Abstract

Throughout the years, the expectations and capabilities of autonomous vehicles have increased, as has the level of automotive intelligence. In the majority of research studies, longitudinal and lateral control topics have been explored to understand and design intelligent systems. For example: Automatic parallel parking, Adaptive cruise control, co-operative adaptive cruise control, semi and fully autonomous cars. Sensors onboard the vehicle and communications networks transmit scene information to other vehicles and infrastructure. To be able to achieve autonomously driving on complex environments and to utilize the information as part of the motion planning and control schemes, different motion planning and control techniques were implemented. Upon implementing these initiatives, the main task is executed to increase the level of safety, comfort, and energy efficiency in the workplace. As part of the present paper, an in-depth review of various parallel parking methodologies based on automatic parallel parking is presented. In this presentation, the main topics that will be covered will be algorithm types, simulations, and field tests, as well as human factors that influence vehicle behavior. Additionally, various parking information services are also offered for parking guidance, facility management, and even for providing an insight into the parking situation. We have also provided a brief description of the techniques used by research teams, a comparison between these techniques, and additional information about the research teams’ contributions to motion planning. The paper concludes by discussing a future research direction and application.

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