Driver Performance at High Speeds Using a Simulator

Fitzpatrick, Kay; Chrysler, Susan T; Park, Eun Sug; Iragavarapu, Vichika; Nelson, Alicia

doi:10.3141/2321-12

Cited by 12 publications

(8 citation statements)

References 1 publication

(1 reference statement)

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“…In driving simulators, measuring the driving workload of a driver can be conducted relatively easily by means of physiological measures and performance. Fitzpatrick [ 18 ] studied the notice and reaction time of drivers to a lead decelerating vehicle using a driving simulator. The objective of the study was to measure how long drivers took to notice and react to a lead decelerating vehicle.…”

Section: Introductionmentioning

confidence: 99%

Driver’s Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China

Lyu

Xie

et al. 2017

IJERPH

100

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Complex traffic situations and high driving workload are the leading contributing factors to traffic crashes. There is a strong correlation between driving performance and driving workload, such as visual workload from traffic signs on highway off-ramps. This study aimed to evaluate traffic safety by analyzing drivers’ behavior and performance under the cognitive workload in complex environment areas. First, the driving workload of drivers was tested based on traffic signs with different quantities of information. Forty-four drivers were recruited to conduct a traffic sign cognition experiment under static controlled environment conditions. Different complex traffic signs were used for applying the cognitive workload. The static experiment results reveal that workload is highly related to the amount of information on traffic signs and reaction time increases with the information grade, while driving experience and gender effect are not significant. This shows that the cognitive workload of subsequent driving experiments can be controlled by the amount of information on traffic signs; Second, driving characteristics and driving performance were analyzed under different secondary task driving workload levels using a driving simulator. Drivers were required to drive at the required speed on a designed highway off-ramp scene. The cognitive workload was controlled by reading traffic signs with different information, which were divided into four levels. Drivers had to make choices by pushing buttons after reading traffic signs. Meanwhile, the driving performance information was recorded. Questionnaires on objective workload were collected right after each driving task. The results show that speed maintenance and lane deviations are significantly different under different levels of cognitive workload, and the effects of driving experience and gender groups are significant. The research results can be used to analyze traffic safety in highway environments, while considering more drivers’ cognitive and driving performance.

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Section: Introductionmentioning

confidence: 99%

Driver’s Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China

Lyu

Xie

et al. 2017

IJERPH

100

View full text Add to dashboard Cite

show abstract

“…Other studies used drivers' notice and react time measures to study the relationships between driving performance and traffic flow. 20 Driving workload was found to likely increase due to heavy traffic compared to free driving. 21 While driving, drivers must properly perceive road signs, maintain alertness to make decisions, and perform driving actions at the right time.…”

Section: Introductionmentioning

confidence: 97%

Studying the effects of freeway alignment, traffic flow, and sign information on subjective driving workload and performance

Xie

Lyu

et al. 2019

Advances in Mechanical Engineering

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Road alignment, traffic flow, and sign information interact and create complex traffic situations. To evaluate the effects of freeway horizontal radius, slope grade, traffic flow, and sign information on subjective driving workload and performance, a simulated driving experiment based on an orthogonal test design was conducted. The National Aeronautics and Space Administration Task Load Index was used to measure self-reported workload. Data regarding speed and lane deviation were collected through the driving simulator. A multivariate analysis of variance results indicated that the radius of the horizontal curve significantly influenced workload score, average speed, and lane deviation. It was observed that in a high workload environment, participants exerted more effort on the driving task; however, driving performance still decreased. Although there was no significant correlation between slope grade and subjective driving workload or performance, the primary effect of slope grade on workload and average speed was statistically significant. The amount of sign information significantly influenced the driver's perceived workload; however, it did not significantly impact driving performance. In addition, the low correlation coefficient between subjective workload and performance was obtained. These research findings can provide insights for the design of freeway alignments and traffic signs to maintain optimal workload and minimize safety risks.

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“…The purpose of this study is to utilize a driving simulator to investigate the pattern of drivers' behavior during rainfall events using different geometries. Driving simulators have played an important role in traffic studies (Fitzpatrick et al, 2010;Fitzpatrick, Chrysler, Park, Iragavarapu, & Nelson, 2012).Simulators have also been used as a tool for studies and analyses related to driving behaviors. This research utilizes participants (drivers) of varying sex and age groups, driving the simulator in a virtual world ranging from suburban to highway, with and without rainfalls and recording their driving speed.…”

mentioning

confidence: 99%

Evaluation of Driver Behavior to Hydroplaning in the State of Florida Using Driving Simulation

Villiers¹,

Guo²

2019

CSID-JID

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This project used a driving simulator to investigate patterns of drivers' behavior during rainfall events using different geometries. The researchers conducted a literature review of previous transportation studies using driving simulators and selected and analyzed extensive field data on major highway sections throughout Florida. The driving simulator at the University of Central Florida simulated the parameters such as speed and rainfall intensity observed in the field. Based on an analysis, the researcher found that drivers are not affected by light rainfall events. However, heavy rainfall has a significant impact on their speed; on average drivers reduced their speed by 6 to 12 mph. Also, there is no interaction between rainfall intensity and either gender or age group. The female participants appeared to drive faster as compared to their male counterparts and the age group ranging from 16 to 21 years of age appeared to be the more aggressive drivers. Eighty percent (80%) of the participants reported on the survey that they have experienced some level of hydroplaning while driving on the road. The simulator appears to provide identical results to the field data analysis, lending credence to the validity of using a driving simulator to investigate the pattern of drivers' behavior during rainfall events. The researchers recommend further validation and refinement of this study. Continuation of this project may also help Florida Department of Transportation and other agencies with future decision making, such as Variable Message Signs, determining appropriate corrective measures on existing roadway sections, and/or designing future roadway sections to reduce hydroplaning.

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Driver Performance at High Speeds Using a Simulator

Cited by 12 publications

References 1 publication

Driver’s Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China

Driver’s Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China

Studying the effects of freeway alignment, traffic flow, and sign information on subjective driving workload and performance

Evaluation of Driver Behavior to Hydroplaning in the State of Florida Using Driving Simulation

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