Paper Info
Title
Road collisions avoidance using vehicular cyber-physical systems: a taxonomy and review.
Abstract
Road traffic is known to have its own complex dynamics. One implication of complexity is that road traffic collisions have become an unwelcome but unavoidable part of human life. One of the major causes of collisions is the human factor. While car manufacturers have been focusing on developing feasible solutions for autonomous and semi-autonomous vehicles to replace or assist human drivers, the proposed solutions have been designed only for individual vehicles. The road traffic, however, is an interaction-oriented system including complex flows. Such a system requires a complex systems approach to solving this problem as it involves considering not only pedestrians, road environment, but also road traffic which can include multiple vehicles. Recent research has demonstrated that large-scale autonomous vehicular traffic can be better modeled using a collective approach as proposed in the form of vehicular cyber-physical systems (VCPS) such as given by Li et al. (IEEE Trans Parallel Distrib Syst 23(9):1775–1789, 2012) or Work et al. (Automotive cyber physical systems in the context of human mobility. In: National workshop on high-confidence automotive cyber-physical systems, Troy, MI, 2008).  To the best of our knowledge, there is currently no comprehensive review of collision avoidance in the VCPS. In this paper, we present a comprehensive literature review of VCPS from the collision-avoidance perspective. The review includes a careful selection of articles from highly cited sources presented in the form of taxonomy. We also highlight open research problems in this domain.
Year
DOI
Venue
2016
10.1186/s40294-016-0025-8
CASM
Keywords
DocType
Volume
Agent based modelling, Complex system, Cyber physical system, Collisions, Emotions, Road traffic, Vehicular cyber physical system
Journal
4
Issue
ISSN
Citations 
1
2194-3206
2
PageRank 
References 
Authors
0.38
14
2
Name
Order
Citations
PageRank
Faisal Riaz120.38
Muaz A. Niazi217724.55