Abstract
Aggressive driving behavior is among the important causes of traffic accidents. Hence, detection of driver aggressiveness has an importance in terms of decreasing the number of traffic accidents. Collected driving data while the vehicle is in traffic can be used to make inferences about the aggressiveness of the driver. In this study, a multimodal method is proposed in order to detect driver aggressiveness. The proposed method is based on utilizing the visual data taken from the on vehicle camera and sensor data taken from the controller area network bus (CAN-bus) in order to decide whether the driving session involves aggressive driving behavior. Lane following pattern and vehicle following distance information is obtained from the data collected by camera while vehicle speed and engine speed information is obtained from CAN-bus. These information is fused to conceive feature vectors that represent the driving session and aggressiveness decision is made according to the classification of these feature vectors.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
