This paper is devoted to solving the problem of effective traffic flow management and parking lot organization by creating interception parking lots that help reduce traffic jams and improve parking availability. An algorithm has been proposed, and a simulation model of an interceptor parking lot has been implemented in Python. The development allows for the examination of the dynamics of parking lots, taking into account changes in traffic intensity throughout the day and week. It provides extensive opportunities for configuring parameters such as the number of lanes, parking lot capacity, vehicle arrival intensity, and duration of stay. The developed model can be helpful for urban planners, commercial parking lot owners, and researchers working on optimizing the use of urban space. Its integration with modern IoT solutions opens up prospects for the creation of intelligent parking systems that will help reduce traffic congestion, increase driver comfort, and reduce the impact of motor transport on the city's environment.
