[1]王 睿.基于机器视觉的城市轨道交通对标停车系统研究[J].机车电传动,2019,(02):107-110.[doi:10.13890/j.issn.1000-128x.2019.02.120]
 WANG Rui.Research on Benchmarking Parking System of Urban Rail Transit Based on Machine Vision[J].Electric Drive for Locomotives,2019,(02):107-110.[doi:10.13890/j.issn.1000-128x.2019.02.120]
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基于机器视觉的城市轨道交通对标停车系统研究()
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机车电传动[ISSN:1000-128X/CN:43-1125/U]

卷:
期数:
2019年02期
页码:
107-110
栏目:
城市轨道车辆
出版日期:
2019-03-10

文章信息/Info

Title:
Research on Benchmarking Parking System of Urban Rail Transit Based on Machine Vision
文章编号:
1000-128X(2019)02-0107-04
作者:
王 睿
(中车株洲电力机车有限公司,湖南 株洲 412001)
Author(s):
WANG Rui
( CRRC Zhuzhou Locomotive Co., Ltd., Zhuzhou, Hunan 412001, China )
关键词:
自动驾驶机器视觉车载摄像头对标停车城市轨道交通地铁车辆
Keywords:
auto-driving machine vision on-board camera benchmark parking urban rail transportation metro vehicle
分类号:
U284.48;U268.4
DOI:
10.13890/j.issn.1000-128x.2019.02.120
文献标志码:
A
摘要:
车辆自动驾驶技术是基于环境感知技术对周围环境进行感知,并根据获得的信息,通过车载中心电脑控制车辆的转向和速度,使车辆能够安全、可靠地行驶,并达到预定目的地的车辆控制技术。基于自动驾驶技术中的机器视觉,通过安装在车辆上的车载摄像头识别车标及车辆信号灯,允许车辆在没有人工参与的前提下,在自主进站停车过程中,识别车辆的位置并实施制动停车。机器视觉通过传感器及相机来代替人类双眼的功能进行测量和判断,是未来车辆发展的趋势,对标停车只是机器视觉可以完成的功能之一。未来,通过安装在车辆上的摄像头可以实现轨道交通的机器视觉,实时掌握路面信息,感知周围环境,在缓解交通压力、提升城市交通效率、提升能量利用等方面发挥更多的作用。
Abstract:
Vehicle auto-driving technology is a control technology that senses the surrounding environment based on environmental awareness, and controls the steering and speed of the vehicle through the on-board center computer according to the acquired information, so that the vehicle can drive safely and reliably and reach the predetermined destination. Based on the machine vision in automatic driving technology, vehicle signs and signal lights were recognized by on-board camera installed on the vehicle, which allows the vehicle to identify the position of the vehicle and implement braking parking in the process of self-stop parking without human participation. Machine vision measured and judged the function of human eyes by sensors and cameras, which was the trend of vehicle development in the future. Benchmarking parking was only one of the functions that machine vision can accomplish. In the future, through the camera installed on the vehicle, the machine vision of rail transit can be realized, real-time road information can be grasped, and the surrounding environment can be perceived, which will play a more important role in alleviating traffic pressure, improving urban traffic efficiency and improving energy utilization

参考文献/References:

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备注/Memo

备注/Memo:
作者简介:王 睿(1991—),男,硕士,研究方向为城市车辆自动驾驶与无人驾驶。
更新日期/Last Update: 2019-03-10