IRC-SET 2018 pp 389-400 | Cite as

Simulation-Based Analysis of a Network Model for Autonomous Vehicles with Vehicle-to-Vehicle Communication

  • Qi Yao YimEmail author
  • Kester Yew Chong Wong
Conference paper


Autonomous vehicle technology is an expansively researched area of transport that aims to tackle long-standing problems of traffic such as congestion, safety and efficiency. Many of these vehicles combine automated driving with communication among vehicles and infrastructure to bring about a seamless driving experience that would not have been possible with human driving. The development of computer simulations for such vehicles aims to address concerns on whether the benefits proposed by autonomous vehicle makers can be realized in various traffic environments. This paper assesses the efficiency of autonomous vehicles that are introduced on an arterial road network with features similar to Singapore’s road networks. A cellular automata simulation has been developed that considers vehicle-to-vehicle communication abilities of autonomous vehicles. A traffic data collection algorithm based on web traffic services was developed to estimate real-time travel times along each stretch of road in the network simulation, from which autonomous vehicles can optimize their speed and route for a faster journey time. Based on preliminary results, the simulation was tested under multiple traffic densities and situations. The results display interesting interactions between vehicles and road elements such as lanes and traffic lights, which has allowed both autonomous and non-autonomous vehicles to travel to their designated destination faster when autonomous vehicles have been introduced.


Autonomous vehicles Road model Road networks Traffic simulation Cellular automata 


  1. 1.
    Tan, C. K., & Tham, K. S. (2014). Autonomous vehicles, next stop: Singapore. Journeys, 5–11.Google Scholar
  2. 2.
    Litman, T. (2017). Autonomous vehicle implementation predictions (p. 28). Victoria Transport Policy Institute.Google Scholar
  3. 3.
    Gora, P., & Rüb, I. (2016). Traffic models for self-driving connected cars. Transportation Research Procedia, 14, 2207–2216.CrossRefGoogle Scholar
  4. 4.
    Hu, J., Kong, L., Shu, W., & Wu, M. Y. (2012, December). Scheduling of connected autonomous vehicles on highway lanes. In: 2012 IEEE Global Communications Conference (GLOBECOM) (pp. 5556–5561). IEEE.Google Scholar
  5. 5.
    The Rise of a Robotic Dawn in Services Industry. (2017, January 2). Retrieved from
  6. 6.
    Singapore to Start Trials of Driverless Trucks for Port Transport. (2017, January 9). Retrieved from
  7. 7.
    Nagel, K., & Schreckenberg, M. (1992). A cellular automaton model for freeway traffic. Journal de Physique I, 2(12), 2221–2229.CrossRefGoogle Scholar
  8. 8.
    Schadschneider, A., Chowdhury, D., Brockfeld, E., Klauck, K., Santen, L., & Zittartz, J. (2000). A new cellular automaton model for city traffic. In Traffic and Granular Flow ’99 (pp. 437–442). Berlin, Heidelberg: Springer.Google Scholar
  9. 9.
    Gora, P. (2009). Traffic simulation framework—A cellular automaton-based tool for simulating and investigating real road network traffic. Recent Advances in Intelligent Information Systems, 641–653.Google Scholar
  10. 10.
    Herrera, J. C., Work, D. B., Herring, R., Ban, X. J., Jacobson, Q., & Bayen, A. M. (2010). Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment. Transportation Research Part C: Emerging Technologies, 18(4), 568–583.CrossRefGoogle Scholar
  11. 11.
    Knospe, W., Santen, L., Schadschneider, A., & Schreckenberg, M. (2002). A realistic two-lane traffic model for highway traffic. Journal of Physics A: Mathematical and General, 35(15), 3369.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.National Junior CollegeSingaporeSingapore
  2. 2.Mathematics DepartmentNational Junior CollegeSingaporeSingapore

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