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Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection

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  • Cho, Hsun-Jung
  • Tseng, Ming-Te
  • Hwang, Ming-Chorng

Abstract

Based on the Lighthill–Whitham–Richards (LWR) traffic flow theory, this paper provides alternative methods to compute shockwave speed mainly by using detection data that reflects three states of vehicular presences: vehicles in moving, vehicles stopped, and void of vehicles. As the duration of a state is firmly identified within a cycle, the proposed methods compute shockwave speeds directly by means of Euclidian geometrics on time–space trajectory of shockwaves. This approach is also applicable to congested signal links with a long queue (but a residual queue) beyond detection zone. In addition, given signal timing and the shockwave speeds calculated by the methods, characteristics of arrival traffics, i.e. upstream flow rate and speed, can be predicted before the end of current cycle. It justifies that the methods are capable of whether to extend green phase before next cycle or not and will be a promising tool for real-time operations of signal control. Finally, the predicted shockwave speeds, upstream flow rate, and space mean speed by the proposed method are testified using simulated data from CORSIM. The mean absolute percentage errors of the estimated speeds of forward recovery shockwave and backward forming shockwave are 4.0% and 12.4% respectively. For the predicted flow rate and space mean speed of downstream arrival traffics, the mean absolute percentage errors are 18% and 4%, respectively. The results demonstrate the effectiveness of the presented approach.

Suggested Citation

  • Cho, Hsun-Jung & Tseng, Ming-Te & Hwang, Ming-Chorng, 2014. "Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 1151-1165.
    • Handle: RePEc:eee:apmaco:v:232:y:2014:i:c:p:1151-1165
    DOI: 10.1016/j.amc.2013.12.180
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    References listed on IDEAS

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    1. Wu, Xinkai & Liu, Henry X. & Geroliminis, Nikolas, 2011. "An empirical analysis on the arterial fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 255-266, January.
    2. Wu, Xinkai & Liu, Henry X., 2011. "A shockwave profile model for traffic flow on congested urban arterials," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1768-1786.
    3. Michalopoulos, Panos G. & Stephanopoulos, Gregory & Stephanopoulos, George, 1981. "An application of shock wave theory to traffic signal control," Transportation Research Part B: Methodological, Elsevier, vol. 15(1), pages 35-51, February.
    4. Panos G. Michalopoulos & Gregory Stephanopoulos & Vijay B. Pisharody, 1980. "Modeling of Traffic Flow at Signalized Links," Transportation Science, INFORMS, vol. 14(1), pages 9-41, February.
    5. Paul I. Richards, 1956. "Shock Waves on the Highway," Operations Research, INFORMS, vol. 4(1), pages 42-51, February.
    6. Cho, Hsun-Jung & Lo, Shih-Ching, 2002. "Modeling self-consistent multi-class dynamic traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 342-362.
    7. Denos C. Gazis, 2002. "The Origins of Traffic Theory," Operations Research, INFORMS, vol. 50(1), pages 69-77, February.
    8. Dion, Francois & Rakha, Hesham & Kang, Youn-Soo, 2004. "Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 99-122, February.
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