Study of Drivers’ Behaviour at a Passive Railway Crossing

Kasalica, Sandra; Vukadinović, Radisav; Lučanin, Vojkan

doi:10.7307/ptt.v24i3.312

Cited by 10 publications

(9 citation statements)

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“…More generally, the majority of participants (80.6%) reported that they would enter the crossing during a time when flashing lights would be activated at an active level crossing. This underestimation of speed may go some way to explaining results from previous research, where a substantial proportion of drivers (57-77%) were observed to cross a passive rail level crossing when a train approached (Kasalica et al, 2012;Tey et al, 2011). The decision a driver must make about when it is safe to cross will be influenced by how confident they feel about their perception of the train speed, which was shown in this study to be quite high, despite poor performance.…”

Section: Effects On Decisions To Enter Level Crossings and Safetysupporting

confidence: 48%

“…Observational studies of actual rail level crossings report that 57-77% of drivers will cross (the rail crossing) in the presence of an approaching train (Kasalica et al, 2012;Tey et al, 2011). Additionally, observational studies identify that the majority of drivers slow down and perform visual scanning behaviours as they approach the rail tracks, prior to crossing (Kasalica et al, 2012;Meeker and Barr, 1989). The obvious checking for the behaviour of trains exhibited by drivers supports the suggestion that perceptual errors rather than deliberate violations underlie many train and road user crashes.…”

Section: Factors Associated With Drivers' Crossing Behavioursmentioning

confidence: 74%

“…Numerous train crash investigations have found that driver errors rather than deliberate violations are primarily responsible for train and road vehicle crashes (Baysari et al, 2009;Caird, 2002;Salmon et al, 2013). Observational studies of actual rail level crossings report that 57-77% of drivers will cross (the rail crossing) in the presence of an approaching train (Kasalica et al, 2012;Tey et al, 2011). Additionally, observational studies identify that the majority of drivers slow down and perform visual scanning behaviours as they approach the rail tracks, prior to crossing (Kasalica et al, 2012;Meeker and Barr, 1989).…”

Section: Factors Associated With Drivers' Crossing Behavioursmentioning

confidence: 99%

See 2 more Smart Citations

Is it safe to cross? Identification of trains and their approach speed at level crossings

et al. 2018

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Section: Effects On Decisions To Enter Level Crossings and Safetysupporting

confidence: 48%

Section: Factors Associated With Drivers' Crossing Behavioursmentioning

confidence: 74%

Section: Factors Associated With Drivers' Crossing Behavioursmentioning

confidence: 99%

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Is it safe to cross? Identification of trains and their approach speed at level crossings

et al. 2018

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“…Another field study in Australia shows that 59% of drivers are not compliant to stop signs [8]. Kasalica et al [9] found that 8 out of 35 drivers (23%) did not stop or slow down after perceiving an approaching train at a passive HRGC in Serbia. Driver violations are the main cause of incidents at HRGCs, and a new technology has the potential to mitigate the problem by providing train information to drivers directly.…”

Section: Introductionmentioning

confidence: 99%

Transmission Range Evaluations for Connected Vehicles at Highway-Rail Grade Crossings

Hsu¹,

Jones

2017

Designs

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This study evaluates the transmission range requirements of Connected Vehicles (CVs) at Highway-Rail Grade Crossings (HRGCs) in terms of safety improvement. The safety improvement of HRGCs is evaluated by using a reliability-based risk analysis that calculates risk of collision for CVs and non-CVs. Trains are assumed to have onboard units that transmit train location and speed information to CVs via vehicle to vehicle communications. The stopping distance and time to collision of a vehicle are the demand functions in reliability-based risk analysis. The demand functions consist of probability density functions of a vehicle's initial speed, perception-reaction time, initial deceleration rate, final speed, and final deceleration rate. Train arrival time depending on the train speed and transmission range is the supply threshold for calculating the CV's risk of collision at passive HRGCs. The transmission range's projected highway distance is the supply threshold for CVs at active HRGCs. After deriving probability density functions of demand functions from the published data, Monte Carlo simulations generate the probabilities or risks that a CV would fail to stop within the transmission range or train arrival time. With the provision of a 600 m transmission range, the risk of collision for the CV is lower than that for the non-CV with a 300 m sight distance to the train at the passive HRGC. The CV's risk of collision is lower than the non-CV's with a 300 m transmission range at active HRGCs. The CV application at HRGCs can improve safety by reducing CVs' risk of collision. A 600 m transmission range is desirable at passive HRGCs. A 300 m transmission is sufficient for CVs at active HRGCs. Overall, a 600 m transmission range is feasible to improve the safety at passive and active HRGCs.

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“…delu šest je objašnjeno da je sprovedena studija direktnog ponašanja vozača pri nailasku voza na ruralnom putnom prelazu osiguranom samo drumskom signalizacijom na jugu Srbije, a za koji su autori imali saznanja da će se u skorije vreme osigurati automatskim uređajem putnog prelaza sa polubranicima. Fokus te studije je bio na tome da li su vozači stali ili usporili pre prelaska, koliku su bezbednosnu marginu sebi ostavili vozači koji su prešli ispred nailazećeg voza, kako su se ponašali u uslovima nedovoljne preglednosti nailazećeg voza[71]. svrhu istraživanja i snimanja ponašanja učesnika u drumskom saobraćaju na izabranom putnom prelazu bila su uključena dva istraživača.…”

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Safety improvement of traffic at railway crossings

Kasalica¹

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In this paper there were developed statistical models for estimation of accident frequency, accident severity and empirical risk, that correspond to local characteristics of crossings in Serbia. The goal was to identify high risk locations. The data used were from five year period. Several regression models were tried (Poisson regression, Zeroinflated Poisson-ZIP, negative binomial model-NB, Zero-inflated NB model-ZINB). The most suitable model for modeling accident frequency was ZIP model. For modeling accident severity multinomial logit model was used, whereas the best model for empirical risk was ZINB model. The variables significantly linked to accident frequency and severity were identified. Finally, the calibrated models together with two ranking criteria were used in order to indentify high risk crossings in Serbian railway network. The first criterion was mean total risk at a crossing, and the second one was based on mean empirical risk. The accepted models for accident frequency and severity were used for estimating the reduction of accidents at railway crossings applying the corresponding technical procedures for safety improvement. In order to accomplish this, there has been performed a complete analysis of technologies and procedures from various regions, which are used nowadays or are in phase of examining there efficency. Their results and experience were used to estimate the efficency that those procedures would have in Serbia. In this paper the drivers' behaviour on railway crossing was also studied, both with road signs and with active warining devices. This upgrade from one system to another was useful for examining drivers' behaviour in two different systems, as well as the safety effects that concequently appeared.

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Study of Drivers’ Behaviour at a Passive Railway Crossing

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Cited by 10 publications

References 0 publications

Is it safe to cross? Identification of trains and their approach speed at level crossings

Is it safe to cross? Identification of trains and their approach speed at level crossings

Transmission Range Evaluations for Connected Vehicles at Highway-Rail Grade Crossings

Safety improvement of traffic at railway crossings

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