Detecting Driving Events using Smartphone

In a fast-paced environment of today society, safety issues related to driving is considered a second priority in contrast to travelling from one place to another in a shortest possible time. This often leads to possible accidents. In order to reduce road traffic accidents, one domain which requires to be focused on is driving behaviour. This paper proposes two algorithms which detect driving events using a smartphone since it is easily accessible and widely available in the market. More importantly, the proposed algorithms classify whether or not these events are aggressive based on raw data from various on board sensors on a smartphone. Initial experimental results reveal that the pattern matching algorithm outperforms the rule-based algorithm for driving events in both lateral and longitudinal movements.

[1]  Woon-Sung Lee,et al.  Development of a Driving Simulator for Virtual Experience and Training of Drunk Driving , 2011 .

[2]  Mohan M. Trivedi,et al.  Driving style recognition using a smartphone as a sensor platform , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[3]  Eamonn J. Keogh,et al.  Derivative Dynamic Time Warping , 2001, SDM.

[4]  Ramachandran Ramjee,et al.  Nericell: rich monitoring of road and traffic conditions using mobile smartphones , 2008, SenSys '08.

[5]  E. Geller,et al.  Self-Management to Increase Safe Driving Among Short-Haul Truck Drivers , 2005 .

[6]  P. L. Needham Collision prevention: the role of an accident data recorder (ADR) , 2001 .

[7]  Majid Sarrafzadeh,et al.  SmartLDWS: A robust and scalable lane departure warning system for the smartphones , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[8]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[9]  Donald J. Berndt,et al.  Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.

[10]  Ram Dantu,et al.  Safe Driving Using Mobile Phones , 2012, IEEE Transactions on Intelligent Transportation Systems.

[11]  Douglas C. Schmidt,et al.  Using Smartphones to Detect Car Accidents and Provide Situational Awareness to Emergency Responders , 2010, MOBILWARE.

[12]  Ching-Yao Chan,et al.  On the detection of vehicular crashes-system characteristics and architecture , 2002, IEEE Trans. Veh. Technol..