%0 Conference Paper %1 6151382 %A Bhoraskar, R. %A Vankadhara, N. %A Raman, B. %A Kulkarni, P. %B Communication Systems and Networks (COMSNETS), 2012 Fourth International Conference on %D 2012 %K activityrecognition sensors trafficPrediction %P 1-6 %R 10.1109/COMSNETS.2012.6151382 %T Wolverine: Traffic and road condition estimation using smartphone sensors %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6151382 %X Monitoring road and traffic conditions in a city is a problem widely studied. Several methods have been proposed towards addressing this problem. Several proposed techniques require dedicated hardware such as GPS devices and accelerometers in vehicles 7158 or cameras on roadside and near traffic signals 13. All such methods are expensive in terms of monetary cost and human effort required. We propose Wolverine - a non-intrusive method that uses sensors present on smartphones. We extend a prior study 12 to improve the algorithm based on using accelerometer, GPS and magnetometer sensor readings for traffic and road conditions detection. We are specifically interested in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road. We evaluate the effectiveness of the proposed method based on experiments conducted on the roads in Mumbai, with promising results.

@inproceedings{6151382, abstract = {Monitoring road and traffic conditions in a city is a problem widely studied. Several methods have been proposed towards addressing this problem. Several proposed techniques require dedicated hardware such as GPS devices and accelerometers in vehicles [7][15][8] or cameras on roadside and near traffic signals [13]. All such methods are expensive in terms of monetary cost and human effort required. We propose Wolverine - a non-intrusive method that uses sensors present on smartphones. We extend a prior study [12] to improve the algorithm based on using accelerometer, GPS and magnetometer sensor readings for traffic and road conditions detection. We are specifically interested in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road. We evaluate the effectiveness of the proposed method based on experiments conducted on the roads in Mumbai, with promising results.}, added-at = {2015-02-04T01:00:12.000+0100}, author = {Bhoraskar, R. and Vankadhara, N. and Raman, B. and Kulkarni, P.}, biburl = {https://www.bibsonomy.org/bibtex/22c64441150f76f2166777007d9a2b214/lutful_kabir}, booktitle = {Communication Systems and Networks (COMSNETS), 2012 Fourth International Conference on}, description = {IEEE Xplore Abstract - Wolverine: Traffic and road condition estimation using smartphone sensors}, doi = {10.1109/COMSNETS.2012.6151382}, interhash = {fffb5471ad24875f1fb301179f19a0d2}, intrahash = {2c64441150f76f2166777007d9a2b214}, keywords = {activityrecognition sensors trafficPrediction}, month = jan, pages = {1-6}, timestamp = {2015-02-04T01:00:12.000+0100}, title = {Wolverine: Traffic and road condition estimation using smartphone sensors}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6151382}, year = 2012 }