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A new microsimulation model for the evaluation of traffic safety performances

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  • Astarita, Vittorio
  • Guido, Giuseppe
  • Vitale, Alessandro
  • Giofré, Vincenzo

Abstract

Some papers have been recently presented (Cunto and Saccomanno 2007, Cunto and Saccomanno 2008, Saccomanno et al. 2008) on the potential of traffic microsimulation for the analysis of road safety. In particular, studies have confirmed that the reproduction by simulation of user behaviour under different flow and geometry conditions, can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network. The objective of this paper is to assess the validity of this approach; for this reason a microsimulation model and an automatic video detection system have been developed. The microscopic model allows the estimation of road safety performance through a series of indicators (Deceleration Rate to Avoid Crash, Time to Collision, Proportion of Stopping Distance), representing interactions in real time, between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The microscopic simulation model is used combined with a new video image traffic detection algorithm to calculate vehicle trajectories. Microscopic traffic flow parameters obtained by video detection are used to calibrate the microsimulation model, and the safety performance indicators obtained by the real vehicles trajectories can be compared with simulated scenarios where safety performance indicators are obtained on the simulated trajectories. Results indicate that the methodology can be useful in the estimation of safety performance indicators and in evaluating traffic control measures.

Suggested Citation

  • Astarita, Vittorio & Guido, Giuseppe & Vitale, Alessandro & Giofré, Vincenzo, 2012. "A new microsimulation model for the evaluation of traffic safety performances," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 51, pages 1-2.
    • Handle: RePEc:sot:journl:y:2012:i:51:p:2
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    File URL: http://hdl.handle.net/10077/6117
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    References listed on IDEAS

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    1. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    2. Robert E. Chandler & Robert Herman & Elliott W. Montroll, 1958. "Traffic Dynamics: Studies in Car Following," Operations Research, INFORMS, vol. 6(2), pages 165-184, April.
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    Cited by:

    1. Vittorio Astarita & Ciro Caliendo & Vincenzo Pasquale Giofrè & Isidoro Russo, 2020. "Surrogate Safety Measures from Traffic Simulation: Validation of Safety Indicators with Intersection Traffic Crash Data," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    2. Zhao, Peibo & Lee, Chris, 2016. "Evaluation of Rear-End Collision Risk in Car-Heavy Vehicle Mixed Traffic Flow on Freeways Using Surrogate Safety Measures," 57th Transportation Research Forum (51st CTRF) Joint Conference, Toronto, Ontario, May 1-4, 2016 319279, Transportation Research Forum.
    3. Li Li & Dong Zhang, 2018. "Merging Vehicles and Lane Speed-Flow Relationship in a Work Zone," Sustainability, MDPI, vol. 10(7), pages 1-13, June.
    4. Vittorio Astarita & Vincenzo Pasquale Giofrè & Giuseppe Guido & Alessandro Vitale, 2019. "A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data," Energies, MDPI, vol. 12(3), pages 1-22, January.
    5. Salvatore Leonardi & Natalia Distefano, 2023. "Turbo-Roundabouts as an Instrument for Improving the Efficiency and Safety in Urban Area: An Italian Case Study," Sustainability, MDPI, vol. 15(4), pages 1-21, February.

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