Title :
Severity assessment of anomalies using driving behaviour signals
Author :
S. Thajchayapong;C. Saiprasert;C. Charoensiriwath;C. Tanprasert
Author_Institution :
National Electronic and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Ministry of Science and Technology, Thailand
Abstract :
This paper reports an ongoing development of an algorithm for severity assessment of road anomalies using only driving behaviour signals. This algorithm is to be used in an active safety system where severity assessment operates in a distributed manner, i.e. at the leading vehicle that encounters an anomaly. Based on real-world 1,300 braking signals collected from 52,000 participants, it is shown that braking signals themselves can be clustered according to their duration and magnitude. These preliminary results demonstrate that it is feasible to cluster severity using driving behaviour signals.
Keywords :
"Vehicles","Roads","Clustering algorithms","Safety","Algorithm design and analysis","Acceleration","Smart phones"
Conference_Titel :
Connected Vehicles and Expo (ICCVE), 2015 International Conference on
Electronic_ISBN :
2378-1297
DOI :
10.1109/ICCVE.2015.83