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Driver Alertness Mapping Disclosure Number: IPCOM000240598D
Publication Date: 2015-Feb-11
Document File: 2 page(s) / 59K

Publishing Venue

The Prior Art Database


The disclosure introduces the concept of on demand notification of potential danger introduced by a driver that is detected to drive either in unsafe manner (e.g., too fast, frequent lane movements, etc.) or in a status of fatigue (e.g., eye contact detection, alertness quizzes, monitoring acceleration patterns, etc.). Privacy of the driver can still be maintained by determining the notification radius to be 'large enough' to not pinpoint the specific driver and yet provide the surrounding drivers or walking citizens with the notification to apply extra caution due to this dynamic hazard in their area.

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Driver Alertness Mapping

In the world of connected cars, smartphone devices and Internet of Things, there appear many new ways to provide safer and smarter driving. A car with a smartphone connected to it, serves a sensor that allows both to provide a personal report and to obtain a global map of a certain feature. For instance, average velocity sensing in "Waze*" system provides global traffic maps as well as creates personalized traffic reports and route planning.

More examples of such a sensing :

Air pollution map. based on carbon output measurements :

US2011/0012720 A1, "integration of vehicle on-board diagnostics and smart phone sensors" Road condition map, based on accelerometer sensors:

"Nericell" is a system researched and developed by Microsoft that detects potholes, honking, bumps, and brakes using smartphones (Mohan et al. 2008). For detection it uses various sensors like the microphone, GPS, accelerometer and GSM radio. Neffcell has been tested for its practical application use on the roads of Bangalore, India.

"Pothole Patrol" is a system that monitors the road conditions using GPS and an accelerometer.

The system was deployed for testing in taxis which blanketed the city of Boston to identify uneven road surfaces. Their implementation was successful as it was able to identify potholes of various sizes throughout the city (Ericksson et al. 2008).

It has been proposed also to use smartphone or other car-mounted sensors to detect driving style of drivers (US 2012/0053805 A1, "Methods for detection of driving conditions and habits") or their distraction and or sleepiness ("Driver distraction and drowsiness warning and sleepiness reduction for accident", US 20140139655 A1)

Sharing the driver state information might assist to create dynamic driving safety status (DDSS) road maps thus increasing driver's alertness when approaching areas where potentially hazardous drivers are present. However people are aware of privacy problems that might appear if they allow to monitor their driving behavior and give away the sensitiv...