Driver behaviour, dilemma zone and safety effects at urban signalised intersections in Greece

Papaioannou, Panagiotis

doi:10.1016/j.aap.2006.06.014

Cited by 181 publications

(95 citation statements)

References 10 publications

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“…Aggressive drivers maybe accompany with one or more kinds of attacking behaviors. Panagiotis proposed to use drivers' behavior as criteria of classification [5]. This paper considers Panagiotiss criteria.…”

Section: Classification Of Drivers Based On Driving Behaviormentioning

confidence: 99%

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Distribution of dilemma zone after intelligent transportation system established

Deng

Yang

2017

AIP Conference Proceedings

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Abstract. Dilemma zone refers to an area where vehicles can neither clear the intersection during the yellow interval nor stop safely before the stop line. The purpose of this paper is to analyzing the distribution of two types of dilemma zone after intelligent transportation system (ITS) established at Outer Ring Roads signalized intersections in Guangzhou Higher Education Mega Center. To collect field data a drone aircraft was used. When calculating the type II dilemma zone's distribution, we considered the information of drivers' aggressiveness, which was classified by driving speed and type I dilemma zone as well. We also compared the two types dilemma zone's distribution before and after ITS established and analyzed the changes, which was brought by ITS.

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Section: Classification Of Drivers Based On Driving Behaviormentioning

confidence: 99%

“…The first step's result shows that 18.75% percent of drivers belong to aggressive drivers. For more information, interested readers are referred to reference [5].…”

Section: Classification Of Drivers Based On Driving Behaviormentioning

confidence: 99%

Distribution of dilemma zone after intelligent transportation system established

Deng

Yang

2017

AIP Conference Proceedings

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“…Two types of dilemma zones are recognized in the literature [6][7][8][9][10][11]. Type I is defined as an area where the driver can neither stop without slamming on the brakes or clear the intersection safely without running the red light.…”

Section: Review Of Relevant Literaturementioning

confidence: 99%

Modeling the Dynamics of Driver’s Dilemma Zone Perception Using Agent Based Modeling Techniques

Abbas¹,

Machiani²

2016

IJT

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“…Many studies have investigated factors that influence the driver decision of whether to stop or go at the end of green. This includes in-vehicle factors (8), intersection features and dilemma zone safety measures (9,10,11), and investigations into individual driver traits (12,13). Unfortunately, transportation agencies do not often have access to detailed vehicle or driver information on a systemic basis, and consequently rely on more widely available tools to identify high-risk intersections for RLR and RLR-related crashes.…”

Section: Introductionmentioning

confidence: 99%

Use of High-Resolution Signal Controller Data to Identify Red Light Running

Lavrenz

Day

Grossman

et al. 2016

Transportation Research Record

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Intersection crashes are a safety concern for many transportation agencies, and those related to red-light-running (RLR) vehicles are of particular interest. Many camera-based RLR detection systems are controversial with the public, and there is relatively little published literature on the methodologies. This study proposes a methodology that combines high resolution signal controller data with conventional stop bar loop detection to identify vehicles that enter the intersection after the start of red, when many of the most serious RLR crashes occur. The methodology is validated using on-site video collection at several locations, and the algorithm was refined to reduce the incidence of false RLR indications. One case study demonstrates that an increase in side street green split from 20% to 24% of cycle length is associated with a 34% reduction in daily RLR counts, and a reduction in the likelihood of RLR by a factor of 1.7 -a substantial safety improvement for minimal cost. Additionally, law enforcement and transportation agencies can utilize this technique to more efficiently manage and deploy safety resources, especially in cases where detailed crash histories are unknown or too infrequent.

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Driver behaviour, dilemma zone and safety effects at urban signalised intersections in Greece

Cited by 181 publications

References 10 publications

Distribution of dilemma zone after intelligent transportation system established

Distribution of dilemma zone after intelligent transportation system established

Modeling the Dynamics of Driver’s Dilemma Zone Perception Using Agent Based Modeling Techniques

Use of High-Resolution Signal Controller Data to Identify Red Light Running

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