Table of Contents Author Guidelines Submit a Manuscript
Journal of Advanced Transportation
Volume 2017, Article ID 3082781, 17 pages
https://doi.org/10.1155/2017/3082781
Research Article

Will Automated Vehicles Negatively Impact Traffic Flow?

Department of Transport & Planning, Delft University of Technology, Delft, Netherlands

Correspondence should be addressed to S. C. Calvert; ln.tfledut@trevlac.c.s

Received 16 March 2017; Revised 15 June 2017; Accepted 20 August 2017; Published 28 September 2017

Academic Editor: Xiaopeng Li

Copyright © 2017 S. C. Calvert et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. E. Shladover, “Review of the State of Development of Advanced Vehicle Control Systems (AVCS),” Vehicle System Dynamics, vol. 24, no. 6-7, pp. 551–595, 1995. View at Publisher · View at Google Scholar · View at Scopus
  2. S. C. Calvert, A. Soekroella, I. R. Wilmink, and B. v. Arem, “Considering knowledge gaps for automated driving in conventional traffic,” in Proceedings of the Fourth International Conference on Advances in Civil, Structural and Environmental Engineering—ACSEE 2016, Rome, Italy, 2016.
  3. D. Milakis, M. Snelder, B. Van Arem, B. Van Wee, and G. H. De Almeida Correia, “Development and transport implications of automated vehicles in the Netherlands: Scenarios for 2030 and 2050,” European Journal of Transport and Infrastructure Research, vol. 17, no. 1, pp. 63–85, 2017. View at Google Scholar · View at Scopus
  4. C. Diakaki, M. Papageorgiou, I. Papamichail, and I. Nikolos, “Overview and analysis of Vehicle automation and communication systems from a motorway traffic management perspective,” Transportation Research Part A: Policy and Practice, vol. 75, pp. 147–165, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Timmer, L. B. Kool, R. Pel, F. van Est, and Brom., Converging roads: linking self-driving cars to public goals.
  6. M. Gorter, Adaptive Cruise Control in Practice, Delft University of Technology, 2015.
  7. S. O.-R. A. V. S. C. SAE, Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems.
  8. T. M. Gasser and D. Westhoff, “BASt-study: Definitions of automation and legal issues in Germany,” in Proceedings of the 2012 Road Vehicle Automation Workshop, 2012.
  9. S. F. Varotto, R. G. Hoogendoorn, B. V. Arem, and S. P. Hoogendoorn, “Empirical longitudinal driving behavior in authority transitions between adaptive cruise control and manual driving,” Transportation Research Record, vol. 2489, pp. 105–114, 2015. View at Publisher · View at Google Scholar · View at Scopus
  10. T. Litman, “Autonomous Vehicle Implementation Predictions,” Victoria Transport Policy Institute, vol. 28, 2014. View at Google Scholar
  11. A. Hars, “Top misconceptions of autonomous cars and self-driving vehicles. Thinking outside the box,” Innovation Briefs, 2016. View at Google Scholar
  12. R. Hoogendoorn, B. Van Arem, and S. Hoogendoorn, “Automated driving, traffic flow efficiency, and human factors,” Transportation Research Record, vol. 2422, pp. 113–120, 2014. View at Publisher · View at Google Scholar · View at Scopus
  13. R. Bertini, H. Wang, T. Knudson, and K. Carstens, “Preparing a Roadmap for Connected Vehicle/Cooperative Systems Deployment Scenarios: Case Study of the State of Oregon, USA,” in Proceedings of the International Symposium on Enhancing Highway Performance, ISEHP 2016, pp. 447–458, deu, June 2016. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Vander Werf, S. E. Shladover, M. A. Miller, and N. Kourjanskaia, “Effects of adaptive cruise control systems on highway traffic flow capacity,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1800, no. 1, pp. 78–84, 2002. View at Google Scholar · View at Scopus
  15. J. VanderWerf, S. Shladover, and M. A. Miller, “Conceptual development and performance assessment for the deployment staging of advanced vehicle control and safety systems,” California Partners for Advanced Transit and Highways (PATH), 2004. View at Google Scholar
  16. A. Kesting, M. Treiber, M. Schönhof, F. Kranke, and D. Helbing, “Jam-avoiding adaptive cruise control (ACC) and its impact on traffic dynamics,” in Traffic and Granular Flow’05, pp. 633–643, Springer, 2007. View at Google Scholar
  17. S. Shladover, D. Su, and X. Lu, “Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow,” Transportation Research Record: Journal of the Transportation Research Board, vol. 2324, pp. 63–70, 2012. View at Publisher · View at Google Scholar
  18. S. E. Shladover, “Cooperative (rather than autonomous) vehicle-highway automation systems,” IEEE Intelligent Transportation Systems Magazine, vol. 1, no. 1, pp. 10–19, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. PSC. and CAR., Planning for Connected and Automated Vehicles, Public Sector Consultants (PSC) Center for Automotive Research (CAR), Michigan, USA, 2017.
  20. V. Milanes, S. E. Shladover, J. Spring, C. Nowakowski, H. Kawazoe, and M. Nakamura, “Cooperative adaptive cruise control in real traffic situations,” IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 1, pp. 296–305, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Saffarian, J. C. F. De Winter, and R. Happee, “Automated driving: Human-factors issues and design solutions,” in Proceedings of the Human Factors and Ergonomics Society 56th Annual Meeting, HFES 2012, pp. 2296–2300, usa, October 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. F. Viti, S. P. Hoogendoorn, T. P. Alkim, and G. Bootsma, “Driving behavior interaction with ACC: Results from a Field Operational Test in the Netherlands,” in Proceedings of the 2008 IEEE Intelligent Vehicles Symposium, IV, pp. 745–750, June 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. A. Kesting and M. Treiber, “How reaction time, update time, and adaptation time influence the stability of traffic flow,” Computer-Aided Civil and Infrastructure Engineering, vol. 23, no. 2, pp. 125–137, 2008. View at Publisher · View at Google Scholar · View at Scopus
  24. L. Xiao and F. Gao, “Practical string stability of platoon of adaptive cruise control vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 1184–1194, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. A. H. Jamson, N. Merat, O. M. J. Carsten, and F. C. H. Lai, “Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions,” Transportation Research Part C: Emerging Technologies, vol. 30, pp. 116–125, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. F. A. Mullakkal-Babu, M. Wang, B. Van Arem, and R. Happee, “Design and analysis of full range adaptive cruise control with integrated collision a voidance strategy,” in Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016, pp. 308–315, bra, November 2016. View at Publisher · View at Google Scholar · View at Scopus
  27. M. Bultmann and A. J. H. Houben, “How autonomous vehicles could relieve or worsen traffic congestion, HERE Deutschland, 2016”.
  28. T. Tillema, G. J. v. d. Gelauff, J. Waard, S. Berveling, and Moorman., Paths to a Self-Driving Future, Five Transition Steps Identified, KiM, Netherlands Institute for Transport Policy Analysis, 2017.
  29. J. Svensson, Deployment paths for Vehicle and Road Automation, Support action for Vehicle and Road Automation network.
  30. D. Milakis, M. Snelder, B. Van Arem, B. Van Wee, and G. Correia, Development of automated vehicles in the Netherlands: scenarios for 2030 and 2050, Delft University of Technology, Delft, Netherlands, 2015.
  31. I. Automotive, “Emerging technologies: Autonomous cars-not if, but when,” IHS Automotive study, 2014, http://press.ihs.com/press-release/automotive/self-driving-cars-moving-industrys-drivers-seat. View at Google Scholar
  32. J. Dokic, B. Müller, and Meyer G., "European roadmap smart systems for automated driving." European Technology Platform on Smart Systems Integration. 2015.
  33. TechSciResearch (2015). Global Autonomous Car Technology Market Forecast and Opportunities, 2035–ADAS, Semi-Autonomous, Fully-Autonomous.
  34. J. Zmud, M. T. Tooley, J. Baker, and Wagner., Paths of automated and connected vehicle deployment: Strategic roadmap for state and local transportation agencies, Texas A&M Transportation Institute, 2015.
  35. P. Gao, H.-W. Kaas, D. Mohr, and D. Wee, Disruptive Trends That Will Transform The Auto Industry, McKinsey & Company, 2016.
  36. S. E. Shladover, “Progressive deployment steps leading toward an automated highway system,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1727, pp. 154–161, 2000. View at Google Scholar · View at Scopus
  37. P. Millot, Designing Human-Machine Cooperation Systems, John Wiley Sons, 2014.
  38. K. Dresner and P. Stone, “A multiagent approach to autonomous intersection management,” Journal of Artificial Intelligence Research, vol. 31, pp. 591–656, 2008. View at Google Scholar · View at Scopus
  39. G. Klunder, M. Li, and M. Minderhoud, “Traffic flow impacts of adaptive cruise control deactivation and (Re)activation with cooperative driver behavior,” Transportation Research Record, no. 2129, pp. 145–151, 2009. View at Publisher · View at Google Scholar · View at Scopus
  40. M. Huisman, Impacts of (Cooperative) Adaptive Cruise Control Systems on Traffic Flow, Delft University of Technology, 2016.
  41. L. C. Davis, “Effect of adaptive cruise control systems on traffic flow,” Physical Review E-Statistical, Nonlinear, and Soft Matter Physics, vol. 69, article 066110, no. 6, 2004. View at Publisher · View at Google Scholar · View at Scopus
  42. B. Van Arem, C. J. G. Van Driel, and R. Visser, “The impact of cooperative adaptive cruise control on traffic-flow characteristics,” IEEE Transactions on Intelligent Transportation Systems, vol. 7, no. 4, pp. 429–436, 2006. View at Publisher · View at Google Scholar · View at Scopus
  43. J. Pauwelussen and P. J. Feenstra, “Driver behavior analysis during ACC activation and deactivation in a real traffic environment,” IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 2, pp. 329–338, 2010. View at Publisher · View at Google Scholar · View at Scopus
  44. W. Knospe, L. Santen, A. Schadschneider, and M. Schreckenberg, “Empirical test for cellular automaton models of traffic flow,” Physical Review E-Statistical, Nonlinear, and Soft Matter Physics, vol. 70, article 016115, no. 1, 2004. View at Publisher · View at Google Scholar · View at Scopus
  45. M. Treiber, A. Kesting, and D. Helbing, “Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps,” Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, vol. 74, no. 1, Article ID 016123, 2006. View at Publisher · View at Google Scholar · View at Scopus
  46. J. Zhou and H. Peng, “Range policy of adaptive cruise control vehicles for improved flow stability and string stability,” IEEE Transactions on Intelligent Transportation Systems, vol. 6, no. 2, pp. 229–237, 2005. View at Publisher · View at Google Scholar · View at Scopus
  47. J. J. Ploeg, Analysis And Design of Controllers for Cooperative And Automated Driving, Technische Universiteit Eindhoven, 2014.
  48. M. Van Twuijver and M. Pol, “Car owners' experiences with in-car speed controlling systems in the Netherlands,” in Proceedings of The European Transport Conference (ETC), Strasbourg, France, 2004.
  49. N. Strand, J. Nilsson, I. C. M. Karlsson, and L. Nilsson, “Exploring end-user experiences: self-perceived notions on use of adaptive cruise control systems,” IET Intelligent Transport Systems, vol. 5, no. 2, pp. 134–140, 2011. View at Publisher · View at Google Scholar · View at Scopus
  50. T. P. Alkim, G. Bootsma, and S. P. Hoogendoorn, “Field operational test "the assisted driver",” in Proceedings of the 2007 IEEE Intelligent Vehicles Symposium, 2007. View at Scopus
  51. E. I. Vlahogianni, M. G. Karlaftis, and J. C. Golias, “Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume,” Transportation Research Part C: Emerging Technologies, vol. 14, no. 5, pp. 351–367, 2006. View at Publisher · View at Google Scholar · View at Scopus
  52. S. C. Calvert, H. Taale, and S. P. Hoogendoorn, “Quantification of motorway capacity variation: Influence of day type specific variation and capacity drop,” Journal of Advanced Transportation, vol. 50, no. 4, pp. 570–588, 2016. View at Publisher · View at Google Scholar · View at Scopus
  53. G. Marsden, M. McDonald, and M. Brackstone, “Towards an understanding of adaptive cruise control,” Transportation Research Part C: Emerging Technologies, vol. 9, no. 1, pp. 33–51, 2001. View at Publisher · View at Google Scholar · View at Scopus
  54. M. Hoedemaeker and K. A. Brookhuis, “Behavioural adaptation to driving with an adaptive cruise control (ACC),” Transportation Research Part F: Traffic Psychology and Behaviour, vol. 1, no. 2, pp. 95–106, 1998. View at Publisher · View at Google Scholar · View at Scopus
  55. S. Darbha and K. R. Rajagopal, “Intelligent cruise control systems and traffic flow stability,” Transportation Research Part C: Emerging Technologies, vol. 7, no. 6, pp. 329–352, 1999. View at Publisher · View at Google Scholar · View at Scopus
  56. P. Y. Li and A. Shrivastava, “Traffic flow stability induced by constant time headway policy for adaptive cruise control vehicles,” Transportation Research Part C: Emerging Technologies, vol. 10, no. 4, pp. 275–301, 2002. View at Publisher · View at Google Scholar · View at Scopus
  57. P. J. Zwaneveld and B. Van Arem, Traffic effects of automated vehicle guidance systems: A literature survey. 1997.
  58. B. Van Arem, J. M. Hogema, C. Vanderschuren, and Verheul., An assessment of the impact of autonomous intelligent cruise control.
  59. W. Schakel, V. Knoop, and B. Van Arem, “Integrated lane change model with relaxation and synchronization,” Transportation Research Record, vol. 2316, pp. 47–57, 2012. View at Publisher · View at Google Scholar · View at Scopus
  60. S. L. Cohen, “Application of relaxation procedure for lane changing in microscopic simulation models,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1883, pp. 50–58, 2004. View at Google Scholar · View at Scopus
  61. J. A. Laval and L. Leclercq, “Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model,” Transportation Research Part B: Methodological, vol. 42, no. 6, pp. 511–522, 2008. View at Publisher · View at Google Scholar · View at Scopus
  62. W. J. Schakel, B. Van Arem, and B. D. Netten, “Effects of cooperative adaptive cruise control on traffic flow stability,” in Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010, pp. 759–764, prt, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  63. M. Treiber, A. Hennecke, and D. Helbing, “Congested traffic states in empirical observations and microscopic simulations,” Physical Review E, vol. 62, no. 2, pp. 1805–1824, 2000. View at Publisher · View at Google Scholar · View at Scopus
  64. F. Kranke, H. Poppe, M. Treiber, and A. Kesting, “Driver assistance systems for the active congestion avoidance in road traffic,” VDI Berichte, vol. 22, pp. 375–391, 2006. View at Google Scholar · View at Scopus
  65. F. Kranke and H. Poppe, “Traffic guard-Merging sensor data and C2I/C2C information for proactive, congestion avoiding driver assistance systems,” in Proceedings of the 32nd FISITA World Automotive Congress 2008, 2008. View at Scopus
  66. Acura, "Adaptive Cruise Control (ACC) with Low Speed Follow," User Manual, 2017, http://m.acura.com/pdf/owners/2017/MDX/2017_MDX_Adaptive_Cruise_Control_with_Low-Speed_Follow.pdf.
  67. Toyota, "Toyota automatic highway driving assist," 2017, https://www.toyota-europe.com/world-of-toyota/safety-technology/toyota-automatic-highway-driving-assist.
  68. N. Lazeron and R. van Dinteren, Brein@Work, Bohn Stafleu van Loghum, Houten, 2010. View at Publisher · View at Google Scholar
  69. L. A. Pipes, “An operational analysis of traffic dynamics,” Journal of Applied Physics, vol. 24, no. 3, pp. 274–281, 1953. View at Publisher · View at Google Scholar · View at Scopus
  70. J. A. Laval and L. Leclercq, “A mechanism to describe the formation and propagation of stop-and-go waves in congested freeway traffic,” Philosophical Transactions of the Royal Society of London. Series A. Mathematical, Physical and Engineering Sciences, vol. 368, no. 1928, pp. 4519–4541, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  71. M. Bando, K. Hasebe, K. Nakanishi, and A. Nakayama, “Analysis of optimal velocity model with explicit delay,” Physical Review Letters E, vol. 58, no. 5, pp. 5429–5435, 1998. View at Google Scholar · View at Scopus
  72. D. C. Gazis, R. Herman, and R. W. Rothery, “Nonlinear follow-the-leader models of traffic flow,” Operations Research, vol. 9, no. 4, pp. 545–567, 1961. View at Publisher · View at Google Scholar · View at MathSciNet
  73. B. S. Kerner and S. L. Klenov, “Deterministic microscopic three-phase traffic flow models,” Journal of Physics A: Mathematical and General, vol. 39, no. 8, 2006. View at Google Scholar · View at MathSciNet
  74. Wiedemann, R. Simulation des Strassenverkehrsflusses. Kalsruhe, Traffic Engineering, University of Karlsruhe. 1974.
  75. S. P. Hoogendoorn, S. Ossen, and M. Schreuder, “Empirics of multianticipative car-following behavior,” Transportation Research Record: Journal of the Transportation Research Board, vol. 1965, no. 1, pp. 112–120, 2006. View at Publisher · View at Google Scholar · View at Scopus
  76. S. P. Hoogendoorn, S. Ossen, and M. Schreuder, “Properties of a microscopic heterogeneous multi-anticipative traffic flow model,” in Transportation and Traffic Theory, R. E. Allsop, M. G. H. Bell, and B. G. Heydecker, Eds., pp. 584–606, Elsevier Ltd., London, UK, 2007. View at Google Scholar
  77. S. H. Hamdar, H. S. Mahmassani, and M. Treiber, “From behavioral psychology to acceleration modeling: Calibration, validation, and exploration of drivers' cognitive and safety parameters in a risk-taking environment,” Transportation Research Part B: Methodological, vol. 78, pp. 32–53, 2015. View at Publisher · View at Google Scholar · View at Scopus
  78. R. G. Hoogendoorn, B. Van Arem, S. P. Hoogendoorn, and K. A. Brookhuis, “Applying the task-capability-interface model to the intelligent driver model in relation to complexity,” in Proceedings of the 92nd Transportation Research Board Annual Meeting, N. Academies, Wash, USA.
  79. M. Saifuzzaman and Z. Zheng, “Incorporating human-factors in car-following models: a review of recent developments and research needs,” Transportation Research Part C: Emerging Technologies, vol. 48, pp. 379–403, 2014. View at Publisher · View at Google Scholar
  80. Z. Zheng, “Recent developments and research needs in modeling lane changing,” Transportation Research Part B: Methodological, vol. 60, pp. 16–32, 2014. View at Publisher · View at Google Scholar · View at Scopus
  81. M. Keyvan-Ekbatani, V. L. Knoop, and W. Daamen, “Categorization of the lane change decision process on freeways,” Transportation Research Part C: Emerging Technologies, vol. 69, pp. 515–526, 2016. View at Publisher · View at Google Scholar · View at Scopus