A study on driver’s workload of telematics using a driving simulator: A comparison among information modalities

Koo, Tae-Yun; Park, Kee-Jun; Kim, Bae-Young; Kim, Hyun-Jun; Suh, Myung‐Won

doi:10.1007/s12541-009-0048-6

Cited by 17 publications

(8 citation statements)

References 6 publications

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“…16,17 However, there are few Korean domestic studies that evaluate the driving workload and behaviors of older drivers related to various information systems, such as mobile phone and navigation systems. 18 In particular, no domestic studies can be found on the effects of audible interface systems such as a voice recognition system that enables the operation of in-vehicle systems with voice on cognitive workload and driving abilities. For the design of a safe Impact of Traffic Environment and Cognitive Workload on Older Drivers' Behavior in Simulated Driving vehicle interface, we need to understand the effects of declining cognitive abilities due to age on driving abilities.…”

Section: Introductionmentioning

confidence: 99%

Impact of traffic environment and cognitive workload on older drivers’ behavior in simulated driving

Son

Lee

Kim

2011

Int. J. Precis. Eng. Manuf.

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As the use of in-vehicle technologies became more popular, there is concern about a concomitant increase in driver distraction arising from their use. While the introduction of voice recognition systems is intended to reduce the distraction due to manual operation of these units, a significant proportion of the distraction associated with their use may arise not from the manual manipulation but rather the cognitive consequences. It is also known that the risk of inattentive driving varies with age. In this study, the impact of cognitive workload and traffic environments on older drivers' behavior was investigated in a driving simulator. To assess the impact of advancing age on driving performance degradation under a dual task condition, the performance of 63 drivers, divided into younger (20-29) and older (60-69) age groups, was evaluated. The authors also considered driving behavioral differences in the context of urban and highway driving, appropriately counterbalanced. At a specified location in the two scenarios, subjects were asked to complete a series of auditory tasks of increasing complexity. Comparisons of younger and older drivers' driving performance, including forward velocity, speed control, standard deviation of lane position and steering wheel reversal rate, were conducted. Results indicated that age and traffic environment impact both driving performance and compensatory behavior during dual task conditions.

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Section: Introductionmentioning

confidence: 99%

Impact of traffic environment and cognitive workload on older drivers’ behavior in simulated driving

Son

Lee

Kim

2011

Int. J. Precis. Eng. Manuf.

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“…Analysis of whether current automobile insurance policies are effective in reducing incidents of car accidents has shown that current insurance's schemes are somewhat lacking [6]. Current recommendations are to avoid operating navigation system and smartphones while driving [7][8] and the passing of laws to prohibit these actions is also under consideration.…”

Section: Introductionmentioning

confidence: 99%

Short paper: Study of driver workload-based smartphone control service

Kim

Hwang

Yoon

et al. 2013

2013 IEEE Vehicular Networking Conference

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When any distracted driving of the driver is concerned, use of smartphones and navigation systems while driving are major causes for traffic accidents. However, in a situation where navigation systems are commonly installed and smartphones are commonly used within vehicles, it is better to implement technologies that control the use of smartphones in high-risk situations and allow brief periods of use otherwise, rather than ban the use of smartphones altogether while driving. This study introduces the DWMS (Driver Workload Management System) and proposes service that controls the use of smartphones according to driver's workloads.The DWMS periodically monitors the driver's behaviors and smartphone usages in order to calculate driving workload. When the calculated workload exceeds the threshold value, the driver is deemed to be overburdened and all incoming calls and SMS (Short Message Service) is blocked. The service will then make a notification when this status is relieved. In addition, at the end of driving, the DWMS will provide a summary of the information on how the driver drives, workload, and behaviors taken as a text message to the driver's smartphone. The result of this study can increase both driving safety and convenience for drivers.

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“…An important issue to consider when implementing any simulator is validity. According to a technical report (Literature survey on driving simulator validation studies, 2006) of the Pennsylvania Transportation Institute examining the differences in driver behavior in simulated and real environments can be a useful method to validate driving simulators [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Study of a simulator database and an experiment for the evaluation of highway driving safety

2011

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Drivers acquire more than 90% of visual information through road signs. However, the road signage along highways can cause driver discomfort and traffic accidents. Conducting experiments along a real highway may cause traffic accidents; therefore, obtaining accurate results from such experiments is difficult. Consequently, this paper reports an experiment for evaluating highway driving safety to reduce the causes of accidents through highway design. It examines the development of a highway database to classify road types in exact accordance with real highways. The study involves an experiment using a driving simulator. The highway database was constructed in two aspects (original and alternative designs) compatible with the DirectX program of Multigen. Four types of physiological measurements (i.e., electrocardiogram, electromyography, electrooculography, and galvanic skin response) were taken from 33 subjects using Biopac equipment in the developed highway database. The skin temperature was measured by a thermal camera. The driver's state was measured through the Subjective Workload Analysis Technique, NASA-Task Load Index, and Modified Cooper-Harper, among various psychological methods. Statistical analysis was conducted to assure the reliability of the results using the Statistical Package for the Social Sciences 12.0 program.

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A study on driver’s workload of telematics using a driving simulator: A comparison among information modalities

Cited by 17 publications

References 6 publications

Impact of traffic environment and cognitive workload on older drivers’ behavior in simulated driving

Impact of traffic environment and cognitive workload on older drivers’ behavior in simulated driving

Short paper: Study of driver workload-based smartphone control service

Study of a simulator database and an experiment for the evaluation of highway driving safety

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