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通过协作车辆定位网络实现的自动驾驶汽车停车系统。

Autonomous Car Parking System through a Cooperative Vehicular Positioning Network.

作者信息

Correa Alejandro, Boquet Guillem, Morell Antoni, Lopez Vicario Jose

机构信息

Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain.

出版信息

Sensors (Basel). 2017 Apr 13;17(4):848. doi: 10.3390/s17040848.

DOI:10.3390/s17040848
PMID:28406426
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5424725/
Abstract

The increasing development of the automotive industry towards a fully autonomous car has motivated the design of new value-added services in Vehicular Sensor Networks (VSNs). Within the context of VSNs, the autonomous car, with an increasing number of on-board sensors, is a mobile node that exchanges sensed and state information within the VSN. Among all the value added services for VSNs, the design of new intelligent parking management architectures where the autonomous car will coexist with traditional cars is mandatory in order to profit from all the opportunities associated with the increasing intelligence of the new generation of cars. In this work, we design a new smart parking system on top of a VSN that takes into account the heterogeneity of cars and provides guidance to the best parking place for the autonomous car based on a collaborative approach that searches for the common good of all of them measured by the accessibility rate, which is the ratio of the free parking places accessible for an autonomous car. Then, we simulate a real parking lot and the results show that the performance of our system is close to the optimum considering different communication ranges and penetration rates for the autonomous car.

摘要

汽车行业朝着全自动驾驶汽车的不断发展,推动了车辆传感器网络(VSN)中新的增值服务的设计。在VSN的背景下,配备越来越多车载传感器的自动驾驶汽车是一个移动节点,在VSN中交换感知到的信息和状态信息。在VSN的所有增值服务中,设计新的智能停车管理架构(自动驾驶汽车将与传统汽车共存于其中)是必不可少的,以便从与新一代汽车日益智能化相关的所有机会中获利。在这项工作中,我们在VSN之上设计了一种新的智能停车系统,该系统考虑了汽车的异构性,并基于一种协作方法为自动驾驶汽车提供前往最佳停车位的引导,该协作方法通过可达率来衡量所有车辆的共同利益,可达率是自动驾驶汽车可到达的空闲停车位的比例。然后,我们对一个真实停车场进行了模拟,结果表明,考虑到自动驾驶汽车的不同通信范围和穿透率,我们系统的性能接近最优。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/d1a436bff8e6/sensors-17-00848-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/55cea789d167/sensors-17-00848-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/eb2d0a74ee74/sensors-17-00848-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/eabdd4fbb72b/sensors-17-00848-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/251ba8b603a2/sensors-17-00848-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/0caed221db17/sensors-17-00848-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/da6c59aee562/sensors-17-00848-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/e791594ce011/sensors-17-00848-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/9cce20dc3f95/sensors-17-00848-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/d1a436bff8e6/sensors-17-00848-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/55cea789d167/sensors-17-00848-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/eb2d0a74ee74/sensors-17-00848-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/eabdd4fbb72b/sensors-17-00848-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/251ba8b603a2/sensors-17-00848-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/0caed221db17/sensors-17-00848-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/da6c59aee562/sensors-17-00848-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/e791594ce011/sensors-17-00848-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/9cce20dc3f95/sensors-17-00848-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/697c/5424725/d1a436bff8e6/sensors-17-00848-g009.jpg

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