Evolution modeling of collective vehicles in vehicle ad hoc networks

Vehicular ad hoc networks (VANETs) are considered as one of most promising technologies for facilitating intelligent transportation system (ITS) that includes road safety, traffic management, and infotainment dissemination. However, most of existing models cannot support the dynamic interactions between traveling of vehicles and road information. This paper presents an evolution model for VANETs, which can describe the dynamic interaction process between the group movement behaviors of vehicles and road information from environments or from neighborhood vehicles. Simulation of typical scenarios indicates that vehicle traffic follows a kind of blind obedience, which inspires us that, through the control or influence of the state of some vehicles, it can be expected to find some technical means to control or induce evolutionary behavior of the entire transportation.

[1]  Xu Xiao-ming Approach to enhance convergence efficiency of Vicsek model , 2009 .

[2]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[3]  Panagiotis Papadimitratos,et al.  TraNS: realistic joint traffic and network simulator for VANETs , 2008, MOCO.

[4]  E. Shaw The Schooling of Fishes , 1962 .

[5]  Bo Yan,et al.  Intelligence Toll Management System of Highway Traffic , 2008, 2008 Workshop on Power Electronics and Intelligent Transportation System.

[6]  Xie Xiaopeng,et al.  Research on In-vehicle Bus Network Based on Internet of Things , 2012, 2012 Fourth International Conference on Computational and Information Sciences.

[7]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[8]  Zheng Yao,et al.  On the need for bidirectional coupling of road traffic microsimulation and network simulation , 2008, MobilityModels '08.

[9]  Serge Fdida,et al.  Modeling Mobility with Behavioral Rules: The Case of Incident and Emergency Situations , 2006, AINTEC.

[10]  Wang-Cheol Song,et al.  Data aggregation for Vehicular Ad-hoc Network using particle swarm optimization , 2012, 2012 14th Asia-Pacific Network Operations and Management Symposium (APNOMS).

[11]  Anupam Shukla,et al.  Multi-objective adaptive intelligent water drops algorithm for optimization & vehicle guidance in road graph network , 2013, 2013 International Conference on Informatics, Electronics and Vision (ICIEV).

[12]  Fabián E. Bustamante,et al.  An integrated mobility and traffic model for vehicular wireless networks , 2005, VANET '05.

[13]  Jaehyun Kim,et al.  Performance analysis on mobility of ad-hoc network for inter-vehicle communication , 2005, Fourth Annual ACIS International Conference on Computer and Information Science (ICIS'05).

[14]  A. Ōkubo Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. , 1986, Advances in biophysics.

[15]  Tharam S. Dillon,et al.  On-Road Sensor Configuration Design for Traffic Flow Prediction Using Fuzzy Neural Networks and Taguchi Method , 2013, IEEE Transactions on Instrumentation and Measurement.

[16]  V. A. Gajbhiye,et al.  Biologicaly inspired routing protocol for vehicular adhoc network , 2013, 2013 6th IEEE/International Conference on Advanced Infocomm Technology (ICAIT).

[17]  Inbum Jung,et al.  Variable speed limit to improve safety near traffic congestion on urban freeways , 2012, 2012 IEEE International Conference on Information Science and Technology.

[18]  Panganamala Ramana Kumar,et al.  Scheduling Automated Traffic on a Network of Roads , 2006, IEEE Transactions on Vehicular Technology.