scholarly journals Driver behaviour and traffic accident involvement among professional heavy semi-trailer truck drivers in China

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260217
Author(s):  
Wanli Han ◽  
Jianyou Zhao ◽  
Ying Chang
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Principal Component ◽  
Binary Logistic Regression ◽  
Driving Behavior ◽  
Truck Drivers ◽  
Driver Behaviour ◽  
Professional Drivers ◽  
Accident Prediction ◽  
Driving Time

The purpose of this study was to develop a driving behavior scale for professional drivers of heavy semi-trailer trucks in China, and study the causes of such driving behavior and its impact on traffic safety operation. Data was processed by IBM SPSS 25. In addition to principal component analysis, Promax rotation, Bartlett’s test, Cronbach’s alpha, correlation analysis and binary logistic regression were examined. A DBQ with 4 dimensions and 20 items, and a PDBQ with 1 dimension and 6 items were developed for professional drivers of heavy semi-trailer trucks in China. The KMO coefficients of PDBQ and DBQ were 0.822 and 0.852, respectively, and the significant level of Bartlett’s popularity test was p < 0.0001. The accident prediction model showed that the variables related to traffic accidents were negligence/lapses and driving time of heavy semi-trailer truck drivers. 1–5 a.m. was found to be the most dangerous period for drivers of medium and heavy semi-trailer trucks, during which accidents were most likely to happen. As negligence/lapses increased by one unit, the probability of traffic accidents increased by 2.293 times.

scholarly journals The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi

2020 ◽  
Vol 14 (1) ◽  
pp. 237-250
Author(s):  
Dinh Hiep ◽  
Vu V. Huy ◽  
Teppei Kato ◽  
Aya Kojima ◽  
Hisashi Kubota
Keyword(s):  
Primary School ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Primary Schools ◽  
Traffic Accidents ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Almost All

Introduction: One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents. Methods: The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software. Results and Discussion: The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk). Conclusion: Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.

scholarly journals Research on Risky Driving Behavior of Novice Drivers

2019 ◽  
Vol 11 (20) ◽  
pp. 5556
Author(s):  
Longhai Yang ◽  
Xiqiao Zhang ◽  
Xiaoyan Zhu ◽  
Yule Luo ◽  
Yi Luo
Keyword(s):  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Risky Behaviors ◽  
Driving Behavior ◽  
Risky Driving ◽  
Novice Drivers ◽  
Driving Skills ◽  
Planned Behavior Theory

Novice drivers have become the main group responsible for traffic accidents because of their lack of experience and relatively weak driving skills. Therefore, it is of great value and significance to study the related problems of the risky driving behavior of novice drivers. In this paper, we analyzed and quantified key factors leading to risky driving behavior of novice drivers on the basis of the planned behavior theory and the protection motivation theory. We integrated the theory of planned behavior (TPB) and the theory of planned behavior (PMT) to extensively discuss the formation mechanism of the dangerous driving behavior of novice drivers. The theoretical analysis showed that novice drivers engage in three main risky behaviors: easily changing their attitudes, overestimating their driving skills, and underestimating illegal driving. On the basis of the aforementioned results, we then proposed some specific suggestions such as traffic safety education and training, social supervision, and law construction for novice drivers to reduce their risky behavior.

scholarly journals Analisis Perilaku Pengemudi Truk Serta Kontribusinya Pada Kecelakaan

2021 ◽  
Vol 23 (1) ◽  
pp. 79-87
Author(s):  
Budi Dwi Hartanto
Keyword(s):  
Path Analysis ◽  
Direct Effect ◽  
Human Error ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Driving Behavior ◽  
Truck Drivers ◽  
Accident Risk ◽  
Aggressive Driving ◽  
The Relationship

ABSTRAKIn Indonesia, the death rate due to road traffic accidents is still quite high, with some of these accidents involving trucks. Several studies stated that the main cause of traffic accidents is human error. Therefore, research related to the behavior of truck drivers and their contribution to accidents is necessary.There are four variables used in this study, namely green driver (X1), multitasking driving (X2), aggressive driving (Y), and accidents (Z). Path analysis is used to describe the relationship and influence between variables.The results of the analysis show that the green driver variable and the multitasking driving variable simultaneously have a direct effect on aggressive driving behavior, but the two variables have no direct effect on the level of accident risk. Green drivers and multitasking driving have an indirect effect on the level of accident risk through the level of aggressive driving behavior which functions as an intervening variable.ABSTRAKDi Indonesia tingkat kematian yang diakibatkan  kecelakaan lalu lintas jalan masih cukup tinggi, dimana sebagian dari kecelakaan tersebut melibatkan kendaraan angkutan barang (truk). Beberapa penelitian menyebutkan bahwa penyebab utama terjadinya kecelakaan lalu lintas adalah human error. Oleh sebab maka penelitian terkait dengan perilaku pengemudi truk serta kontribusinya pada kecelakaaan perlu untuk dilakukan.Terdapat empat variabel yang digunakan dalam penelitian ini yaitu variabel usia muda serta minim pengalaman (X1), mengemudi dalam kondisi multitasking (X2), mengemudi secara agresif (Y), dan potensi terjadinya kecelakaan (Z). Untuk menggambarkan hubungan dan pengaruh antar variabel digunakan analisis jalur (path analysis).Dari hasil analisis diketahui bahwa variabel usia muda serta minim pengalaman dan variabel mengemudi dalam kondisi multitasking secara simultan berpengaruh langsung terhadap perilaku mengemudi agresif, namun kedua variabel tidak berpengaruh langsung terhadap tingkat resiko kecelakaan. Usia muda serta minim pengalaman dan mengemudi dalam kondisi multitasking berpengaruh tidak langsung terhadap tingkat resiko kecelakaan melalui tingkat perilaku mengemudi agresif yang berfungsi sebagai variabel intervening

scholarly journals A Model for Traffic Accidents Prediction Based on Driver Personality Traits Assessment

2017 ◽  
Vol 29 (6) ◽  
pp. 631-642 ◽  
Author(s):  
Marjana Čubranić-Dobrodolac ◽  
Krsto Lipovac ◽  
Svetlana Čičević ◽  
Boris Antić
Keyword(s):  
Personality Traits ◽  
Structural Equation ◽  
Traffic Accidents ◽  
Predictive Power ◽  
Correlation Coefficients ◽  
Binary Logistic Regression ◽  
Driving Ability ◽  
Hierarchical Regression ◽  
Driver Behaviour ◽  
Additional Information

The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11) was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ) for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

scholarly journals MODELING THE PROBABILITY OF SPEEDING BEHAVIOUR AND ACCIDENT INVOLVEMENT USING BINARY LOGISTIC REGRESSION IN EAST JAVA PROVINCE

2020 ◽  
Vol 2 (3) ◽  
pp. 149
Author(s):  
Willy Kriswardhana ◽  
Sonya Sulistyono ◽  
Iin Ervina ◽  
Dadang Supriyanto ◽  
Nunung Nuring Hayati ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Traffic Safety ◽  
High Speed ◽  
Probability Model ◽  
Binary Logistic Regression ◽  
Driving Behavior ◽  
Maximum Speed ◽  
Speed Limit ◽  
Negative Consequences ◽  
Driving Experience

Driving at high speed has negative consequences, namely, the high number of accidents. Several factors have been considered as causes of the increasing severity of victims of traffic accidents, such as a human, vehicle, and environmental factors. The risky driving behavior factor is a factor that needs to be considered in traffic safety studies. This study aims to determine the probability model of speeding behavior based on several driver characteristics and their relationship to accident involvement. This study used a binary logistic regression method to determine the probability of driving behavior exceeding the speed limit and accident involvement. The results showed that the younger a person is, the higher the probability of breaking the maximum speed limit. Furthermore, driving experience also shows a similar trend, where the longer the driving experience of someone, the less likely it is to be involved in an accident. Directions for further research are also presented. Berkendara dengan kecepatan tinggi mempunyai konsekuensi negatif, yaitu tingginya angka kecelakaan. Beberapa faktor telah dipertimbangkan sebagai penyebab dari peningkatan tingkat keparahan korban kecelakaan lalulintas. Faktor tersebut seperti faktor manusia, kendaraan, dan lingkungan. Faktor perilaku berkendara yang berbahaya, menjadi faktor yang perlu diperhatikan dalam kajian keselamatan lalulintas. Penelitian ini bertujuan untuk mengetahui model probabilitas pada perilaku speeding berdasarkan beberapa karakteristik pengendara, serta hubungannya dengan keterlibatan kecelakaan. Penelitian ini menggunakan metode regresi logistik biner untuk mengetahui probabilitas perilaku berkendara melebihi batas kecepatan dan keterlibatan kecelakaan. Hasil penelitian menunjukkan bahwa semakin muda usia seseorang, maka semakin tinggi probabilitasnya dalam melanggar batas kecepatan maksimum. Lebih lanjut diperlihatkan bahwa pengalaman mengemudi juga menunjukkan tren yang serupa. Pengalaman mengemudi seseroang, yang lebih lama akan memperkecil kemungkinan dalam keterlibatan kecelakaan. Arahan untuk penelitian selanjutnya juga ditampilkan.

scholarly journals Safety and health of professional drivers who drive on Brazilian highways

2017 ◽  
Vol 51 (0) ◽  
Author(s):  
Fernanda Veruska Narciso ◽  
Marco Túlio de Mello
Keyword(s):  
Quality Of Life ◽  
Traffic Accidents ◽  
Working Hours ◽  
Truck Drivers ◽  
Education Programs ◽  
Professional Drivers ◽  
Global Epidemic ◽  
Safety And Health ◽  
Rest Breaks

ABSTRACT Traffic accidents and resulting injuries and deaths have become a global epidemic. In Brazil, most professional drivers, especially truck drivers, face irregular working hours and can be awake for more than 18 hours/day, which reduces their performance and alertness. In this article, we discuss the laws related to Brazilian professional drivers and their current amendments (No. 12,619/2012 and No. 13,103/2015) in relation to working hours at the wheel and rest breaks, which are vital for the quality of life of drivers and society in general. We note that the new law appears to be less efficient than the previous one as it causes insecurity and concern to the users of the transportation system, drivers, and employers. To restrict and reduce accidents, deaths, and injuries in traffic, appropriate legislation is essential, aiming at the safety of workers and users of highways. The law must also benefit the commercial aspect, strengthening the reduction in production and logistics losses. Additionally, traffic education programs are needed, as well as better supervision in relation to total working hours.

scholarly journals The Driver Behaviour and Impact of Speed on Road Safety on the Motorways in Croatia

2017 ◽  
Vol 29 (2) ◽  
pp. 155-164
Author(s):  
Goran Zovak ◽  
Goran Kos ◽  
Boris Huzjan
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Road Safety ◽  
Traffic Accidents ◽  
Straight Section ◽  
Driver Behaviour ◽  
Speed Limits ◽  
Survey Results ◽  
Geometric Elements ◽  
High Serviceability

The paper presents the current research related to the speed of traffic flow on the roads of high serviceability. It analyses the speed of vehicle as one of the main causes of traffic accidents. A flat four-lane motorway section, motorway section in the tunnel and a city bypass section were chosen for this research, and several speed limit scenarios for the vehicles have been applied with the aid of variable signalling. The survey results show that few vehicles respect the speed limits in traffic in the case of a straight section of motorway or city stretch of the motorway which has good geometric elements; however, speed limits are exceptionally well respected in tunnels. Although a large number of drivers do not respect the signs, a certain group of drivers can be influenced by variable signs of limitations, and thus positive changes can be achieved in traffic flow which will result in increasing the traffic safety on the motorways. Thus, increasing the degree of respect for speed limits on the motorways directly affects the increase in the level of traffic safety. It is necessary to influence the group of drivers who do not respect the speed limits with other measures, including repressive ones.

scholarly journals The Development of Data Warehouse to Support Data Mining Technique for Traffic Accident Prediction

2018 ◽  
Vol 73 ◽  
pp. 12007
Author(s):  
Budiawan Wiwik ◽  
Singgih Saptadi ◽  
Ary Arvianto
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Prediction Models ◽  
Data Access ◽  
Design Data ◽  
Accident Prediction ◽  
The World

Traffic accidents are one of the major health problems that cause serious death in the world and ranks 9th in the world. Traffic accidents in Indonesia ranks 5th in the world. One effort to improve traffic safety is to design traffic accident prediction models. Prediction models will utilize accident-related data in traffic through data mining processing. The data warehouse offers benefits as a basis for data mining. Building an effective data warehouse requires knowledge and attention to key issues in database design, data acquisition and processing, as well as data access and security. This study is the first step in the development of data mining accidents based prediction system. The output of this initial stage is the design of data warehouses that can provide periodic and incidental data to the data mining process, especially in the prediction of accidents. The method used to design data warehouse is Entity Relationship Diagram (ERD).

scholarly journals Analyses of Aggressiveness, Impulsiveness, and Demographics of the Drivers in Sulaimaniyah City Using Questionnaire Forms

2020 ◽  
Vol 7 (3) ◽  
pp. 241-254
Author(s):  
Hardy Karim ◽  
Keyword(s):  
Personality Traits ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Driving Behavior ◽  
Potential Contribution ◽  
Moderate Correlation ◽  
Aggressive Driving ◽  
Male And Female ◽  
Gender And Age ◽  
Measuring Scale

In order to increase traffic safety on our roads, certain forms of behavior and personality traits of passenger car drivers were studied. As an attempt to understand the potential contribution of drivers’ impulsiveness and aggressiveness in traffic accidents in Sulaimaniyah City, this study was conducted. The correlation between drivers’ impulsiveness and aggressiveness were also explored. Participants, who filled Barratt Impulsiveness Scale (BIS-11) and Aggressive Driving Behavior Questionnaire (ADBQ), were 244 drivers. The male drivers who answered the questionnaires were 143, while female drivers were 101. The results of the statistical analyses showed that male drivers are driving more aggressively than female drivers; as a result, male drivers faced higher numbers of traffic accidents than female drivers. There were no significant differences between male and female drivers regarding drivers’ impulsivity. Speeding as a measuring scale of the aggressive driving is significantly correlated with second-order impulsiveness subscales. The attentional and motor impulsiveness subscales are more correlated with the total score of the driving aggressiveness than non-planning subscale. There was moderate correlation between the impulsiveness total score and the overall aggressiveness score. The impulsiveness of the drivers was negatively correlated with the drivers’ ages and positively correlated with number of crashes; while the driving aggressiveness was significantly correlated with number of crashes and negatively with gender and age of the drivers. The traffic police in Sulaimaniyah City can benefit from the results of this paper during permitting driving license and enforcement processes.

scholarly journals Traffic Accidents Analysis on Dry and Wet Road Bends Surfaces in Greater Manchester-UK

2017 ◽  
Vol 2 (3) ◽  
pp. 284-291 ◽  
Author(s):  
Karzan S. Ismael ◽  
Noorance A. Razzaq
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Safety Issue ◽  
Health And Safety ◽  
Weather Conditions ◽  
Road Surface ◽  
Road Accidents ◽  
Driver Behaviour ◽  
Traffic Lights ◽  
On The Road

Road accidents becomes global health and safety issues because of the gradual increase in the number of injuries and fatalities. In the UK, road accidents due to weather conditions has been one of the traffic safety challenges for researchers as well as drivers particularly in Greater Manchester. This is because of its influence on driver behaviour approaching traffic lights on the road bends. Hence, to better understand driver behaviour, this paper presents various driving behaviour on wet and dry road conditions. Data were obtained from police reports of road accidents at hazardous locations in Greater Manchester between 2011 and 2015. The reported data covers information regarding: Accidents, Vehicle, and Casualties. The obtained data was used to examine how road surface is associated with road accidents by using Chi-Square statistical test. The analysis showed that road surface significantly contributed to accidents at bend roads. Moreover, drivers’ behaviour was investigated as they can be expected to have a significant impact on accident occurrence. Finally, the main goal is that these results might reflect the safety issue at bend roads.

Sign in / Sign up

Export Citation Format

Share Document