Transportation

, Volume 31, Issue 3, pp 297–325 | Cite as

Network effects of intelligent speed adaptation systems

  • Ronghui Liu
  • James Tate
Article

Abstract

Intelligent Speed Adaptation (ISA) systems use in-vehicle electronic devices to enable the speed of vehicles to be regulated automatically. They are increasingly appreciated as a flexible method for speed management and control particularly in urban areas. On-road trials using a small numbers of ISA equipped vehicles have been carried out in Sweden, the Netherlands, Spain and the UK. This paper describes the developments made to enhance a traffic microsimulation model in order to represent ISA implemented across a network and the impact of this on the networks. The simulation modelling of the control system is carried out on a real-world urban network, and the impacts on traffic congestion, speed distribution and the environment assessed. The results show that ISA systems are more effective in less congested traffic conditions. Momentary high speeds in traffic are effectively suppressed, resulting in a reduction in speed variation which is likely to have a beneficial impact on safety. Whilst ISA reduces excessive traffic speeds in the network, it does not affect average journey times. In particular, the total vehicle-hours travelling at speeds below 10 km/hr have not changed, indicating that the speed control had not induced more slow-moving queues to the network. A statistically significant, eight percent, reduction in fuel consumption was found with full ISA penetration. These results are in accordance with those from field trials and they provide the basis for cost-benefit analyses on introducing ISA into the vehicle fleet. However, contrary to earlier findings from the Swedish ISA road trials, this study suggested that ISA is likely to have no significant effect on emission of gaseous pollutants CO, NOx and HC.

congestion driver support systems dynamic network modelling intelligent speed adaptation microsimulation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alkim T, Schuurman H & Tampere C (2000) Effect of external cruise and co-operative following on highway: An analysis with the MIXIC traffic simulation model. Proceedings of the 2000 Intelligent Vehicle Conference.Google Scholar
  2. Almquist S, Hyden C & Risser R (1991) Use of speed limiters in cars for increased safety and a better environment. Transport Research Record 1318: 34-39.Google Scholar
  3. Almquist S & Nygård M (1997) Dynamic Speed Adaptation. Field Trial with Automatic Speed Adaptation in Urban Area. Bulletin 154. Lund University, Sweden.Google Scholar
  4. Anderson RWG, McLean AJ, Farmer MJB, Lee BH & Brooks CG (1995) Vehicle travel speeds and the incidence of fatal pedestrian crashes. International Research Conference on the Biomecanics of Impact, 13–15 September IRCOBI Cong. 1995.Google Scholar
  5. Andre M & Pronello C (1997) Relative influence of acceleration and speed on emissions under actual driving conditions. International Journal of Vehicle Design 18(3/4).Google Scholar
  6. Barbosa HM, Tight MR & May AD (2000) A model of speed profiles for traffic calmed roads. Transportation Research 34A: 103-123.Google Scholar
  7. Barth M, An F, Younglove T, Scora G, Levine C, Ross M & Wenzel T (2000) Comprehensive Modal Emission Model. User Guide, University of California, Riverside Center for Environmental Research and Technology, 3rd January 2000.Google Scholar
  8. Beebe J, Bell MC & Tate JE (2003) Analysis of modal emissions — implications for air quality modelling and management. Paper presented at the 4th University Air Quality Conference, Prague, March 2003.Google Scholar
  9. Carsten O & Comte SL (1997) UK work on automatic speed control. In: Proceedings of ICTCT 97 Conference, November 1997, Lund, Sweden.Google Scholar
  10. Comte SL (2000). New Systems, new behaviour? Transportation Research 3F: 95-111.Google Scholar
  11. Comte SL, Wardman M & Whelan G (2000). Public acceptance of speed limiters for private car use: Implications for policy and implementation. Transport Policy 7: 259-267.Google Scholar
  12. Dahlstedt S (1994) The SARTRE-tables. Opinions about traffic and traffic safety of some European cities. VTI Report No 403/403A, Linköping, Sweden.Google Scholar
  13. DoT (1991) New car fuel consumption: the official figures December 1991, Department of Transport, UK.Google Scholar
  14. Ferreira LJA (1982) Car fuel consumption in urban traffic, the results of a survey in Leeds using instrumented vehicles. ITS Working Paper 162, Institute for Transport Studies, University of Leeds.Google Scholar
  15. Finch DJ, Kompfner P, Lockwood CR & Maycock G (1994) Speed, speed limits and accidents. Project Report 58. Transport Research Laboratory, Crowthorne, UK.Google Scholar
  16. Garber NJ & Gadirau R (1988) Speed variance and its influence on accidents. AAA Foundation for Traffic Safety, Washington DC, USA.Google Scholar
  17. Gipps PG (1981) A behavioural car-following model for computer simulation. Transportation Research 15B: 105-111.Google Scholar
  18. Hauer E (1971) Accidents, overtaking and speed control. Accident Analysis and Prevention 3: 1-13.Google Scholar
  19. Hodge AR (1992) A Review of the 20 mile/h speed zones: 1991. Traffic Engineering & Control 33(10): 545-547.Google Scholar
  20. Hoogendoorn SP & Minderhoud MM (2002) Motorway flow quality impacts of advanced driver support systems. Paper presented at 81st Transportation Research Board Annual Conference, Washington.Google Scholar
  21. Kulmala R (1996) Traffic safety and transport telematics. In: Proceedings of the Conference on Road Safety in Europe, 9–11 September 1996, Birmingham.Google Scholar
  22. Lind G (1999) Large-scale testing of intelligent speed adaptation — important evaluation issues. In: Proceedings of AET European Transport Conference, Seminar D, 91-103, Cambridge.Google Scholar
  23. Liu R (2003) The DRACULA microscopic traffic simulation model. To appear in Kitamura R, Kuwahara M & Schreckenberg M (eds) Transport Simulation, Springer.Google Scholar
  24. Liu R, Tate J & Boddy R (1999) Simulation modelling on the network effects of EVSC systems, Deliverable 11.3, External Vehicle Speed Control, Department of the Environment, Transport and the Region, UK.Google Scholar
  25. Liu R, van Vliet D & Watling DP (1995) DRACULA: Dynamic Route Assignment Combining User Learning and microsimulAtion. In: Proceedings of PTRC European Transport Forum, Seminar E, 143-152.Google Scholar
  26. Martin J (2002) After a 4 year trial — what the Swedes think of ISA. Traffic Engineering & Control 43(10): 376-379.Google Scholar
  27. Munden JM (1967) The relationship between a driver's speed and his accident rate. TRRL Report LR 88, Transport and Road Research Laboratory, Crowthorne, UK.Google Scholar
  28. Pasanen R & Salmivaara H (1993) Driving speeds and pedestrian safety in the City of Helsinki. Traffic Engineering & Control 34(6): 308-310.Google Scholar
  29. QUARTET (1992) Assessment of current tools for environment assessment in QUARTET, DRIVE II Project V2018: QUARTET, September 1992.Google Scholar
  30. Salusjärvi M (1981) The speed limit experiments on public roads in Finland. Technical Research Centre of Finland. Publication 7/1981. Espoo, Finland.Google Scholar
  31. van Vliet D (1982) SATURN — a modern assignment model. Traffic Engineering & Control 23(12): 578-581.Google Scholar
  32. van Vliet D (2002) SATURN 10.2 User Manual, Institute for Transport Studies, University of Leeds.Google Scholar
  33. Várhelyi A (1996) Dynamic Speed Adaptation Based on Information technology — a Theoretical Background. PhD Thesis, Lund University, Sweden.Google Scholar
  34. Várhelyi A & Mäkinen T (2001) The effects of in-car speed limiters: Field studies. Transportation Research 9C: 191-211.Google Scholar
  35. Webb PJ (1980) The effect of an advisory speed signal on motorway traffic speeds. TRRL Supplementary Report SR615, Transport and Road Research Laboratory, Crowthorne, UK.Google Scholar
  36. West LB Jr & Dunn JW (1971) Accidents, speed deviation and speed limits. Traffic Engineering 11(41), Washington DC, USA.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Ronghui Liu
    • 1
  • James Tate
    • 1
  1. 1.Institute for Transport StudiesUniversity of LeedsLeedsUK

Personalised recommendations