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Real-Time Delay Estimation Model for Mixed Traffic Conditions Using RFID Detections as Data Source

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Abstract

Queue and delay are the primary performance measures of an intersection. This study aims to determine queue and delay for an approach of a signalized intersection using data obtained from RFID sensors. Model-based estimation schemes were developed for queue estimation that utilized the conservation of vehicles equation as the state equation. Relationships were developed between the time of detection of RFID cars during the red and green phase of a signal cycle and corresponding queue to frame the measurement equation. Real-time estimation of queue was carried out using Kalman filter estimation scheme and delays were estimated from the queue polygons developed. The queue and delay values estimated were comparable with the actual values indicating that the developed method can be used for real-time estimation of queue and delay. The estimation scheme can be used for Advanced Traveller Information Systems (ATIS) for mixed traffic conditions.

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References

  1. Saha A, Chandra S, Ghosh I (2017) Delay at signalized intersections under mixed traffic conditions. J Transport Eng Part A Syst 143(8):04017041

    Article  Google Scholar 

  2. Sharma R, Patel P, Umrigar N, Zala LB (2018) Delay estimation at signalized intersections under heterogeneous traffic conditions. Int Res J Eng Technol (IRJET) 5(05), pp 2395-0056

  3. Othayoth D, Rao KK (2018) Estimation of stopped delay to control delay conversion factor and development of delay model for non-lane based heterogeneous traffic. Eur Transport-Trasporti Europei 69:1–21

    Google Scholar 

  4. Murat YS, Kutluhan S, Cakici Z (2014) Investigation of cyclic vehicle queue and delay relationship for isolated signalized intersections. Elsevier Science Bv, Amsterdam

    Book  Google Scholar 

  5. Murat YS (2006) Comparison of fuzzy logic and artificial neural networks approaches in vehicle delay modeling. Transport Res Part C Emerg Technol 14(5):316–334

    Article  Google Scholar 

  6. Unal O, Cetin M (2014) Estimating queue dynamics and delays at signalized intersections from probe vehicle data (No. 14-4796)

  7. Li F, Tang K, Yao J, Li K (2017) Real-time queue length estimation for signalized intersections using vehicle trajectory data. Transp Res Rec 2623(1):49–59

    Article  MathSciNet  Google Scholar 

  8. Liu H, Rai L, Wang J, Ren C (2019) A new approach for real-time traffic delay estimation based on cooperative vehicle-infrastructure systems at the signal intersection. Arab J Sci Eng 44(3):2613–2625

    Article  Google Scholar 

  9. Ban XJ, Hao P, Sun Z (2011) Real time queue length estimation for signalized intersections using travel times from mobile sensors. Transport Res Part C Emerg Technol 19(6):1133–1156

    Article  Google Scholar 

  10. Hao P, Ban XJ, Guo D, Ji Q (2014) Cycle-by-cycle intersection queue length distribution estimation using sample travel times. Transport Res Part B Methodol 68:185–204

    Article  Google Scholar 

  11. Jayan A, Anusha SP (2019) Evaluation of Effectiveness of RFID and Bluetooth Sensors for Travel Time Studies under Mixed Traffic Conditions (No. 19-04397)

  12. Wu A, Yang X (2013) Real-time queue length estimation of signalized intersections based on RFID data. Proc Soc Behav Sci 96:1477–1484

    Article  Google Scholar 

  13. Abbas M, Rajasekhar L, Gharat A, Dunning JP (2013) Microscopic modeling of control delay at signalized intersections based on Bluetooth data. J Intell Transport Syst 17(2):110–122

    Article  Google Scholar 

  14. Mathew JK, Devi VL, Bullock DM, Sharma A (2016) Investigation of the use of Bluetooth sensors for travel time studies under Indian conditions. Transport Res Proc 17(December 2014):213–222

    Article  Google Scholar 

  15. Gore N, Arkatkar S, Joshi G, Bhaskar A (2019) Exploring credentials of Wi-Fi sensors as a complementary transport data: an Indian experience. IET Intel Transport Syst 13(12):1860–1869

    Article  Google Scholar 

  16. Anusha SP, Vanajakshi L, Subramanian SC (2021) Dynamical systems approach for queue and delay estimation at signalized intersections under mixed traffic conditions. Transport Lett. https://doi.org/10.1080/19427867.2021.1908492

    Article  Google Scholar 

  17. Cheng Y, Qin X, Jin J, Ran B, Anderson J (2011) Cycle-by-cycle queue length estimation for signalized intersections using sampled trajectory data. Transp Res Rec 2257(1):87–94

    Article  Google Scholar 

  18. Yin J, Sun J, Tang K (2018) A Kalman filter-based queue length estimation method with low-penetration mobile sensor data at signalized intersections. Transp Res Rec 2672(45):253–264

    Article  Google Scholar 

  19. Indo-HCM (2017) Indian highway capacity manual (Indo-HCM)

  20. Traffic Intelligence Server, ITS Planners and Engineers, Hyderabad, India

  21. May AD (1990) Traffic flow fundamentals. Prentice Hall Inc., Englewood Cliffs

    Google Scholar 

  22. Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82:35–45

    Article  MathSciNet  Google Scholar 

  23. Ajitha T (2012) A model based approach for real-time estimation of traffic density under Indian conditions. Ph.D. Thesis, Indian Institute of Technology, India

Download references

Acknowledgements

The authors acknowledge the support for this study by Transportation Research Centre (TRC) set up at College of Engineering, Trivandrum, Kerala through State Budget allotment 2016–2017 by the Kerala Government vide letter no. L4/30202/16/DTE dated 23/09/2016. The author also acknowledge the opportunity provided by the 6th conference of the Transportation Research Group of India (CTRG-2021) to present the work that formed the basis of manuscript.

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Correspondence to A. N. Muhammed Hafiz.

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Muhammed Hafiz, A.N., Anusha, S.P. Real-Time Delay Estimation Model for Mixed Traffic Conditions Using RFID Detections as Data Source. Transp. in Dev. Econ. 8, 22 (2022). https://doi.org/10.1007/s40890-022-00157-4

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