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Research on Pedestrian Detection and Vehicle Distance Algorithms of Electric Vehicle Based on Image Processing

机译:基于图像处理的电动车辆行人检测与车辆距离算法研究

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With the economic growth of our country and the continuous improvement of people's living standards, cars have begun to enter thousands of households and become a necessity for people. However, the rapid growth of the number of automobiles has led to a sustained increase in carbon dioxide emissions and a significant decline in urban air quality, which seriously restricts the sustainable development of cities. With the introduction of the national air quality protection policy, electric vehicles will eventually replace the existing fuel vehicles and become a new generation of transportation for people to travel. At the same time, the large expansion of the number of cars has increased the hidden dangers of traffic accidents. In order to ensure the safety of pedestrians, drivers are given a more intelligent driving environment. This paper presents the research of pedestrian detection and pedestrian distance algorithm based on image processing. By comparing the performance of pedestrian detection algorithm based on SSD with traditional HOG+SVM pedestrian detection algorithm, the results of pedestrian-vehicle distance calculation are detected, and the feasibility and effectiveness of the algorithm are obtained. The results show that the proposed algorithm has good feasibility and practicability, and provide a good reference for the research of pedestrian detection algorithm for electric vehicles.
机译:随着我国的经济增长和人民生活水平的不断提高,汽车已经开始进入成千上万的家庭,成为人民的必需品。然而,汽车数量的快速增长导致二氧化碳排放的持续增加,城市空气质量的显着下降,这严重限制了城市的可持续发展。随着国家空气质量保护政策的引入,电动汽车最终将取代现有的燃料车辆,成为人们旅行的新一代运输。与此同时,汽车数量的大幅扩张增加了交通事故的隐患。为了确保行人的安全性,司机得到了更智能的驾驶环境。本文介绍了基于图像处理的行人检测和行人距离算法的研究。通过比较基于SSD与传统猪+ SVM行人检测算法的行人检测算法的性能,检测到行人车辆距离计算的结果,获得了算法的可行性和有效性。结果表明,该算法具有良好的可行性和实用性,对电动车辆行人检测算法的研究提供了良好的参考。

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