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Assessing the Impact of Connected and Automated Vehicles. A Freeway Scenario

  • Michail MakridisEmail author
  • Konstantinos Mattas
  • Biagio Ciuffo
  • María Alonso Raposo
  • Christian Thiel
Conference paper
Part of the Lecture Notes in Mobility book series (LNMOB)

Abstract

In the next decades, road transport will undergo a deep transformation with the advent of connected and automated vehicles (CAVs), which promise to drastically change the way we commute. CAVs hold significant potential to positively affect traffic flows, air pollution, energy use, productivity, comfort, and mobility. On the other hand, there is an increasing number of sources and reports highlighting potential problems that may arise with CAVs, such as, conservative driving (relaxed thresholds), problematic interaction with human-driven vehicles (inability to take decisions based on eye contact or body language) and increased traffic demand. Therefore, it is of high importance to assess vehicle automated functionalities in a case-study simulation. The scope of this paper is to present some preliminary results regarding the impact assessment of cooperative adaptive cruise control (CACC) on the case-study of the ring road of Antwerp, which is responsible for almost 50% of the traffic and pollution of the city. Scenarios with various penetration rates and traffic demands were simulated showing that coordination of vehicles may be needed to significantly reduce traffic congestion and energy use.

Keywords

Cooperative adaptive cruise control (CACC) Connected and automated vehicles (CAVs) Platooning Traffic simulation Traffic flow 

References

  1. Alonso Raposo M, Ciuffo B, Makridis M, Thiel C (to be published) The r-evolution of driving: from Connected Vehicles to Coordinated Automated Road Transport (C-ART). Eur CommGoogle Scholar
  2. Arnaout GM, Bowling S (2014) A progressive deployment strategy for cooperative adaptive cruise control to improve traffic dynamics. Int J Autom Comput 11:10–18. doi: 10.1007/s11633-014-0760-2 CrossRefGoogle Scholar
  3. Calvert SC, van den Broek THA, van Noort M (2012) Cooperative driving in mixed traffic networks - Optimizing for performance. In: 2012 IEEE Intelligent Vehicles Symposium. pp 861–866Google Scholar
  4. Chin H, Okuda H, Tazaki Y, Suzuki T (2015) Model predictive cooperative cruise control in mixed traffic. In: IECON 2015—41st Annual Conference IEEE Industrial Electronics Society. pp 003199–003205Google Scholar
  5. Degraeuwe B, Thunis P, Clappier A, Weiss M, Lefebvre W, Janssen S, Vranckx S (2016) Impact of passenger car NOx emissions and NO2 fractions on urban NO2 pollution—Scenario analysis for the city of Antwerp, Belgium. Atmos Environ 126:218–224. doi: 10.1016/j.atmosenv.2015.11.042 CrossRefGoogle Scholar
  6. Do lower speed limits on motorways reduce fuel consumption and pollutant emissions?—European Environment Agency. https://www.eea.europa.eu/themes/transport/speed-limits. Accessed 1 Jun 2017
  7. Fakharian Qom S, Xiao Y, Hadi M (2016) Evaluation of Cooperative Adaptive Cruise Control (CACC) vehicles on managed lanes utilizing macroscopic and mesoscopic simulationGoogle Scholar
  8. Frank M, Wolfe P (1956) An algorithm for quadratic programming. Nav Res Logist Q 3:95–110. doi: 10.1002/nav.3800030109 MathSciNetCrossRefGoogle Scholar
  9. Gipps PG (1981) A behavioural car-following model for computer simulation. Transp Res Part B Methodol 15:105–111. doi: 10.1016/0191-2615(81)90037-0 CrossRefGoogle Scholar
  10. Ilgin Guler S, Menendez M, Meier L (2014) Using connected vehicle technology to improve the efficiency of intersections. Transp Res Part C Emerg Technol 46:121–131. doi: 10.1016/j.trc.2014.05.008 CrossRefGoogle Scholar
  11. Kloostra B, Roorda MJ (2017) Fully autonomous vehicles: analyzing transportation network performance and operating scenarios in the Greater Toronto Area, CanadaGoogle Scholar
  12. Lefebvre W, Vercauteren J, Schrooten L, Janssen S, Degraeuwe B, Maenhaut W, de Vlieger I, Vankerkom J, Cosemans G, Mensink C, Veldeman N, Deutsch F, Van Looy S, Peelaerts W, Lefebre F (2011) Validation of the MIMOSA-AURORA-IFDM model chain for policy support: Modeling concentrations of elemental carbon in Flanders. Atmos Environ 45:6705–6713. doi: 10.1016/j.atmosenv.2011.08.033 CrossRefGoogle Scholar
  13. Lefebvre W, Van Poppel M, Maiheu B, Janssen S, Dons E (2013) Evaluation of the RIO-IFDM-street canyon model chain. Atmos Environ 77:325–337. doi: 10.1016/j.atmosenv.2013.05.026 CrossRefGoogle Scholar
  14. Litman T (2015) Autonomous vehicle implementation predictions: Implications for transport planningGoogle Scholar
  15. Lu X-Y, Kan XD, Shladover SE, Wei D, Ferlis RA (2017) An enhanced microscopic traffic simulation model for application to connected automated vehiclesGoogle Scholar
  16. Mahmassani HS (2016) 50th anniversary invited article—autonomous vehicles and connected vehicle systems: Flow and operations considerations. Transp Sci 50:1140–1162. doi: 10.1287/trsc.2016.0712 CrossRefGoogle Scholar
  17. Ngoduy D (2013) Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach. Commun Nonlinear Sci Numer Simul 18:2838–2851. doi: 10.1016/j.cnsns.2013.02.007 MathSciNetCrossRefzbMATHGoogle Scholar
  18. Open street maps https://planet.openstreetmap.org/ Accessed 31 May 2017
  19. Pavlovic J, Marotta A, Ciuffo B (2016) CO2 emissions and energy demands of vehicles tested under the NEDC and the new WLTP type approval test procedures. Appl Energy 177:661–670. doi: 10.1016/j.apenergy.2016.05.110 CrossRefGoogle Scholar
  20. Shladover S, Su D, Lu X-Y (2012) Impacts of cooperative adaptive cruise control on freeway traffic flow. Transp Res Rec J Transp Res Board 2324:63–70. doi: 10.3141/2324-08 CrossRefGoogle Scholar
  21. van Arem B, van Driel CJG, Visser R (2006) The impact of cooperative adaptive cruise control on traffic-flow characteristics. IEEE Trans Intell Transp Syst 7:429–436. doi: 10.1109/TITS.2006.884615 CrossRefGoogle Scholar
  22. Xiao L, Wang M, van Arem B (2017) Realistic car-following models for microscopic simulation of adaptive and cooperative adaptive cruise control vehiclesGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Michail Makridis
    • 1
    Email author
  • Konstantinos Mattas
    • 1
  • Biagio Ciuffo
    • 1
  • María Alonso Raposo
    • 1
  • Christian Thiel
    • 1
  1. 1.Directorate for Energy, Transport and Climate ChangeEuropean Commission – Joint Research CentreIspraItaly

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