A Multimodal Approach for Aggressive Driving Detection

Kumtepe, Omurcan
Yuncu, Enes
Akar, Gözde
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.


On Vehicle Aggressive Driving Behavior Detection Using Visual Information
Kumtepe, Omurcan; Akar, Gözde; Yuncu, Enes (2015-05-19)
Most of the traffic accidents are caused by human related factors. One of the most important human related factor in terms of traffic accident risk is aggressive driving behavior. Although driver aggressiveness is related with psychological reasons, it can be detected by observation of driving behavior using different sensing devices. This work presents a driver aggressiveness detection method exploiting the visual data obtained by on vehicle camera. The proposed method uses this visual data in order to ext...
Driver Aggressiveness Detection Using Visual Information from Forward Camera
Kumtepe, Omurcan; Akar, Gözde; Yuncu, Enes (2015-08-28)
Among the human related factors, aggressive driving behavior is one of the major causes of traffic accidents [17]. On the other hand, detection and characterization of driver aggressiveness is a challenging task since there exist different psychological causes behind it. However information about the driver behavior could be extracted from the data that is collected via different sensing devices. This paper presents a method to detect driver aggressiveness using only visual information provided by forward c...
An innovative model integrating spatial and statistical analyses for a comprehensive traffic accident study
Şener, İpek Neşe; İnal, Ayhan; Department of Civil Engineering (2004)
The negative social and economic results of traffic accidents are the most serious problems within the concept of traffic safety. Every year, unfortunately, a huge number of traffic accidents result in destructive losses. Especially, when the holiness of human life is concerned, traffic safety has an invaluable role for the traffic improvement strategies. In this manner, Turkey places one of the highest ranks regarding the growing rate and severity of traffic accidents that should be immediately taken under...
A contextual model of driving anger: A meta-analysis
DEMİR, BAŞAR; DEMİR, SILA; Özkan, Türker (2016-10-01)
Driver anger is an important individual difference variable that has been investigated extensively for understanding driving outcomes. The Driving Anger Expression Inventory (DAX - i.e., physical, verbal, use of vehicle as an aggression tool, and adaptive/constructive practices) and the Driver Behavior Questionnaire (DBQ - i.e., errors, lapses, and violations) are common outcome measures for investigating how people express their anger while driving. The current study aims to conduct a meta-analytic review ...
Symmetric Relationship Between Self and Others in Aggressive Driving Across Gender and Countries
Özkan, Türker; Parker, Dianne; Sumer, NEBİ; Summala, Heikki (2010-01-01)
Objective: It was hypothesized that the combination of self-reported aggressive behaviors committed by the driver himself/herself (oselfo scale) and perceiving himself/herself as an object of other drivers' aggressive acts (oothero scale) increases road accident involvement risk across gender and countries. The aim of this study was, therefore, to investigate this symmetric relationship between aggressive driving of self and other and its relationship on accident involvement among British, Dutch, Finnish, a...
Citation Formats
O. Kumtepe, E. Yuncu, and G. Akar, “A Multimodal Approach for Aggressive Driving Detection,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55672.