Are You an Aggressive Driver?

2013 ◽  
Keyword(s):  
Author(s):  
Juan Carmona ◽  
Fernando García ◽  
Miguel Ángel de Miguel ◽  
Arturo de la Escalera ◽  
José María Armingol

2019 ◽  
Vol 25 (3) ◽  
pp. 276-283
Author(s):  
Abdulbari Bener ◽  
Khair Jadaan ◽  
David Crundall ◽  
Alessandro Calvi

Author(s):  
Jorge A. Laval ◽  
Ludovic Leclercq

This paper introduces a parsimonious theory for congested freeway traffic that describes the spontaneous appearance of oscillations and their ensuing transformation into stop-and-go waves. Based upon the analysis of detailed vehicle-trajectory data, we conclude that timid and aggressive driver behaviours are the cause for this transformation. We find that stop-and-go waves arise independently of the details of these behaviours. Analytical and simulation results are presented.


2015 ◽  
Vol 27 (02) ◽  
pp. 1650018 ◽  
Author(s):  
Han-Tao Zhao ◽  
Cen Nie ◽  
Jing-Ru Li ◽  
Yu-Ao Wei

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20[Formula: see text]pcu/km the more aggressive drivers the greater the flow, when the density below 40[Formula: see text]pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10[Formula: see text]pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density.


Author(s):  
Daniel P. Piatkowski ◽  
Wesley Marshall ◽  
Aaron S. Johnson

This research investigated aggressive driver–bicyclist interactions. Individuals who identified themselves as both a driver and a bicyclist were asked about their behavior when they encountered a bicyclist on the road while they were driving a car. Open-ended survey responses were analyzed from individuals who reported a propensity for driving too closely to a bicyclist who they felt was not staying to the side of the road. The data were drawn from a snowball-sampled, online survey specifically targeted to elicit responses about rare (i.e., deviant or illegal) behaviors. Little research exists on why individuals would choose to intimidate a bicyclist while they were driving. Applicable theories from sociology and behavioral economics (i.e., theories of crime as social control and as altruistic punishment) were drawn on in this study to help understand why individuals might do so. This paper argues that aggressive driving behavior directed at bicyclists in the sample population could be characterized with two general themes: “teaching them a lesson” and “they had it coming.” In both cases, individuals deflected the blame for their aggressive behavior away from themselves. Instead, they cast themselves as serving a social good by teaching bicyclists how they should behave or by punishing bicyclists for behaving in ways with which the drivers disagreed. The study reported here was an initial step in an effort to identify testable hypotheses through qualitative methods to explain such behaviors and eventually to mitigate them. The intent is to inform actionable directions to address dangerous on-street interactions that act as barriers to a safe transportation system that accommodates all users.


2021 ◽  
Vol 3 (5) ◽  
pp. 81-95
Author(s):  
Claudia VLAICU ◽  
◽  
Felicia HAIDU

Various studies have documented that aggressive driving is indeed a real problem. In each country there are various aspects of dangerous driving of empirical and practical concern and there are also individual differences to be explored. The present study aims at profiling the Romanian aggressive driver and questioning whether there are differences according to demographic variables such as: gender, age, area of living, marital status, religion, socio-economic status and level of instruction. An educational purpose may be nevertheless included. If psychologist may be provided with the profile of psychological driver and the predisposition of some to risky drivind according to age, marital status, religion, area of living and other demographic variables, they may shorten the time spent for evaluation and recommend counseling sessions for anger management for those identified with risky driving behavior. Nevetheless, other sound measures of dangerous driving are needed to understand differences and commonalties between aggression, negative cognitive/emotional driving, and risky driving. The study presents the DDDI results that might help psychologist in evaluating some variables that are part of the profile of the aggressive driver in Romania; we used it as a psychometric screening tool to select individuals who are prone to dangerous driving styles and who could benefit from sketching a cognitive-behaviour therapy (CBT)-type therapeutic intervention, at least in Romania. The educational implication of this study are that such types of interventions as cognitive-behavioral interventions (e.g., relaxation, cognitive restructuring, and behavioral skill building) may be suggested after testing the drivers in order to reduce and maintain reductions of driving anger, aggressive anger expression, aggression, risky behavior, and general anger


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