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Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia

Received: 29 May 2021     Accepted: 8 July 2021     Published: 15 July 2021
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Abstract

Studying Critical gap and headway distribution has vital role in reduction of traffic problems. Critical gap and its distribution are traffic characteristics that are used in determination of capacity, delay and level of service at unsignalized intersection. Many study has been done on critical gap in developed countries under homogeneous traffic and road conditions. This study is aimed to insight available headway distribution and critical gap of driver in urban intersection under heterogeneous traffic condition and weak lane discipline in developing country like Ethiopia. In this paper three unsignalized intersection in Adama city has been selected on the basis of traffic volume and importance of the intersection. The primary data that were used for this study were traffic volume, available headways, waiting time, geometry of road. By using digital Camera, videos data were recorded; later quantitative data were extracted from videos. Two Statistical Packages that were used in analysis of this study. Statistical Package for Social Science Statistic 20 was used to fit best distribution model of headway. Kolmogorov Smirnov and Anderson Darling testing techniques were conducted to check validity of model for headways in different flow ranges. From hypothesized distributions, exponential, gamma, lognormal and normal distributions were selected for different intersection. It has been indicated that, for higher flow rate lognormal distribution model is best fit in estimating cumulative density function of headway. Critical gaps of drivers for three selected intersections were also computed by using maximum likelihood method. Through Comparison of estimated values indicates that, Franko intersection has highest critical gap of 5.17sec.

Published in International Journal of Transportation Engineering and Technology (Volume 7, Issue 2)
DOI 10.11648/j.ijtet.20210702.12
Page(s) 48-59
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Headway Distribution, Maneuver Type Maximum Likelihood, Waiting Time

References
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[2] Abhishek, O., & Marko A. A. Boon, R.-Q. (2017). A single-server queue with batch arrivals and semi-Markov services. Queueing Syst, 217–240.
[3] Akhilesh et al., M. K. (2014). Study on Speed and Time-headway Distributions on Two-lane Bidirectional Road in Heterogeneous Traffic Condition. 11th Transportation Planning and Implementation Methodologies for Developing Countries, 428-438.
[4] Al-Obaedi, J. (2016). Estimation of Passenger Car Equivalents for Basic Freeway Sections at Different Traffic Conditions. World Journal of Engineering and Technology, 1-17.
[5] Amin, H. J. (2015). A review of Estimation approaches at uncontrolled intersection in case of heterogeneous traffic conditions. 5-9.
[6] Andyka, K., & Haris, N. (2011). Critical Gap Analysis of Dual Lane Roundabouts. Procedia Social and Behavioral Sciences, 709-717.
[7] Arvind et al., M. (2008). Macroscopic Review of Driver Gap Acceptance and Rejection Behavior in the US - Data Collection Results for 8 State Intersections. Minessota: Intelligent Transportation Systems Institute.
[8] Bartin et al., O. (2017). Simulation of Vehicle ’ Gap Acceptance Decision Using Reinforcement Learning. Uludağ University Journal of The Faculty of Engineering, 161-178.
[9] Doddapaneni et al., A. (2017). Multi Vehicle-Type Right Turning Gap Acceptance and Capacity Analysis at Uncontrolled Urban Intersections. Periodica Polytechnica Transportation Engineering, 1-9.
[10] Dutta, M. M. (2018). Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions. Journal of Modern Transportation, 119-132.
[11] Farah et al., H. (2009). A passing Gap Acceptance model for two lane rural highway. Transportmetrica, 159-172.
[12] Gavulova, A. e. (2012). Use of statistical techniques for critical gaps Estimation. “Reliability and Statistics in Transportation and Communication” (pp. 20-26). Zillina: Transport and Telecommunication Institute.
[13] Maurya, A. (2015). Speed and Time headway Distribution Under Mixed Traffic Condtion. Journal of Eastern Asia Society for Transportation Studies, 1-19.
[14] R. Morris, M. (2010). Highway Capacity Manual (Vol. I). Washington DC: Transportation Research Board Committee.
[15] Wan Ibrahim, W. (2007). Estimating Critical Gap Acceptance For Unsignalized T-Intersection Under Mixed Traffic Conditions. Procedings of Eastern Asia Society For Transportation Studies, 2-13.
[16] ZongZhong et al., T. (1999). Implementing the maximum likelihood methodology to measure a driver's critical gap. Transportation Research Part A 33, 187-197.
Cite This Article
  • APA Style

    Fikedu Rage Faye. (2021). Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia. International Journal of Transportation Engineering and Technology, 7(2), 48-59. https://doi.org/10.11648/j.ijtet.20210702.12

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    ACS Style

    Fikedu Rage Faye. Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia. Int. J. Transp. Eng. Technol. 2021, 7(2), 48-59. doi: 10.11648/j.ijtet.20210702.12

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    AMA Style

    Fikedu Rage Faye. Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia. Int J Transp Eng Technol. 2021;7(2):48-59. doi: 10.11648/j.ijtet.20210702.12

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  • @article{10.11648/j.ijtet.20210702.12,
      author = {Fikedu Rage Faye},
      title = {Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia},
      journal = {International Journal of Transportation Engineering and Technology},
      volume = {7},
      number = {2},
      pages = {48-59},
      doi = {10.11648/j.ijtet.20210702.12},
      url = {https://doi.org/10.11648/j.ijtet.20210702.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtet.20210702.12},
      abstract = {Studying Critical gap and headway distribution has vital role in reduction of traffic problems. Critical gap and its distribution are traffic characteristics that are used in determination of capacity, delay and level of service at unsignalized intersection. Many study has been done on critical gap in developed countries under homogeneous traffic and road conditions. This study is aimed to insight available headway distribution and critical gap of driver in urban intersection under heterogeneous traffic condition and weak lane discipline in developing country like Ethiopia. In this paper three unsignalized intersection in Adama city has been selected on the basis of traffic volume and importance of the intersection. The primary data that were used for this study were traffic volume, available headways, waiting time, geometry of road. By using digital Camera, videos data were recorded; later quantitative data were extracted from videos. Two Statistical Packages that were used in analysis of this study. Statistical Package for Social Science Statistic 20 was used to fit best distribution model of headway. Kolmogorov Smirnov and Anderson Darling testing techniques were conducted to check validity of model for headways in different flow ranges. From hypothesized distributions, exponential, gamma, lognormal and normal distributions were selected for different intersection. It has been indicated that, for higher flow rate lognormal distribution model is best fit in estimating cumulative density function of headway. Critical gaps of drivers for three selected intersections were also computed by using maximum likelihood method. Through Comparison of estimated values indicates that, Franko intersection has highest critical gap of 5.17sec.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Estimation of Critical Gap Using Maximum Likelihood Method at Unsignalized Intersection: A Case Study in Adama City, Ethiopia
    AU  - Fikedu Rage Faye
    Y1  - 2021/07/15
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    DO  - 10.11648/j.ijtet.20210702.12
    T2  - International Journal of Transportation Engineering and Technology
    JF  - International Journal of Transportation Engineering and Technology
    JO  - International Journal of Transportation Engineering and Technology
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    EP  - 59
    PB  - Science Publishing Group
    SN  - 2575-1751
    UR  - https://doi.org/10.11648/j.ijtet.20210702.12
    AB  - Studying Critical gap and headway distribution has vital role in reduction of traffic problems. Critical gap and its distribution are traffic characteristics that are used in determination of capacity, delay and level of service at unsignalized intersection. Many study has been done on critical gap in developed countries under homogeneous traffic and road conditions. This study is aimed to insight available headway distribution and critical gap of driver in urban intersection under heterogeneous traffic condition and weak lane discipline in developing country like Ethiopia. In this paper three unsignalized intersection in Adama city has been selected on the basis of traffic volume and importance of the intersection. The primary data that were used for this study were traffic volume, available headways, waiting time, geometry of road. By using digital Camera, videos data were recorded; later quantitative data were extracted from videos. Two Statistical Packages that were used in analysis of this study. Statistical Package for Social Science Statistic 20 was used to fit best distribution model of headway. Kolmogorov Smirnov and Anderson Darling testing techniques were conducted to check validity of model for headways in different flow ranges. From hypothesized distributions, exponential, gamma, lognormal and normal distributions were selected for different intersection. It has been indicated that, for higher flow rate lognormal distribution model is best fit in estimating cumulative density function of headway. Critical gaps of drivers for three selected intersections were also computed by using maximum likelihood method. Through Comparison of estimated values indicates that, Franko intersection has highest critical gap of 5.17sec.
    VL  - 7
    IS  - 2
    ER  - 

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Author Information
  • Department of Civil Engineering, Mettu University, Mettu, Ethiopia

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