUMO traffic generator to simulate real-world conditions in Laghouat City. The simulation considers a variety of parameters, including recommended parking distance, traffic congestion, and parking space availability. Numerical results show that agent cooperation can reduce the overall parking search time for all drivers by up to 10 % compared to alternative methods, including greedy and selfish approaches.