Modeling aggressive driver behavior at unsignalized intersections

Kaysi, Isam; Abbany, Ali Samih

doi:10.1016/j.aap.2006.10.013

Cited by 94 publications

(34 citation statements)

References 14 publications

(19 reference statements)

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“…A couple of recent studies have also used observations at an intersection to record such characteristics as changing lanes, gap acceptance, and acceleration/deceleration rates to declare an act as being aggressive (see Kaysi andAbbany, 2007 andHamdar et al, 2008). Such observations are then correlated with the gender/age of the driver and situational/environmental factors.…”

Section: Aggressive Driving Studiesmentioning

confidence: 99%

Examining the influence of aggressive driving behavior on driver injury severity in traffic crashes

Paleti

Eluru

Bhat

2010

Accident Analysis & Prevention

210

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Section: Aggressive Driving Studiesmentioning

confidence: 99%

Examining the influence of aggressive driving behavior on driver injury severity in traffic crashes

Paleti

Eluru

Bhat

2010

Accident Analysis & Prevention

210

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“…Serag [12] used a gap/lag acceptance binary logit model considering the aggressive behavior of drivers as a factor which influences the probability of acceptance of a gap or lag. Kaisy and Abbany [13] had also investigated the aggressive behavior of minor street drivers at priority unsignalized intersections. A behavioral model is formulated which is incorporated into a simulation framework to estimate the delay and conflict measures at unsignalized intersections.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The literature review [12][13][14] revealed that very few studies are available which considers the aggressive …”

Section: Literature Reviewmentioning

confidence: 99%

Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions

Dutta

Ahmed

2017

J. Mod. Transport.

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Explicit traffic control measures are absent in uncontrolled intersections which make them susceptible to frequent conflicts and resulting collisions between vehicles. In developing countries like India, drivers at such intersections do not yield to higher priority movements which cause more crashes between vehicles. The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature. Three intersections in the northeast region of India have been selected as the case study area. Preliminary analysis of the data revealed that drivers behave aggressively, not because they have to wait for a long time at the stop line, but because of their lack of respect for traffic rules. Binary logit models are developed for minor road right turning vehicles which show that gap acceptance behavior is influenced by gap duration, clearing time and aggressive nature of drivers. The equations obtained were used to estimate the critical gaps for aggressive and non-aggressive drivers. Critical gaps are also calculated using an existing method called clearing behavior approach. It is also shown that the estimation of critical gap is more realistic if clearing time and aggressive behavior of drivers are considered.

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“…Gap and choice situation factors may include gap size, speed of vehicles, type of subject and conflicting vehicle types, waiting time, type of sign control, etc. [1][2][3][4][5][6]. Many researchers dealt with gap acceptance at unsignalized intersections with the assumption that priority is fully respected, such as Hawkes [7], Ashworth [8,9], Ashton [10], Miller [11], Polus et al [12], Davis and Swenson [13], Xu and Tian [14].…”

Section: Introductionmentioning

confidence: 99%

“…The driver characteristics that affect the gap acceptance decision may include gender, age, driving skill, etc. [1][2][3]. Gap and choice situation factors may include gap size, speed of vehicles, type of subject and conflicting vehicle types, waiting time, type of sign control, etc.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neuro-fuzzy interface system for gap acceptance behavior of right-turning vehicles at partially controlled T-intersections

Sangole

Patil

2014

J. Mod. Transport.

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Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed countries. Intersections with no specific priority to any movement, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geometry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neuro-fuzzy interface system (ANFIS) to the modeling of gap acceptance behavior of right-turning vehicles at limited priority T-intersections (in India, vehicles are driven on the left side of a road). Field data are collected using video cameras at four T-intersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver's decision (accepted/rejected). ANFIS models are developed by using 80 % of the extracted data (total data observations for major road rightturning vehicles are 722 and 1,066 for minor road rightturning vehicles) and remaining are used for model validation. Four different combinations of input variables are considered for major and minor road right turnings separately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. The models developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.

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Modeling aggressive driver behavior at unsignalized intersections

Cited by 94 publications

References 14 publications

Examining the influence of aggressive driving behavior on driver injury severity in traffic crashes

Examining the influence of aggressive driving behavior on driver injury severity in traffic crashes

Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions

Adaptive neuro-fuzzy interface system for gap acceptance behavior of right-turning vehicles at partially controlled T-intersections

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