Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

Li, Yi; Chen, Yu-Ren

doi:10.3390/ijerph14010031

Cited by 11 publications

(9 citation statements)

References 16 publications

(16 reference statements)

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“…(3) The exact distance at which a vehicle brakes to prevent a collision is dependent on visual reaction time, providing a de nite speed to drive at. (4,5) Hence, based on the principle of reaction time, we were able to suggest the effective attenuation of vehicular speed. We propose that more research needs to be carried out to explore the theme's expanse, aiding the administration in facilitating the road mishaps.…”

Section: Introductionmentioning

confidence: 94%

Spreading Awareness of Attenuating Vehicular Speed After Lifting of Covid-19 Lockdown Using Web-Based Estimation of Visual Reaction Time for Primary Prevention of Road Traffic Collision

Rajdeep

Patel

et al. 2022

Preprint

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Objectives- Attenuating the vehicular speed after lifting of lockdown during Covid-19, by employing visual reaction time (RT) as a tool to prime citizens for creating decorum of driving and checking the road traffic fatalities.Background- It is indispensable to curb the driving speed post lockdown to avoid accidents. Even though, the impact of inactivity on RT has been well established, an insight into the new method can deal with the gross issue of road traffic casualty worldwide. Method- Using a web-based platform (http://physicsiology.com), RT was derived by visual stimulation test. Of which, the slowest and the fastest RT were obtained. Using these and prefeed average vehicular speed before lockdown in the website the post lockdown vehicular speed were quantified for the participant. Apart from spreading awareness the website has also collected data for age and days of lockdown.Results- Compared to pre lockdown vehicular speed, reduced post lockdown speed was well calculated and suggested. Furthermore, from 643 participants, there was a correlation between RT, age, and days of lockdown.Conclusion- Containment of speed can be achieved through RT to prime people for prevention of road traffic collision after lifting of Covid-19 lockdown.

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Section: Introductionmentioning

confidence: 94%

Spreading Awareness of Attenuating Vehicular Speed After Lifting of Covid-19 Lockdown Using Web-Based Estimation of Visual Reaction Time for Primary Prevention of Road Traffic Collision

Rajdeep

Patel

et al. 2022

Preprint

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show abstract

“…The traffic volume was relatively low. Given that the response time of most drivers is about 2 s [17], visual road scenarios were matched with driving speed 2 s after.…”

Section: Naturalistic Driving Experimentsmentioning

confidence: 99%

“…By adjusting the target of the experiment, the influence and effectiveness of a specific road feature can be evaluated. (2) Establishing a behavior prediction model and assessing the importance of the predictors [17,18]. According to research findings worldwide, road attributes influencing driving speed can be enumerated: road alignment [19], roadside conditions [16], lane and shoulder width [20], speed limit [21], recovery-zone width, and junction density [22].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Effects of Visual Road Information on Drivers’ Speed Choices to Promote Self-Explaining Roads

Qin

Chen

Lin

2020

IJERPH

Self Cite

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Roads should deliver appropriate information to drivers and thus induce safer driving behavior. This concept is also known as “self-explaining roads” (SERs). Previous studies have demonstrated that understanding how road characteristics affect drivers’ speed choices is the key to SERs. Thus, in order to reduce traffic casualties via engineering methods, this study aimed to establish a speed decision model based on visual road information and to propose an innovative method of SER design. It was assumed that driving speed is determined by road geometry and modified by the environment. Lane fitting and image semantic segmentation techniques were used to extract road features. Field experiments were conducted in Tibet, China, and 1375 typical road scenarios were picked out. By controlling variables, the driving speed stimulated by each piece of information was evaluated. Prediction models for geometry-determined speed and environment-modified speed were built using the random forest algorithm and convolutional neural network. Results showed that the curvature of the right boundary in “near scene” and “middle scene”, and the density of roadside greenery and residences play an important role in regulating driving speed. The findings of this research could provide qualitative and quantitative suggestions for the optimization of road design that would guide drivers to choose more reasonable driving speeds.

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“…The total number of car accidents will be significantly reduced since 5G autonomous cars will always keep a safe distance from the neighbouring cars with a variable speed depending on road and traffic conditions. Furthermore, these cars will be able to respond quickly and effectively to abrupt traffic changes such as immediate breaking within ms, compared to the perception response time (PRT) of a human driver that ranges on average between 1.6 to 3 s [14].…”

Section: A Future Fully 5g Enabled Citymentioning

confidence: 99%

An eHealth-Care Driven Perspective on 5G Networks and Infrastructure

Konstantinou¹,

Rommel

Morales³

et al. 2020

Internet of Things, Infrastructures and Mobile Applications

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published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User

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Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

Cited by 11 publications

References 16 publications

Spreading Awareness of Attenuating Vehicular Speed After Lifting of Covid-19 Lockdown Using Web-Based Estimation of Visual Reaction Time for Primary Prevention of Road Traffic Collision

Spreading Awareness of Attenuating Vehicular Speed After Lifting of Covid-19 Lockdown Using Web-Based Estimation of Visual Reaction Time for Primary Prevention of Road Traffic Collision

Quantifying the Effects of Visual Road Information on Drivers’ Speed Choices to Promote Self-Explaining Roads

An eHealth-Care Driven Perspective on 5G Networks and Infrastructure

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