ALERT: A Multi-layer and Vanet-based Approach to Minimize Accident Effects in Urban centers

• Yan V. Brandão Federal University of São João del Rei
• Lucas Marchisotti de Souza Federal University of São João del Rei
• Thiago Da Silva Gomides Federal University of São João del Rei
• Daniel Ludovico Guidoni Federal University of São João del Rei

DOI: https://doi.org/10.5753/sbrc_estendido.2020.12420

Abstract

The growth in the number of traffic accidents has become a cause for concern in urban centers. As a result of the increase of population in large cities and the increase in the number of vehicles, the accidents impacts may be even greater. In order to reduce these impacts, we present ALERT, a fully distributed algorithm capable of reducing congestion caused by accidents, thus contributing to an efficient urban mobility in smart cities. The algorithm performs the detection of accidents and the dissemination of warning messages in multiple hops. In addition, the system is able to share road traffic information, so vehicles know in advance the conditions of road displacement of nearby segments. Simulation results indicate that the proposed algorithm is capable of reducing the average travel time of the vehicles.

Keywords: Smart cities, Mobile networks, Manned and unmanned vehicle networks

References

Ahmed, E. and Gharavi, H. (2018). Cooperative vehicular networking: A survey. IEEETransactions on Intelligent Transportation Systems, 19(3):996-1014.

de Souza, A. M., Pedrosa, L. L. C., Botega, L. C., and Villas, L. (2018). Itssafe: Anintelligent transportation system for improving safety and traffic efficiency. In 2018IEEE 87th Vehicular Technology Conference (VTC Spring), pages 1-7.

Gomides, T., Fernandes, M., Souza, P., and Guidoni, D. (2019). Sgtd: Sistema de geren-ciamento de tráfego distribuído para redes veiculares.

Hussain, R., Hussain, F., and Zeadally, S. (2019). Integration of vanet and 5g security:A review of design and implementation issues. Future Generation Computer Systems,101:843 — 864.

Lopez, P. A., Behrisch, M., Bieker-Walz, L., Erdmann, J., Flôtterôd, Y.-P., Hilbrich, R.,Liicken, L., Rummel, J., Wagner, P., and WieBner, E. (2018). Microscopic traffic si-mulation using sumo. In The 21st IEEE International Conference on Intelligent Trans-portation Systems. IEEE.

Sommer, C., German, R., and Dressler, F. (2011). Bidirectionally Coupled Network andRoad Traffic Simulation for Improved IVC Analysis. IEEE Transactions on MobileComputing, 10(1):3-15.

Varga, A. and Hornig, R. (2008). An overview of the omnet++ simulation environment. InProceedings of the Ist International Conference on Simulation Tools and Techniquesfor Communications, Networks and Systems & Workshops, Simutools "08.

Wang, S., Djahel, S., Zhang, Z., and McManis, J. (2016). Next road rerouting: A multia-gent system for mitigating unexpected urban traffic congestion. IEEE Transactions onIntelligent Transportation Systems, 17(10):2888-2899.

Weiner, S. (2010). Feasibility of a 802.11 vanet based car accident alert system. Northe-astern University.

WHO (2020). Road traffic injuries. nttps://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries.