Distinguishing driver and passenger phone use is a building block for a variety of applications but it’s greatest promise arguably lies in helping reduce driver distraction. Cell phone distractions have been a factor in high-profile accidents and are associated with a large number of automobile accidents. For example a National Highway Traffic Safety Administration study identified cell phone distraction as a factor in crashes that led to 995 fatalities and 24,000 injuries in 2009. This has led to increasing public attention and the banning of handheld phone use in several US states as well as many countries around the world. In addition, the cell phone distractions can also cause pedestrians or cyclists injured in traffic accidents: In the last decade, more than 688,000 pedestrians and motorist are injured in traffic accidents and 47,700 of them fatally. This number has been rising at an annual rate of 4.9% from 2009-2012.
Unfortunately, an increasing amount of research suggests that the safety benefits of hands-free phone operation are marginal. Some approaches run the gamut from improved driving mode user interfaces, which allow quicker access to navigation and other functions commonly used while driving, to apps that actively prevent phone calls. Some more subtle approaches try to rout the incoming calls to voicemail or delaying incoming text notifications. However, none of these solutions can automatically distinguish a driver’s cell phone from a passenger’s.
We introduce our app that classifies on which car seat a phone is being used by utilizing the vehicle's sound system via Bluetooth. The app can automatically silence the ringtone of incoming message and calls to reduce the distraction to the driver when the phone is detected to be used on the driver's seat. In addition, the app is aware of the collision-prone crossroad in the New York City and can automatic warn drivers to watch out for pedestrians and cyclists when the phone is found to approach a collision-prone crossroad. This would further help to reduce the odds of collisions with pedestrians and cyclists in busy city environments.