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Discrete Dynamics in Nature and Society
Volume 2018, Article ID 3821731, 14 pages
Research Article

Effect Analysis of Early Warning for Abandoned Object on Highway Based on Internet-of-Vehicles CA Model

1School of Automation, Wuhan University of Technology, Wuhan 430070, China
2School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan 442002, China
3School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China

Correspondence should be addressed to Wei Chen; nc.ude.tuhw@nehctaerg

Received 11 October 2017; Accepted 21 December 2017; Published 22 January 2018

Academic Editor: Tetsuji Tokihiro

Copyright © 2018 Juan Bao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An early warning on the highway will effectively reduce traffic accidents. Considering the influence of an abandoned object on driving behavior, a Visual-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (V-ATCA-AO) and an Internet-of-Vehicles-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (IoV-ATCA-AO) are proposed. Based on the two models, two types of traffic accidents caused by an abandoned object are analyzed: rear-end collision caused by the abandoned object ahead and collision of the vehicle with the abandoned object. Simulation results show the following: the accidents occur when the road density is smaller, while the accidents will not occur when the density is larger. The results are different from the rear-end collision rate curve without abandoned object in a single lane. Compared with the visual-based avoidance pattern in V-ATCA-AO, the Internet-of-Vehicles-based avoidance pattern in IoV-ATCA-AO can create an early warning for the abandoned object and tell the vehicle to make an earlier lane change and decelerate in advance, thereby significantly reducing the accident rate. Spatiotemporal characteristics in front of the abandoned object directly affect the accident rate: the less the “stability” of a traffic jam in front of the abandoned object, the higher the accident rate.