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Red-light running traffic violations: A novel time-based method for determining a fine structure

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  • Baratian-Ghorghi, Fatemeh
  • Zhou, Huaguo
  • Zech, Wesley C.

Abstract

In 2016, the monetary fine for a red-light running (RLR) traffic violation varies widely in the U.S., with a fine of $50 in North Carolina and as much as $490 in California. Currently, a scientific method for determining the monetary fine based on the safety impacts associated with such violations does not exist, thereby causing disparities in fine structures. This study develops a novel fine structure for RLR traffic violations based upon the estimated economic impact of potential crashes by RLR violations and estimated delays caused by providing all-red intervals to prevent potential conflicts. A physical model is developed to determine the crash probability at a discrete time after the traffic signal turns red. The Highway Capacity Software is also employed to estimate additional delay incurred by road users. Considering that the use of red-light cameras is increasing in the nation, while it is often criticized as a revenue instrument, policymakers need to develop an objective fine structure that closely reflects the risk a RLR vehicle poses to other drivers.

Suggested Citation

  • Baratian-Ghorghi, Fatemeh & Zhou, Huaguo & Zech, Wesley C., 2016. "Red-light running traffic violations: A novel time-based method for determining a fine structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 55-65.
  • Handle: RePEc:eee:transa:v:93:y:2016:i:c:p:55-65
    DOI: 10.1016/j.tra.2016.08.015
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    References listed on IDEAS

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    1. Lu, Guangquan & Wang, Yunpeng & Wu, Xinkai & Liu, Henry X., 2015. "Analysis of yellow-light running at signalized intersections using high-resolution traffic data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 39-52.
    2. Wong, Timothy, 2014. "Lights, camera, legal action! The effectiveness of red light cameras on collisions in Los Angeles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 165-182.
    3. Obeng, Kofi & Burkey, Mark, 2008. "Explaining crashes at intersections with red light cameras: A note," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(5), pages 811-817, June.
    4. Rashidi, Eghbal & Parsafard, Mohsen & Medal, Hugh & Li, Xiaopeng, 2016. "Optimal traffic calming: A mixed-integer bi-level programming model for locating sidewalks and crosswalks in a multimodal transportation network to maximize pedestrians’ safety and network usability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 33-50.
    5. Egbendewe-Mondzozo, Aklesso & Higgins, Lindsey M. & Shaw, W. Douglass, 2010. "Red-light cameras at intersections: Estimating preferences using a stated choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 281-290, June.
    6. Maria De Paola & Vincenzo Scoppa & Mariatiziana Falcone, 2013. "The deterrent effects of the penalty points system for driving offences: a regression discontinuity approach," Empirical Economics, Springer, vol. 45(2), pages 965-985, October.
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    Cited by:

    1. Yuting Zhang & Xuedong Yan & Xiaomeng Li & Jiawei Wu & Vinayak V. Dixit, 2018. "Red-Light-Running Crashes’ Classification, Comparison, and Risk Analysis Based on General Estimates System (GES) Crash Database," IJERPH, MDPI, vol. 15(6), pages 1-15, June.

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