The effect of tire grip on learning driving skill and driving style: A driving simulator study

Groot, S. de; Ricote, F. Centeno; Winter, Joost de

doi:10.1016/j.trf.2012.02.005

Cited by 31 publications

(19 citation statements)

References 70 publications

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“…The vehicle-related factors can significantly influence the relevant driving behaviors and running out of curve crashes, such as vehicle type (Liu and Subramanian, 2009;Fitzsimmons et al, 2013) and vehicle occupancy (Liu and Ye, 2011). The typical driver-related factors associated with driving performances in curve segments include alcohol or drug use (Buddhavarapu et al, 2013), age (Tsimhoni and Green, 1999), driving style (De Groot et al, 2012;Evans, 2006) and driving experience (Cavallo et al, 1988).…”

Section: Factors Associated With Curve Safetymentioning

confidence: 99%

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Yan

Wong

2015

Accident Analysis & Prevention

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Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.

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Section: Factors Associated With Curve Safetymentioning

confidence: 99%

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Yan

Wong

2015

Accident Analysis & Prevention

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“…The results indicated that drivers would reduce driving speed and acceleration to achieve a lower driving risk. As to the road surface friction in the driving simulator, Groot, Ricote, et al [16] found that different levels of tire grip influenced lane keeping and driving speed.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Influence of Adverse Weather on Traffic Flow Characteristics Using a Driving Simulator and VISSIM

et al. 2019

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The occurrence of adverse weather exacerbates traffic flow conditions, often leading to severe traffic congestions. Many studies have been conducted based on field-collected data to obtain the effects of weather on traffic flow characteristics. However, there is a limitation for filed data-based studies, in that weather conditions and traffic conditions are both noncontrollable and nonrepeatable, making it difficult to comprehensively assess the influence of weather conditions, especially the rare extreme weather conditions, on traffic flow characteristics. This paper proposes to assess these effects with the combination of driving simulator and traffic simulation. A driving simulator can collect driving behavior by conducting weather-related driving simulation experiments, while a microscopic traffic simulation program can evaluate the changes in traffic flow characteristics by inputting driving behavior parameters coming from the driving simulator. The proposed method can overcome the limitation of the field data-based approach. In this paper, the structure of the assessment platform is introduced at first. Then a verification experiment is conducted to measure the influences of adverse weather conditions on traffic flow characteristics. The verification experiment results show that the influences of adverse weather on traffic flow characteristics have consistent tendencies with outcomes from previous research and demonstrate that the method is practicable for the analysis of the influence of weather on traffic flow characteristics. This paper provides a practical way to analyze the influence of weather on traffic flow from driving behavior’s point of view.

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“…2). It contained straight segments and mostly 90-degree sharp curves with a radius of about 20 m (for research using the same track, see [9][10][11][12]). The lane width was 5 m. The width of the simulated car was 1.76 m, and its length was 4.22 m. In each trial, participants drove 5 min.…”

Section: Trackmentioning

confidence: 99%

Blind Driving by Means of a Steering-Based Predictor Algorithm

Bazilinskyy

Beaumont

Geest

et al. 2017

Advances in Intelligent Systems and Computing

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The effect of tire grip on learning driving skill and driving style: A driving simulator study

Cited by 31 publications

References 70 publications

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Assessing the Influence of Adverse Weather on Traffic Flow Characteristics Using a Driving Simulator and VISSIM

Blind Driving by Means of a Steering-Based Predictor Algorithm

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