scholarly journals Factors of the “Aggressive Driving” Behaviour amongst Malaysian Drivers

2019 ◽  
Vol 8 (6) ◽  
pp. 3359-3366
Keyword(s):  
Motor Vehicle ◽  
Anger Expression ◽  
Driving Behavior ◽  
Motor Vehicle Crash ◽  
Aggressive Driving ◽  
The Road ◽  
Driving Anger ◽  
Multiple Factors ◽  
Driving Behaviour ◽  
On The Road

This study explores factors that lead towards aggressive driving behaviour among Malaysian drivers and to determine the highest factor that contributes to these aggressive driving styles in Malaysia. Driving aggressively increases the chances of drivers becoming involved in a motor vehicle crash, and aggressive driving behavior occurs happens due to multiple factors. The Driving Anger Expression Inventory (DAX) is used to calculate the factors corresponding to their anger while driving. There are four factors that has been identified to define how people expressed their anger while driving by using DAX, they are Verbally Aggressive Expression (α=0.7332), Physically Aggressive Expression (α=0.8548), Using the Vehicle for Aggressive Expression (α=0.7267) and Adaptive/Constructive Expression (α=0.8711). At the end of this research, we found out that the Adaptive/Constructive Expression is the highest factor and most commonly used amongst drivers to adapt to these aggressive situations on the road. Followed by the factor Verbally Aggressive Expression and Using the Vehicle for Aggressive Expression. Then, the least often used factor in Malaysia is Physically Aggressive Expression. Therefore, some mitigation plans should be considered towards reducing accidents in Malaysia which is on a yearly rising trend.

The Driving Anger Expression Inventory: a measure of how people express their anger on the road

2002 ◽  
Vol 40 (6) ◽  
pp. 717-737 ◽  
Author(s):  
Jerry L. Deffenbacher ◽  
Rebekah S. Lynch ◽  
Eugene R. Oetting ◽  
Randall C. Swaim
Keyword(s):  
Anger Expression ◽  
The Road ◽  
Driving Anger ◽  
On The Road

scholarly journals Cognitive maps influence over driving strategies in Russia: analyzing Driving Anger Expression Inventory (DAX) and Dula Dangerous Driving Index (DDDI) factors

2017 ◽  
Vol 8 (4) ◽  
pp. 107-122 ◽  
Author(s):  
A.I. Chetverikova ◽  
V.V. Ermolaev ◽  
O.N. Tkachenko
Keyword(s):  
Aggressive Behavior ◽  
Emotional State ◽  
Self Regulation ◽  
Anger Expression ◽  
Cognitive Maps ◽  
The Road ◽  
Driving Anger ◽  
Dangerous Driving ◽  
On The Road ◽  
First Time

This article summarizes our investigation of drivers cognitive maps and its influence over their behavior. 182 subjects participated in our research, i.e. 97 professional drivers, 85 car enthusiasts, 156 men and 26 women, 20—66 years old, mileage about 3—150 thousands kilometers per year. Questionnaire “Dula Dangerous Driving Index” was used on Russian subjects for the first time ever. Our results show that subjects’ need for get their rocks off when they are angered (or suspicious, or failed to trust the world around) and aggressive behavior during driving are correlated. Most drivers feel emotional tension during driving and use some self-regulation techniques to decrease the tension stabilize their emotional state. The following factors were found to correlate with one’s aggressive behavior on the road: feeling suspicious of world/self/others, low level of self-acceptance, external locus of control.

Gender Differences and Aggressive Driving Behavior: A Factor Analytic Study

2007 ◽  
Vol 51 (18) ◽  
pp. 1283-1286 ◽  
Author(s):  
Mustapha Mouloua ◽  
J. Christopher Brill ◽  
Edwin Shirkey
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Driving Behavior ◽  
Aggressive Driving ◽  
Highway Traffic ◽  
National Highway Traffic Safety ◽  
The Road ◽  
Factor Analytic ◽  
Components Analysis ◽  
On The Road

Aggressive driving behavior can be manifested in a wide variety of unsafe driving practices such as tailgating, honking, obscene and rude gestures, flashing high beams at slower traffic, and speeding. According the National Highway Traffic Safety Administration 2000 report, aggressive driving was a major cause of traffic accidents and injury. The present study was designed to systematically examine 5 previously developed scales related to aggressive driving behavior using a factor analytic approach. A sample of 253 students were administered these five questionnaires and the data were coded and statistically analyzed using a principal components analysis with Varimax rotation on the 81 items of the five combined scales. Nineteen components accounting for 67.4% of the variance were retained. Component scores were computed for the 19 components and then correlated with gender. Three significant ( p < .05) positive r's were found between gender; factors 11 (bright lights action), 12 (delaying action), and 19 (driving drunk). Males in the sample reported performing these actions more than females. There was one negative r between gender and factor 4 (considerate thoughts), suggesting that females reported more pleasant thoughts than males when angered or annoyed on the road.

Cell Phone Conversation while Driving

2015 ◽  
pp. 1307-1318 ◽  
Author(s):  
Abu Sadat Nurullah
Keyword(s):  
Cell Phone ◽  
Motor Vehicle ◽  
Cell Phones ◽  
Driving Behavior ◽  
Risky Driving ◽  
Physical Demands ◽  
Cell Phone Use ◽  
The Road ◽  
A Cell ◽  
On The Road

This article presents a review of studies on the conversational aspect of cell-phone use while operating a motor vehicle. Research has indicated that talking on a cell phone while driving poses a safety threat to people both in the vehicle and on the road. This is because cell phone conversations take considerable cognitive, visual, and physical demands on the person involved in this task. However, research has also shown that people engage in risky driving behavior, even after being cognizant of the dangers associated with it. Therefore, policies need to be implemented to thwart the use of cell phones while operating a motor vehicle, to educate people about the risks that this behavior poses, and in so doing, to make the road safer for drivers and pedestrians.

scholarly journals Identification of Contributing Factors for Driver’s Perceptual Bias of Aggressive Driving in China

2021 ◽  
Vol 13 (2) ◽  
pp. 766
Author(s):  
Yongfeng Ma ◽  
Xin Gu ◽  
Ya’nan Yu ◽  
Aemal J. Khattakc ◽  
Shuyan Chen ◽  
...  
Keyword(s):  
Traffic Accidents ◽  
Motor Vehicle ◽  
Anger Expression ◽  
Gaussian Mixture ◽  
Driving Behavior ◽  
Perceptual Bias ◽  
Impact Factors ◽  
Aggressive Driving ◽  
Contributing Factors ◽  
Objective Indicator

Aggressive driving is common across the world. While most aggressive driving is conscious, some aggressive driving behavior may be unconscious on part of motor vehicle drivers. Perceptual bias of aggressive driving behavior is one of the main causes of traffic accidents. This paper focuses on identifying impact factors related to aggressive driving perceptual bias. Questionnaire data from 690 drivers, collected from a drivers’ retraining course administered by the Traffic Management Bureau in Nanjing, China, were used to collect drivers’ socioeconomic characteristics, personality traits, and external environment data. Actual penalty points were considered as an objective indicator and Gaussian mixture model (GMM) was used to cluster an objective indicator into different levels. The driving anger expression (DAX) was used to measure drivers’ self-assessment of aggressive driving behavior and then to identify perceptual biases. Then a binary logistic model was estimated to explore the influence of different factors on drivers’ perceptual bias of aggressive driving behavior. Results showed that bus drivers were less likely to have perceptual bias of aggressive driving behavior. Truck drivers, drivers with an extraversion characteristic, and drivers who have dissatisfaction with road infrastructure and actual work were likely to have a perceptual bias. The findings are potentially beneficial for proposing targeted countermeasures to identify dangerous drivers and improve drivers’ safety awareness.

Advance Information on the Road: A Simulator Study of the Effect of Road Markings

1976 ◽  
Vol 18 (6) ◽  
pp. 521-532 ◽  
Author(s):  
Harald Witt ◽  
Carl G. Hoyos
Keyword(s):  
Driving Simulator ◽  
Driving Behavior ◽  
Speed Profile ◽  
The Road ◽  
Positive Effects ◽  
Road Signs ◽  
Advance Information ◽  
Simulator Study ◽  
On The Road ◽  
Accident Statistics

Accident statistics and studies of driving behavior have shown repeatedly that curved roads are hazardous. It was hypothesized that the safety of curves could be improved by indicating in advance the course of the road in a more effective way than do traditional road signs. A code of sequences of stripes put on right edge of the pavement was developed to indicate to the driver the radius of the curve ahead. The main characteristic of this code was the frequency of transitions from code elements to gaps between elements. The effect of these markings was investigated on a driving simulator. Twelve subjects drove on simulated roads of different curvature and with different placement of the code in the approach zone. Some positive effects of the advance information could be observed. The subjects drove more steadily, more precisely, and with a more suitable speed profile.

scholarly journals ANALISA CLUSTERING PADA DATA PELANGGARAN LALULINTAS DI PENGADILAN NEGERI DUMAI DENGAN MENGGUNAKAN METODE K-MEANS

2019 ◽  
Vol 4 (2) ◽  
pp. 1
Author(s):  
Elisawati Elisawati ◽  
Deasy Wahyuni ◽  
Adi Arianto
Keyword(s):  
Clustering Analysis ◽  
Motor Vehicle ◽  
District Court ◽  
Central Cluster ◽  
The Road ◽  
The Poor ◽  
Cluster Data ◽  
Traffic Violations ◽  
On The Road

The order of traffic on the road is very important for motorists on the highway, the lack of awareness of motor vehicle users and the poor drivers of traffic discipline make the level of traffic violations in driving on the highway always increase so that the number of ticket data received by the Dumai District Court. This research was conducted to analyze and classify data violations using the k-means method to facilitate knowing the types of violations that are often violated by vehicle users. The attributes to be analyzed are the types of violations and types of vehicles. The test was carried out using the Rapidminer 5 application where the data tested was data from the Dumai District Court on December 2017, as many as 616 violations. Central cluster data consists of 3 clusters, namely C1 = Many, C2 = moderate and C3 = few who commit traffic violations. So the results of the data obtained where C1 produces 1 data, C2 gets as much as 4 data and C3 as many as 7 data. Where the type of violation that is often violated is the type of violation that does not use a helmet and the type of vehicle is a motorcycle. From the results of this study can be used or can be followed up with the holding of socialization to reduce the number of traffic violations. Keywords: Clustering Analysis, K-Means, Traffic Violations, Rapidminer

scholarly journals Development of the "Technical Service" Program for Enterprises Working with the GLONASS System and Containing a Large Vehicle Fleet

2021 ◽  
pp. 93-98
Author(s):  
Р.Д. Адакин ◽  
И.М. Соцкая
Keyword(s):  
Fuel Consumption ◽  
Motor Vehicle ◽  
Technical Service ◽  
Short History ◽  
Service Program ◽  
The Road ◽  
Technical Personnel ◽  
History Of ◽  
Vehicle Fleet ◽  
On The Road

Представлена разработанная программа «Технический сервис», обменивающаяся информацией с базой данных систем ГЛОНАСС/GPS. Данная программа работает по сети и позволяет оповещать технический персонал, занимающийся обслуживанием, ремонтом и выпуском на линию или в рейс автотранспорта, напоминая ему о времени наступления прохождения технического обслуживания (ТО) для каждой единицы техники предприятия. При этом идёт информирование о количестве заменяемых жидкостей, марок и кодов фильтров, с краткой историей о неисправностях и ДТП техники, а также дублированием всей информации с системы ГЛОНАСС: расход топлива, пробег, скорость, марки и госномера техники. Разработанная программа имеет следующие возможности: хранит список техники с государственными номерами, постоянно обновляя данные о пробегах автотранспорта; хранит для каждой единицы техники необходимую информацию для проведения ТО автотранспорта, краткую историю о крупных неисправностях, проведённых капитальных ремонтах и ДТП автотранспорта. Данную информацию можно распечатать или сохранить на компьютер. Вовремя проведённое ТО является основой и залогом безотказной работы автотранспорта, что сказывается на успешном ведении бизнеса. The developed program "Technical Service" is presented, exchanging information with the database of GLONASS/GPS systems. This program works on the network and allows you to notify technical personnel engaged in service, repair and release on the road or on a motor vehicle trip, reminding them of the time of receipt of maintenance operation (MOT) for each unit of the enterprise equipment. At the same time, there is information about the number of liquids, grades and filter codes to be replaced with a short history of equipment malfunctions and accidents of vehicles, as well as duplication of all information from the GLONASS system: fuel consumption, mileage, speed, brands and license plates of vehicles. The developed program has the following capabilities: stores a list of vehicles with license plates, constantly updating data on vehicle mileage, and stores for each unit of equipment the necessary information for maintenance operation of vehicles, a short history of major malfunctions, major repairs and accidents of vehicles. This information can be printed or saved to a computer. Timely maintenance operation is the basis and key to the failure-free operation of vehicles, which affects the successful conduct of business.

Influence of Autonomous Vehicles on Car-Following Behavior of Human Drivers

2019 ◽  
Vol 2673 (12) ◽  
pp. 367-379 ◽  
Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson
Keyword(s):  
Autonomous Vehicles ◽  
Simulation Models ◽  
Driving Behavior ◽  
Data Driven ◽  
Microscopic Simulation ◽  
Car Following ◽  
The Road ◽  
Human Driver ◽  
Significant Difference ◽  
On The Road

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.

scholarly journals Driving Behaviour in Depression: Findings from a Driving Simulator Study

Safety ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 70
Author(s):  
Vagioula Tsoutsi ◽  
Dimitris Dikeos ◽  
Maria Basta ◽  
Maria Papadakaki
Keyword(s):  
Sleep Disturbance ◽  
Sleep Disturbances ◽  
Driving Simulator ◽  
Executive Dysfunction ◽  
Lateral Position ◽  
Driving Ability ◽  
Aggressive Driving ◽  
The Road ◽  
Driving Behaviour ◽  
Preceding Vehicle

Depression is characterized by mental, emotional and executive dysfunction. Among its symptoms, sleep disturbance and anxiety are very common. The effects of depression and its treatment may have an impact on driving behaviour. In order to evaluate driving performance in depression, 13 patients and 18 healthy controls completed questionnaires and scales and were tested in a driving simulator. Driving simulator data included lateral position (LP), speed and distance from the preceding vehicle. History of collisions was associated with depression, body mass index (BMI) and next-day consequences of sleep disturbance. Aggressive driving was associated with fatigue and sleep disturbances. Concerning driving simulator data, a reduced ability to maintain constant vehicle velocity was positively correlated to BMI and insomnia. An LP towards the middle of the road was associated with anxiety. On the other hand, an LP towards the shoulder was associated with depression and next-day consequences of sleep disturbance, while a positive correlation was found between distance from the preceding vehicle and use of drugs with potential hypnotic effects; both these findings show that patients suffering from depression seem to realize the effects of certain symptoms on their driving ability and thus drive in a more defensive way than controls.

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