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Evaluating the assumption of independent turning probabilities

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  • Bar-Gera, Hillel
  • Mirchandani, Pitu B.
  • Wu, Fan

Abstract

Several urban traffic models make the convenient assumption that turning probabilities are independent, meaning that the probability of turning right (or left or going straight through) at the downstream intersection is the same for all travelers on that roadway, regardless of their origin or destination. In reality most travelers make turns according to planned routes from origins to destinations. The research reported here identifies and quantifies the deviations that result from this assumption of independent turning probabilities. An analysis of this type requires a set of reasonably realistic "original" route flows, which were obtained by a static user-equilibrium traffic assignment and an entropy maximization condition for most likely route flows. These flows are compared with those route flows resulting from the Assumption of Independent Turning Probabilities (ITP). A small subnetwork of 3Â km by 5Â km in Tucson, Arizona, was chosen as a case study. An overall "typical ratio" of 2.2 between original route flows and ITP route flows was obtained. Aggregating route flows to origin-destination flows led to an overall "typical ratio" of 1.7. Such deviations are particularly high for routes that go back-and-forth, reaching a ratio of more than 3 in certain time periods. Substantial deviations for origins and destinations that are on the same border of the subnetwork are also observed in the analyses. In addition, under the ITP assumption, morning rush hour traffic peaking is the same in all directions, while in the original flows some directions do not exhibit a peak in the morning rush hour period. Overall, the conclusion of the paper is that the assumption of independent turning probabilities leads to substantial deviations both at the route level and at the origin-destination level, even for such a small network of the case study. These deviations are particularly detrimental when a network is being modeled and studied for route-based measures of effectiveness such as the number and types of routes passing a point - for monitoring specified vehicles and/or managing detouring strategies.

Suggested Citation

  • Bar-Gera, Hillel & Mirchandani, Pitu B. & Wu, Fan, 2006. "Evaluating the assumption of independent turning probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 903-916, December.
    • Handle: RePEc:eee:transb:v:40:y:2006:i:10:p:903-916
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    References listed on IDEAS

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    1. Chang, Tang-Hsien & Sun, Guey-Yin, 2004. "Modeling and optimization of an oversaturated signalized network," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 687-707, September.
    2. Oded Berman & Dmitry Krass & Chen Wei Xu, 1995. "Locating Discretionary Service Facilities Based on Probabilistic Customer Flows," Transportation Science, INFORMS, vol. 29(3), pages 276-290, August.
    3. Yang, Hai & Zhou, Jing, 1998. "Optimal traffic counting locations for origin-destination matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 109-126, February.
    4. Hillel Bar-Gera, 2002. "Origin-Based Algorithm for the Traffic Assignment Problem," Transportation Science, INFORMS, vol. 36(4), pages 398-417, November.
    5. Bell, Michael G. H., 1991. "The real time estimation of origin-destination flows in the presence of platoon dispersion," Transportation Research Part B: Methodological, Elsevier, vol. 25(2-3), pages 115-125.
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    Cited by:

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    3. Papinski, Dominik & Scott, Darren M., 2011. "A GIS-based toolkit for route choice analysis," Journal of Transport Geography, Elsevier, vol. 19(3), pages 434-442.

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