Test Method of Automated Valet Parking System for Intelligent Vehicles

As a hot topic of research, the automated valet parking system lacks methods necessary for systematic testing and evaluation. To address these issues, this work conducted a series of studies. First, a framework for a test scenario based on an autonomy levels for unmanned system (ALFUS) was proposed. Under this framework, a test scenario of an automated valet parking system was studied through integrated environment elements, task elements, and a spatial-temporal order, which was derived from actual parking scenario data and the working principle of a valet parking system. Then, a test and evaluation method based on the scenario was proposed using a fuzzy-synthetic evaluation and a test clustering method. The latter was divided into four types from simplicity to complexity based on different environments and tasks. Then, referring to Johari window theory, a matrix was established for analyzing the test results in terms of both the merits and demerits of the automated valet parking system and the test and evaluation method itself. Finally, based on a series of real vehicle tests, an application example of a full set of the test and evaluation method is presented, in which some suggestions for improving both the valet parking system and the test and evaluation method are presented. Experimental results indicate that this study not only improves the performance of test objects but also verifies that the perfection of the test method itself, which is effective for use with current automated valet parking systems. © 2019, Editorial Department of China Journal of Highway and Transport. All right reserved.