## 2 Review of Related Work  
In 2007, the DARPA (Defense Advanced Research Projects Agency) Urban Challenge (DUC) initiated numerous research projects to address challenges of autonomous driving. Since then, a great deal of research has been conducted in related topics. In addition to highway and urban driving, automated valet parking is also of major interest to relieve drivers from the stress of parking [17]. In 2012, a parking information acquisition and release system was designed by [PERSON] et al. based on the dynamic allocation algorithm of parking spaces in the parking lot [18]. The main idea is to optimize among the distribution of parking spaces arranged in a tabulated format and driving paths/distances. However, the algorithm can obtain the availability of parking spaces only after the human-operated vehicles have completed their parking. Thus, if there are more than two vehicles, at least one HV and one AV, choosing the same parking space and converging near that space, this scenario could lead to traffic congestion and the wasting of time and fuel consumption. In 2012, Audi Corporation developed a parking guidance system that could assist and orchestrate the entire parking process [19]. The approach of the system includes three steps: scanning, positioning, and arranging parking [20]. The distance to the obstacle is detected by eight ultrasonic sensors installed in the bumper and the parking space is detected by 10 ultrasonic sensors. This parking system can only be executed if the speed of the vehicle is below 30 km/h. While this is an excellent demonstration of an automated valet parking system, during the transition period to fully autonomous driving, HVs will also be represent; the guidance system cannot allocate parking spaces to the HVs with no communication devices equipped and hence cannot complete the space allocation task for the AVs. In 2016, [PERSON] et al. [21] proposed a system to reduce the time wasted in looking for parking spaces by offering guaranteed parking reservations with the lowest possible cost and searching time for drivers and the highest revenue and resource utilization for parking managers. However, they did not include other important factors that influence how drivers choose parking spaces, such as the safe locations of the parking spaces and the distance to reach the parking space. In 2018, [PERSON] et al. [22] presented an architecture for Automated Valet Parking (AVP) connected to cloud-based IoT services and mobile user interfaces. Autonomous vehicles can share information and data via the phones of their occupants. Moreover, under this communication architecture, some functions of the AVs, such as drop-off and pick-up, can be activated by phones. However, the paper only considers the interactions between users and AVs. In an actual scenario, many vehicles will be present at the same time, making efficient planning of traffic flow in the parking lot not possible by just integrating the shared information provided by the users. In 2019, a new path planning system based on the Dijkstra algorithm was designed by [PERSON] et al. [23]. The road occupancy factor is calculated and added to the path weight of the Dijkstra algorithm, and a shortest path is selected by comparing the weight of each path. However, the traffic situation in the parking lot is complex, and each section of the path may be occupied at any time. Hence, the optimal path planning in the parking lot requires a dynamic planning. In 2020, a parking guidance system based on the multi-objective point A* algorithm was designed by [PERSON] et al. [24], which combines the distance factor between the entrance and the parking spaces and path planning using a heuristic function of the A* algorithm to quickly generate multiple driving paths and select the most efficient path. However, the heuristic function of the A* algorithm cannot take into consideration traffic congestion. If congestion happens, the time loss on queuing will reduce the efficiency of the system and subsequently increase the fuel consumption.