Two Wheeler Adjustment Factor to Estimate Queue Length at Signalized Intersection under Heterogeneous Traffic Conditions

Open Access

Year : 2023 | Volume : | : | Page : –
By

Jithender Jatoth,

  1. Research Scholar Department of Civil Engineering, National Institute of Technology Telangana India

Abstract

The two-wheeler adjustment factor derived in the present study to predict queue length at approaches of signalized intersections in mixed traffic conditions. The statistical distribution investigation carried out to understand the queuing behavior by using observed queue length obtained from the field. Field data was collected at Suchitra and KBR park intersections in Hyderabad City by using video graphic technic. Highway Capacity Manual (2010) adopted for estimating queue length with adjustment of saturation flow rate model given in the manual. Average number of vehicles in the queue estimated by using Highway Capacity Manual (2010) methodology with and without application of two-wheelers adjustment factor to saturation flow rate model given in the manual. The estimated queue length by using Highway Capacity Manual (2010) methodology with and without application of two-wheelers adjustment factor was compared with observed queue length obtained from the field. The comparative study showed the significance of adjustment factor for two-wheelers high for estimating queue length accurately.

Keywords: Saturation flow rate, mixed traffic, Queue length, Adjustment Factor

How to cite this article: Jithender Jatoth. Two Wheeler Adjustment Factor to Estimate Queue Length at Signalized Intersection under Heterogeneous Traffic Conditions. International Journal of Transportation Engineering and Traffic System. 2023; ():-.
How to cite this URL: Jithender Jatoth. Two Wheeler Adjustment Factor to Estimate Queue Length at Signalized Intersection under Heterogeneous Traffic Conditions. International Journal of Transportation Engineering and Traffic System. 2023; ():-. Available from: https://journals.stmjournals.com/ijtets/article=2023/view=90307

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References

1. Bonneson. (1990). “Modeling Queued Driver Behavior at Signalized Junctions.” transportation research Record., 1365, 99–107.
2. Lin, F.B., and Cheng, W.S. (1994). “Level-of-service analysis of toll plazas on freeway main lines.” Journal of Transportation Engineering., 120(2), 246–263.
3. Chang, G.L., and Su, C.C. (1995). “Predicting intersection queue with neural network |models.” 4. Viloria, F., Courage, K., and Donald, A. (2000). “Comparison of Queue-Length Models at
Signalized Intersections.” Transportation Research Record., 1710, 00–1600.
5. Cottrell, W.D. (2001). “Empirical freeway queuing duration model.” Journal of Transportation Engineering., 127(1), 13–20.
6. Lin, H., and Liu, D. (2011). “Study of Queue Length and Delay Calculation based on Taxi GPS Data.” ICCTP.
7. Chang, J., Talas, M., and Satya Muthuswamy C. (2013). “Simple Methodology for Estimating Queue Lengths at Signalized Intersections Using Detector Data.” Transportation Research Record: Journal of the Transportation Research Board, No. 2355, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 31–38.
8. Comert, G., and Cetin, M. (2011). “analytical evaluation of the error in queue length estimation at traffic signals from probe vehicle data.” IEEE transactions on intelligent transportation systems., 12,2.
9. Zhang, L., He, Z., Ye, W., Chu, J., Deng, L., (2013). “Queue length estimation based on floating car data.” Journal of Transportation System Engineering and Information Technology., 13(3), 78-
84.
10. Cai, Q., Wang, Z., Zheng, L., Bing, Wu., and Yinhai. (2014). “Wang Shock Wave Approach for Estimating Queue Length at Signalized Intersections by Fusing Data from Point and Mobile Sensors.” Transportation Research Record: Journal of the Transportation Research Board, No. 2422, Transportation Research Board of the National Academies, Washington, D.C., 2014, pp. 79–87.
11. Wu, P.Y., Pitchforth, J., and Kerrie M. (2014). “A Hybrid Queue-based Bayesian Network framework for passenger facilitation modeling.” Transportation Research Part C., 46, 247–260.
12. Motie, M., and Savla, K. (2017). “On a Vacation Queue Approach to Queue Size Computation for a Signalized Traffic Intersection.” IFAC Papers On Line., 50, 9700–9705.
13. Li, Q., Hu, H., and Lixin, M. (2015). “Queue Length Estimation Using Probe Vehicle Data for a Congested Arterial Road.” CICTP 2015.
14. Garcia, J.M., Olivier, B., and David, G. (2002). “Transient analytical solution of m/d/1/n queues.” j. appl. prob., 39, 853–864.
15. Amini, Z., Pedarsani, R., Alexander S., Pravin, V.(2015).“Queue-Length Estimation Using RealTime Traffic Data.”
16. Man, W. Ng. (2012). “Traffic Flow Theory-Based Stochastic Optimization Model for Work Zones on Two-Lane Highways.” Journal of Transportation Engineering., 138, 10.
17. Wu, P.Y., Pitchforth, J., and Kerrie M. (2014). “A Hybrid Queue-based Bayesian Network framework for passenger facilitation modeling.” Transportation Research Part C., 46, 247–260.
18. Smith, M.J. (2013). “A link-based elastic demand equilibrium model with capacity constraints and queueing delays.” Transportation Research Part C., 29, 131–147.
19. Li, J., Fujiwara, O., and Kawakami S. (2000). “A reactive dynamic user equilibrium model innetwork with Queues.” Transportation Research Part B., 34, 605–624.
20. Haijian, Li., Chen, N., Qin, L., Limin, J., and Rong, J. (2017). “Queue length estimation at signalized intersections based on magnetic sensors by different layout strategies.” Transportation Research Procedia., 25, 1626–1644.
21. Yang, Q., and Shi Z. (2018). “The evolution process of queues at signalized intersections under batch arrivals.” Physica A., 505, 413–425.
22. Moshtagh, M., Fathali, J., Smith, J. M. (2018). “The Stochastic Queue Core problem, evacuation networks, and state-dependent queues.” European Journal of Operational Research., 269, 730–
748.Transpo. Res.-C., 3(3), 175–191.


Open Access Article
Volume
Received February 2, 2021
Accepted November 12, 2021
Published January 12, 2023