Sensing Driver Phone Use with Acoustic Ranging through Car Speakers

Yang, Jie; Sidhom, Simon; Chandrasekaran, G.; Vu, Tam; Liu, Hongbo; Cecan, Nicolae; Chen, Yingying; Gruteser, Marco; Martin, Richard P.

doi:10.1109/tmc.2012.92

Cited by 35 publications

(19 citation statements)

References 27 publications

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“…In this system [7], the fundamentally addressed problem is differentiating driver's and passenger's mobile phone. In this system, it leverages the stereo infrastructure, particularly speakers and Bluetooth.…”

Section: Litrature Surveymentioning

confidence: 99%

A Survey Paper on Non Intrusive Texting While Driving Detection Using Smart Phone

2018

IJMTER

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Abstract-Many interesting systems on mobile phone are introduced to prevent the dangerous activity of texting while driving (T&D). However these systems require user's manual input to block the texting activity or some extra devices are used to identify user's location and also some localization techniques are used. Here the idea is to propose a method which is able to detect T&D without any user intervention. To implement this idea various smart phone embedded sensors such as gyroscopes, accelerometers and GPS are used. They are used to collect the information such as touch strokes, holding orientation and vehicle speed. Using these patterns the whether the T&D is existing or not identified.

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Section: Litrature Surveymentioning

confidence: 99%

A Survey Paper on Non Intrusive Texting While Driving Detection Using Smart Phone

2018

IJMTER

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“…A detection system leveraging the car stereo infrastructure, in particular, the speakers and Bluetooth network is proposed and studied in [12]. This acoustic approach has the phone send a series of customized high frequency beeps via the car stereo.…”

Section: Related Workmentioning

confidence: 99%

Camera Based Localization of a Smartphone in a Vehicle

Paruchuri¹

2016

JCSAIT

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Open Access Research articleand Prevention (CDC), in year 2011 alone, 3,331 people were killed in accidents involving a distracted driver [18]. CDC also reports that around 31% of the drivers were reported to have used the text message or email features while driving. Combining these data, around 1,033 people were killed by texting and driving.Even without the statistical data, it is evident that cell phone usage while driving is a major distraction. The consequences of distracted driving are well recognized. In United States, as of March 2016, 14 states have laws that ban driving while talking on a handheld cell phone, and Forty-six States, ban text messaging for all drivers [2].Detecting vehicular movement is straightforward but ascertaining whether the user is indeed the driver is a complex problem. The fundamental problem of distinguishing between a driver and passenger using a mobile phone is the critical input to enable numerous safeties and interface enhancements. As in prior work, we seek to determine the in-vehicle location of the phone and use that as a heuristic to determine whether the phone is used by the driver or passenger. It uses a fundamentally different sensing approach to determine this location.Determining the movement of a vehicle is simple in that the speed can be calculated by using data from the GPS. Based on the speed determined, after a preselected speed, the cell phone can be disabled; or at least functions such as texting, games, can be disabled. However, determining if the user of the cell phone is indeed the driver is a challenging step. For an application that limits Smartphone functionality for a driver to execute successfully, the cell phone should be disabled only when it is used by a person driving a vehicle.Determining position of a Smartphone in a vehicle can enable and provide context for numerous interesting in-vehicle applications, including driver distraction prevention, driving behaviour estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, such as the stereo, cigarette lighter adapter or OBD (on-board diagnostic) adapter. In this paper, we propose an infrastructure-free, in-vehicle positioning system via smart phones. Our methodology uses only embedded camera in smart phones to determine the phones' seat-level locations in a vehicle. AbstractDistracted driving is any activity that could divert a person's attention away from the primary task of driving. All distractions endanger driver, passenger, and bystander safety. Cell phone usage while driving is a major distraction. Multiple solutions have been proposed on limiting smart phone functionality when being used by a driver. However, it remains challenge to detect if it is indeed the driver using the Smartphone.The objective of this paper is to address the fundamental problem of distinguishing the driver from passengers, non-intrusively, i.e., enabling driver phone detection without relying on any particular situations, events...

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“…Yang et.al. [36,37] introduce an acoustic relative-ranging system that classifies on which car seat a phone is being used leveraging the car's audio infrastructure. This approach relies on the vehicle's audio system.…”

Section: Related Workmentioning

confidence: 99%

“…The left-right classification approach proposed in this study can be integrated with the front-rear accelerometer classification described in our previous work [37]. The basic idea of this front-rear classification is that the acceleration forces on a vehicle when passing over speed bumps, potholes, or other uneven surfaces are also position dependent.…”

Section: Extended System With Front-rear Detectionmentioning

confidence: 99%

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Sensing vehicle dynamics for determining driver phone use

Wang

Yang

Liu

et al. 2013

Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services

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146

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This paper utilizes smartphone sensing of vehicle dynamics to determine driver phone use, which can facilitate many traffic safety applications. Our system uses embedded sensors in smartphones, i.e., accelerometers and gyroscopes, to capture differences in centripetal acceleration due to vehicle dynamics. These differences combined with angular speed can determine whether the phone is on the left or right side of the vehicle. Our low infrastructure approach is flexible with different turn sizes and driving speeds. Extensive experiments conducted with two vehicles in two different cities demonstrate that our system is robust to real driving environments. Despite noisy sensor readings from smartphones, our approach can achieve a classification accuracy of over 90% with a false positive rate of a few percent. We also find that by combining sensing results in a few turns, we can achieve better accuracy (e.g., 95%) with a lower false positive rate.

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Sensing Driver Phone Use with Acoustic Ranging through Car Speakers

Cited by 35 publications

References 27 publications

A Survey Paper on Non Intrusive Texting While Driving Detection Using Smart Phone

A Survey Paper on Non Intrusive Texting While Driving Detection Using Smart Phone

Camera Based Localization of a Smartphone in a Vehicle

Sensing vehicle dynamics for determining driver phone use

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