Effects of smartphone based advanced driver assistance system on distracted driving behavior: A simulator study

Dumitru, Adrian Iulian; Gîrbacia, Teodora; Boboc, Răzvan Gabriel; Postelnicu, Cristian-Cezar; Mogan, Gheorghe-Leonte

doi:10.1016/j.chb.2018.01.011

Cited by 46 publications

(17 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The auditory stimulus was composed of two sound bursts, each burst containing a continuous stimulus of 0.6 s at a frequency of 2500 Hz, and which last approximately 1.31 s [ 69 ]. Bursts were separated by 110 ms and had an amplitude of 70 dB without an envelope [ 32 ]. The visual warnings for collisions consisted of a flashing red triangle, while for lane departure a distinct representative visual icon was used.…”

Section: Methodsmentioning

confidence: 99%

“…In general, visual warnings are used for informative purposes, while auditory warnings indicate dangerous situations (object collision or lane departure). Smartphone-based ADASs usually use image processing to detect possible front collisions or driver inattention [ 32 ]. A mobile driver assistance application that has the capability to simultaneously process video stream from the front and back camera of a smartphone can give less false alerts, thus reducing the chances of becoming annoying.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Voinea

Postelnicu

Duguleană

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

Technological advances are changing every aspect of our lives, from the way we work, to how we learn and communicate. Advanced driver assistance systems (ADAS) have seen an increased interest due to the potential of ensuring a safer environment for all road users. This study investigates the use of a smartphone-based ADAS in terms of driving performance and driver acceptance, with the aim of improving road safety. The mobile application uses both cameras of a smartphone to monitor the traffic scene and the driver’s head orientation, and offers an intuitive user interface that can display information in a standard mode or in augmented reality (AR). A real traffic experiment consisting of two driving conditions (a baseline scenario and an ADAS scenario), was conducted in Brasov, Romania. Objective and subjective data were recorded from twenty-four participants with a valid driver’s license. Results showed that the use of the ADAS influences the driving performance, as most of them adopted an increased time headway and lower mean speeds. The technology acceptance model (TAM) questionnaire was used to assess the users’ acceptance of the proposed driver assistance system. The results showed significant interrelations between acceptance factors, while the hierarchical regression analysis indicates that the variance of behavioral intention (BI) can be predicted by attitude toward behavior.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Voinea

Postelnicu

Duguleană

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…Authors of the paper [9] researched the impact of the smartphone-based driver assistance system on driving behavior while the driver is impaired by the use of mobile social networking applications. The developed approach uses the driving simulator that replicates the car structure and its parts and includes the following modules.…”

Section: A Smartphone-based Driver Monitoringmentioning

confidence: 99%

Multimodal Corpus Design for Audio-Visual Speech Recognition in Vehicle Cabin

et al. 2021

View full text Add to dashboard Cite

This paper introduces a new methodology aimed at comfort for the driver in-the-wild multimodal corpus creation for audiovisual speech recognition in driver monitoring systems. The presented methodology is universal and can be used for corpus recording for different languages. We present an analysis of speech recognition systems and voice interfaces for driver monitoring systems based on the analysis of both audio and video data. Multimodal speech recognition allows using audio data when video data are useless (e.g. at nighttime), as well as applying video data in acoustically noisy conditions (e.g., at highways). Our methodology identifies the main steps and requirements for multimodal corpus designing, including the development of a new framework for audiovisual corpus creation. We identify the main research questions related to the speech corpus creation task and discuss them in detail in this paper. We also consider some main cases of usage that require speech recognition in a vehicle cabin for interaction with a driver monitoring system. We also consider other important use cases when the system detects dangerous states of driver's drowsiness and starts a question-answer game to prevent dangerous situations. At the end based on the proposed methodology, we developed a mobile application that allows us to record a corpus for the Russian language. We created RUSAVIC corpus using the developed mobile application that at the moment a unique audiovisual corpus for the Russian language that is recorded in-the-wild condition. INDEX TERMS Driver monitoring, automatic speech recognition, multimodal corpus, human-computer interaction.

show abstract

“…Recent studies have investigated the impact of these ‘soft blocker’ systems demonstrating that they can effectively and significantly reduce the number of mobile phone checks per minute (up to – 20%) with a consequent increase in road safety [8–10]. The study by [11] showed that advanced driver assistance systems integrated in smartphones can help to reduce driving infractions by 43.43% compared to the situation in which the driver does not use it.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of the effects of mobile phone use on driving performance using ANOVA and ANCOVA

Fancello

Adamu

Serra

et al. 2020

IET Intelligent Transport Systems

View full text Add to dashboard Cite

Effects of smartphone based advanced driver assistance system on distracted driving behavior: A simulator study

Cited by 46 publications

References 23 publications

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Multimodal Corpus Design for Audio-Visual Speech Recognition in Vehicle Cabin

Comparative analysis of the effects of mobile phone use on driving performance using ANOVA and ANCOVA

Contact Info

Product

Resources

About