Evaluation Method of Harmony with Traffic Based on a Backpropagation Neural Network Optimized by Mean Impact Value 2021-01-5060

With the development of autonomous driving, the penetration rate of autonomous vehicles on the road will continue to grow. As a result, the social cooperation ability of autonomous vehicles will have a great effect on the social acceptance of autonomous driving, which can be described as harmony with traffic. In order to research the evaluation method of the harmony with traffic, this paper proposes a subjective and objective mapping evaluation method based on the Mean Impact Value and Backpropagation (MIV-BP) Neural Network, with the merging vehicle on the expressway ramp as the research object. Firstly, by taking 16 original objective indexes obtained by theoretical analysis and the subjective evaluation results as input and output, respectively, the BP Neural Network model is constructed as a baseline model. Secondly, nine selected objective indexes are selected by the MIV method based on the baseline model. Finally, the MIV-BP Neural Network model is constructed from these selected objective indexes as an improved model and compared with the baseline model. The results show that the mapping result of the selected objective indexes is better than the original objective indexes. And the precision of the improved model is 96.77%, which is 2.11% higher than the baseline model. Therefore, the mapping model based on the MIV-BP Neural Network can be applied to improve the evaluation precision of the harmony with traffic for the merging vehicle.