Implementing the Maximum Likelihood Method for Critical Gap Estimation under Heterogeneous Traffic Conditions

Arshad Jamal (), Muhammad Ijaz, Meshal Almosageah (), Hassan M. Al-Ahmadi, Muhammad Zahid, Irfan Ullah and Rabia Emhamed Al Mamlook
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Arshad Jamal: Traffic and Transportation Engineering Department, College of Engineering, Imam Abdurrahman Bin Faisal University, Dammam 34212, Saudi Arabia
Muhammad Ijaz: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Meshal Almosageah: Department of Civil Engineering, College of Engineering, Qassim University, Buraydah 52571, Saudi Arabia
Hassan M. Al-Ahmadi: Department of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Muhammad Zahid: Department of Civil, Geological, and Mining Engineering, École Polytechnique de Montréal, Montréal, QC H3T 1J4, Canada
Irfan Ullah: School of Transportation and Logistics, Dalian University of Technology, Dalian 116024, China
Rabia Emhamed Al Mamlook: Department of Industrial Engineering and Engineering Management, Western Michigan University, Kalamazoo, MI 49008, USA

Sustainability, 2022, vol. 14, issue 23, 1-13

Abstract: Gap acceptance analysis is crucial for determining capacity and delay at uncontrolled intersections. The probability of a driver accepting an adequate gap changes over time, and in different intersection types and traffic circumstances. The majority of previous studies in this regard have assumed homogeneous traffic conditions, and applying them directly to heterogeneous traffic conditions may produce biased results. Moreover, driver behavior concerning critical gap acceptance or rejection in traffic also varies from one location to another. The current research focused on the estimation of critical gaps considering different vehicle types (cars, and two- and three-wheelers) under heterogenous traffic conditions at uncontrolled crossings in the city of Peshawar, Pakistan. A four-legged uncontrolled intersection in the study area was used to investigate drivers’ gap acceptance behavior. The gaps were investigated for various vehicle types: two-wheelers, three-wheelers, and cars. For data collection, a video recording method was used, and Avidemux video editing software was used for data investigation. The study investigated the applicability of the maximum likelihood (MLM) method to analyzing a vehicle’s critical gap. MLM estimation results indicate that the essential critical gap values for car drivers are in the range from 7.45 to 4.6 s; for two-wheelers, the critical gap was in the range from 6.78 to 4.7 s; and for three-wheelers, the values were in the range from 6.3 to 4.9 s. At an uncontrolled intersection, the proposed method’s results can assist in distinguishing between different road user groups. This study’s findings are intended to be useful to both researchers and practitioners, particularly in developing countries with similar traffic patterns and vehicle adherence patterns at unsignalized intersections.

Keywords: traffic congestion; driver behavior; surveys; highway safety; critical gap estimation; risk assessment; maximum likelihood method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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