Comparative Appraisal of Critical Gap Estimation Techniques in the Context of U-turning Vehicles

Khan, Tathagatha; Vivek, Adheesh Kumar; Mohapatra, Smruti Sourava

doi:10.1177/03611981211035761

Cited by 13 publications

(6 citation statements)

References 31 publications

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“…The study by Khan et al [ 10 ], which focused on estimating the temporal and spatial critical gap of U-turning vehicles at uncontrolled median openings for six different types of U-turning vehicles, revealed that the critical gap values discovered during the research are significantly smaller than those reported in developed countries. This finding illustrates the aggressive driving nature of drivers in developing countries.…”

Section: Related Workmentioning

confidence: 84%

Modeling Behavior of U-Turning Vehicles at the Median Opening Using a Merging Behavior Approach: A Case Study in Bahir Dar City, Ethiopia

Wolelaw

Tessema

Alene

2022

Computational Intelligence and Neuroscience

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Median openings are one of the most commonly used road features, which are mainly used to allow U-turning movement in urban areas, and this study focuses mainly on modeling the behavior of U-turning vehicles at the median opening using a merging behavior approach. The purpose of the study is to estimate and model the critical gap of u-turning vehicles at the median opening under mixed traffic conditions. Under this study, the accepted gap, rejected gap, driver waiting time, merging time, and critical gap are estimated, and the modified Raff’s method and modified INAFOGA method are used for the estimation of a critical gap. However, modified INAFOGA is used for the modeling of critical gaps under mixed traffic conditions. In this study, sixteen median openings were selected in Bahir Dar city, and data were collected using a video recording technique at each selected median opening during the peak hour of the day. The necessary data were extracted using Forevid analysis software tools. Different types of traffic are involved in the mixed traffic, and each vehicle type is categorized according to the Ethiopian Road Authority’s 2013 design guide into seven different classes, such as 2-wheeler, 3-wheeler, passenger car, minibus, small bus and truck, medium bus, and medium truck. Among those traffic types, three vehicle classes (three-wheeler, passenger car, and minibus) were only considered due to the prohibition of U-turning movement for medium and large vehicles. For the modeling of critical gaps, waiting time and conflicting traffic flow are used as independent variables using the regression technique. Driver waiting time and the critical gap were found to be power related to passenger cars and minibuses and exponentially to three-wheelers. Conflicting traffic flow and critical gaps were power related to passenger cars and minibuses and linearly related to three-wheelers.

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Section: Related Workmentioning

confidence: 84%

Modeling Behavior of U-Turning Vehicles at the Median Opening Using a Merging Behavior Approach: A Case Study in Bahir Dar City, Ethiopia

Wolelaw

Tessema

Alene

2022

Computational Intelligence and Neuroscience

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“…It is important to note that the Ashworth method, using only acceptable intervals, may raise questions about the representativeness of the sample and the ability to account for all possible scenarios. However, if applied with appropriate limitations and careful analysis, this method can help to highlight the specifics of drivers' decision-making on the road and their impact on the critical interval (16) .…”

Section: Figure 5 Results For Each Methods Of Estimating the Critical...mentioning

confidence: 99%

Variable’s prediction of gap acceptance roundabout capacity model – Critical gap

Majid,

Ali

2023

Innovaciencia

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Introduction: The research relevance is determined by the assessment of the capacity of roundabouts and their efficiency are extremely important topics in transport engineering research. As road networks are constantly growing in size and complexity, congestion and insufficient flow capacity are becoming serious problems for traffic. The research aims to determine the critical interval at a certain roundabout using several statistical methods and to compare the results obtained by each of them, respectively. Material and Methods: The statistical methods used in the study included the Ruff, Wu, Troutbeck, Ashworth, and standard deviation methods. Results and Discussion: The results of the study show that the difference between the five methods is minimal, although each method has its characteristics. The analysis of the critical interval for the left and right bands showed that different methods may vary in their estimates, but the overall picture remains within acceptable convergence. The difference between the Wu method and the other methods was found to be negligible, except for the Ashworth method, which has a significant difference in the definition of the critical interval. Conclusion: Thus, all five methods can generally be used to calculate the critical interval at roundabouts. However, due to its simplicity and reliability, the Wu method was recommended for use. The practical significance of the study is that the results provide important guidance and information for the design and management of roundabouts. Estimation of the critical spacing is key to determining the optimal traffic flow regime, which affects safety, flow capacity and convenience for drivers.

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“…The characteristics of the approaching or conflicting vehicle, traffic volume, intersection characteristics and the maneuver planned by the driver of the subject vehicle (e.g., performing a right turn) affect the driver’s decision to accept or reject an open gap ( 1 ). Although temporal gaps are frequently used in research, the spatial gap is a key aspect that significantly affects the safety of vehicles entering from a minor road ( 2 ). Furthermore, the dynamic character of accepted gaps is attributable to heterogeneity in drivers’ demographics, such as age, gender, driving experience, and driving behavior.…”

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confidence: 99%

Drivers’ Dilemma at High-Speed Unsignalized Intersections

Bhatt

Gore

Shah

et al. 2023

Transportation Research Record: Journal of the Transportation R

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At unsignalized intersections, drivers typically reject smaller gaps and accept larger gaps in traffic. However, drivers experience a dilemma or confusion over a wide range of gaps, since incorrect decisions by them can lead to crashes. The present study quantifies the drivers’ dilemma at high-speed unsignalized intersections. Traffic data on gap size (temporal and spatial), driver’s decision (acceptance or rejection), the waiting time of the offending vehicle, the offending and conflicting vehicle types, and the speed of the conflicting vehicle are extracted from recorded video. The decisions by drivers to accept or reject gaps are modeled as a function of the gap size, the waiting time of the offending vehicle, and the speed of the conflicting vehicle using binary logit regression. The results reveal that the probability of rejection decreases as the gap size and waiting time of the subject vehicle increases. On the contrary, as the speed of the conflicting vehicle increases, the probability of rejection increases. The length and location of the dilemma zone were investigated using vehicle type, right-turning movement, and the speed of the conflicting vehicle, and a significant effect was noted. Moreover, the length and location of the dilemma zone are analytically quantified based on drivers’ compliance with a driver assistance system (DAS). The length of the dilemma decreases as the proportion of drivers’ compliance with the DAS increases. Further, the location of the dilemma zone shifts upstream of the intersection with an increase in drivers’ compliance with the DAS.

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Comparative Appraisal of Critical Gap Estimation Techniques in the Context of U-turning Vehicles

Cited by 13 publications

References 31 publications

Modeling Behavior of U-Turning Vehicles at the Median Opening Using a Merging Behavior Approach: A Case Study in Bahir Dar City, Ethiopia

Modeling Behavior of U-Turning Vehicles at the Median Opening Using a Merging Behavior Approach: A Case Study in Bahir Dar City, Ethiopia

Variable’s prediction of gap acceptance roundabout capacity model – Critical gap

Drivers’ Dilemma at High-Speed Unsignalized Intersections

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