微型智能车定位与控制及其集成测试

发布时间：2018-01-07 00:24

本文关键词：微型智能车定位与控制及其集成测试　出处：《大连理工大学》2015年硕士论文　论文类型：学位论文

更多相关文章： 车联网 双目定位 碰撞预警 智能车

【摘要】：近年来,随着汽车数量的增加,交通事故频发,对社会经济及生命财产安全造成了严重威胁。全世界的人们对交通安全更加关注。如何避免车辆碰撞,减少交通事故的发生成为了车联网急需解决的一个问题。对车联网碰撞预警算法进行测试,不仅需要良好的智能车软硬件平台的支持,还需要完整的车辆通信设备以及准确定位车辆的位置。测试时,需多辆传感器设备完善的智能车参与进来,极其容易发生多辆智能车碰撞的事故,因此真实测试的不仅危险性很大而且成本很高,所以目前国内外研究学者多选择在仿真实验平台上进行车联网碰撞预警测试。但是仿真实验并没有使用真实的环境参数,忽略了人类驾驶中存在的人为因素,所以实验测试结果存在一定的不精确性。针对仿真平台的不精确性及真实测试的不现实性,本文设计了一种微型智能车。在智能车硬件平台上,利用手机控制智能车来模拟人类真实驾驶,实现了智能车的加速、减速、启动、刹车、转弯等功能。同时采用摄像头双目定位实现对智能车位置的精确定位,获取智能车位置并计算行驶智能车的速度。通过定位到的位置速度信息,为车联网安全应用进行测试提供方便。还搭建了交通道路模型,模拟真实驾驶车道,最大限度还原真实驾驶场景。最后对其进行集成测试,确保预期的功能已经正确地实现。
[Abstract]:In recent years, with the increase of the number of cars, frequent traffic accidents have posed a serious threat to the social economy and the safety of life and property. People all over the world pay more attention to traffic safety and how to avoid vehicle collision. Reducing the occurrence of traffic accidents has become an urgent problem in vehicle networking. To test the collision early warning algorithm of vehicle networking, not only need the support of intelligent vehicle hardware and software platform. It also needs the complete vehicle communication equipment and the accurate location of the vehicle. When testing, many smart vehicles with perfect sensor equipment are required to participate in the test, which is extremely vulnerable to multiple intelligent vehicle collision accidents. So the real test is not only dangerous but also costly. So many scholars at home and abroad choose to carry on the vehicle network collision early warning test on the simulation experiment platform, but the simulation experiment does not use the real environment parameter, neglects the human factor which exists in the human driving. In view of the imprecision of the simulation platform and the reality of the real test, this paper designs a kind of mini intelligent vehicle on the hardware platform of smart car. The mobile phone is used to control the smart car to simulate the real human driving, realizing the acceleration, deceleration, starting, braking, turning and other functions of the smart car. At the same time, the camera binocular positioning is used to realize the precise location of the smart car. Get the location of the intelligent vehicle and calculate the speed of driving smart car. Through the location of the location speed information to provide convenience for the vehicle network security application testing. Also built a traffic road model to simulate the real driving lane. Maximize the restore of real driving scenarios. Finally, test it to ensure that the expected functionality has been correctly implemented.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495;TP391.9

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