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This paper proposed a path coordination strategy for autonomous parking based on independently designed parking lot topological map. The strategy merges two types of paths at the three stages of path planning, to determinate mode switching timing between low-speed automated driving and automated parking. Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information. Secondly, the direction and lateral distance of the parking space to the last node of global path are used to decide parking type and direction at parking planning stage. Finally, the parking space node is used to connect global path and parking path at path coordination stage.

Unlike the test of passive safety of traditional vehicles, highly automated vehicles (HAV) need more capabilities to be tested. Besides, there are more parameter combinations for the scenarios that need to be tested for each capability, resulting in a high time-consuming and costs for the autonomous vehicle tests. This paper proposes a method for scenario analysis and test effort reduction. Firstly, the trajectories of the vehicle under test (VUT) in the scenario are analyzed, and the trajectories which lead to the test mission failure are obtained. Based on the above trajectories, the threshold that lead to the test mission failure, or a combination of thresholds are analyzed. The above thresholds or a combination of thresholds values are defined as Scenario Character Parameter (SCP). The process of the analysis of the SCPs are related to the abilities of the HAV, but does not depend on the specific algorithm of the HAV.

As the only energy storage component in the internal combustion engine vehicles (ICEVs), the battery is lack of comprehensive supervision and effective protection. Excessive discharge or aging cannot be detected and dealt with, which may lead to damage of the battery, even startup failure of the vehicle. In this paper, a full protection and optimization management scheme of the battery is proposed, to achieve comprehensive protection of the battery and energy optimization. Firstly, power partitioning model of the battery is established to reveal the battery characteristics in different states, which divides the battery into several function zones. Then, based on the power partitioning model, over discharge protection and graded overcurrent protection method are proposed, to achieve full protection of the battery. Thirdly, energy optimization management strategy based on generator’s multimode operation is introduced.