Recognizing Driver Talking Direction in Running Vehicles with a Smartphone

Dai, Haipeng; Liu, Alex X.; Li, Zeshui; Wang, Wei; Zhang, Fengmin; Dong, Chao

doi:10.1109/mass.2019.00011

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…Dai et al [79] identify the driver's talking direction, namely, front, right (when the driver is sitting on the left side), and back, from running vehicles. They use two microphones on a smartphone and a K-means clustering algorithm to first identify whether the driver is talking or not and then classify the sound into one of the three driver talking directions.…”

Section: Author-centric Analysis: Summary Of Individual Resultsmentioning

confidence: 99%

“…The research objectives of the reviewed papers range from the detection of when a person enters the vehicle [65], the classification of users into drivers and passengers [63,66,77,114], the identification of the driver's interaction with the smartphone [64,73,84,106], the classification of driving events and driving styles [68,75,83,90], the detection of distracted drivers [48][49][50][51][52]69,113], the detection of inattentive drivers [49,53,54,111], the detection of gaze direction for distracted driving [78], to the identification of the driver's speech direction [79].…”

Section: Aggregated Results: Summary Of Tangible Resultsmentioning

confidence: 99%

“…The analysis methods used include machine learning models [66,68,[77][78][79]84,86,90,103,105,107,[109][110][111][112],…”

Section: Aggregated Results: Summary Of Tangible Resultsmentioning

confidence: 99%

“…Computer-vision-related research includes driver gaze detection or driver eye detection [49], driver eye closure detection, driver yawn detection [49], and driver pose detection [95], as well as other driver activity detection, such as attending their hair and makeup, reaching behind, operating the radio, eating, and drinking [50]. Audio-related research includes identifying driver talking activity and phone use [64,79].…”

mentioning

confidence: 99%

See 3 more Smart Citations

Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review

Papatheocharous,

Kaiser,

Moser

et al. 2023

Sensors

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Driver behaviour monitoring is a broad area of research, with a variety of methods and approaches. Distraction from the use of electronic devices, such as smartphones for texting or talking on the phone, is one of the leading causes of vehicle accidents. With the increasing number of sensors available in vehicles, there is an abundance of data available to monitor driver behaviour, but it has only been available to vehicle manufacturers and, to a limited extent, through proprietary solutions. Recently, research and practice have shifted the paradigm to the use of smartphones for driver monitoring and have fuelled efforts to support driving safety. This systematic review paper extends a preliminary, previously carried out author-centric literature review on smartphone-based driver monitoring approaches using snowballing search methods to illustrate the opportunities in using smartphones for driver distraction detection. Specifically, the paper reviews smartphone-based approaches to distracted driving behaviour detection, the smartphone sensors and detection methods applied, and the results obtained.

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Section: Author-centric Analysis: Summary Of Individual Resultsmentioning

confidence: 99%