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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 21610

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Special Issue Editors

Dr. Junfang Tian

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Guest Editor

College of Management and Economics, Tianjin University, Tianjin 300072, China
Interests: traffic flow; traffic safety; intelligent transportation systems; transport policy
Special Issues, Collections and Topics in MDPI journals

Professor Zhongxiang Feng

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Guest Editor

School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China
Interests: traffic safety; driving behavior; transportation planning
Special Issues, Collections and Topics in MDPI journals

Dr. Shuxian Xu

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Guest Editor

College of Management Economics, Tianjin University, Tianjin 300072, China
Interests: economics of urban transportation; transportation and land use; traffic safety

Special Issue Information

Dear Colleagues,

With the recent advances in technologies around collecting and processing vehicle data, it is now more feasible for researchers to use these data to analyze the cause of accidents. These data could be obtained from current infrastructure-based traffic detectors such as GPS, radars, pavement sensors, Bluetooth, etc., and mobile applications such as Google, GAODE, BAIDU, etc. In addition to vehicle trajectory data, other multisource data have also become available, such as driver psychology and personality data, road condition data, weather data, front and rear vehicle data, etc. Therefore, gathering and processing big data and applying them to derive useful information for driver behavior and road safety analysis has gained significance. This Special Issue will welcome any research on driver behavior and road safety analysis. Topics include but are not limited to:

Driver behavior analysis. With multisource data, drivers’ behaviors can be analyzed more carefully through both questionnaires and modeling, such as attitudes, decision making processes, driving behavior modeling about risk driving, drowsy driving, night driving, aggressive driving, distracted and impaired driving, etc.

Road safety analysis. Some surrogate safety measures or a surrogate safety assessment model is desperately needed to provide a better understanding of collision-contributing factors and evaluate driving conditions more accurately. Some driver assistance strategies are also needed in collision warning systems to prevent rear, lateral, and other collisions.

The relationship between driver behavior and safety. Since a large proportion of traffic accidents are caused by human error, the impact of driving behavior on road safety plays the most important role in road safety analysis. Additionally, new technologies about road safety, such as intelligent transportation systems, communication between vehicles, and automatic driving, also have an impact on driving behavior, which is an interesting research hotspot.

Dr. Junfang Tian
Prof. Dr. Zhongxiang Feng
Dr. Shuxian Xu
Guest Editors

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Keywords

New sources of data and their use in traffic safety
Questionnaire analysis
Driving behavior modeling
Distracted and impaired driving
Surrogate safety measures
Safety evaluation
Driver assistance strategy
The relationships between driving behaviors and road safety

Published Papers (7 papers)

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Research

18 pages, 1242 KiB

Open AccessArticle

Evaluation of Road Safety Performance Based on Self-Reported Behaviour Data Set

by Vladimir Pajković and Mirjana Grdinić-Rakonjac

Sustainability 2021, 13(24), 13837; https://doi.org/10.3390/su132413837 - 15 Dec 2021

Cited by 2 | Viewed by 2151

Abstract

Self-reported behavioural data, being often linguistic variables that represent a qualitative measure of respondents’ opinions/attitudes, are vague, uncertain, and fuzzy in nature. A road safety performance index, based on these fuzzy data, should consider this uncertainty. In this study, fuzzy numbers were used to describe self-reported behaviour on Montenegrin roads, which was further integrated into the data envelopment analysis (DEA), a technique for measuring the relative performance of decision-making units (DMUs). The vagueness of the performance scores obtained in this way was treated with grey relational analysis (GRA). GRA was applied to the cross-efficiency (CE) matrix constructed by the DEA to distinguish Montenegrin municipalities’ performance, with the main goal of describing road safety in the observed territories in the environment of uncertain/grey data. It is concluded that the proposed DEA–GRA model, based on fuzzy data, provides a more reasonable and encompassing measure of performance, and with which the overall ranking position of municipalities can be obtained. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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14 pages, 3983 KiB

Open AccessArticle

Vehicle Door Opening Control Model Based on a Fuzzy Inference System to Prevent Motorcycle–Vehicle Door Crashes

by Cheng-Yong Huang

Sustainability 2021, 13(22), 12558; https://doi.org/10.3390/su132212558 - 13 Nov 2021

Cited by 3 | Viewed by 2498

Abstract

The goal of this research is to develop a fuzzy logic-based vehicle door control system to avoid motorcycle–vehicle door crash accidents. Accidents of this nature usually occur when the driver has parked the car, opens the door getting out of the car and collides with a motorcycle approaching from the rear, causing injury to the motorcyclist. In order to prevent such accidents, the fuzzy logic control system inputs the speed (MS) and safety distance (SD) of the motorcycle approaching from the rear, and then the fuzzy inference unit (FIU) calculates the clear output (Crisp) defuzzification Vehicle Door Opening Model (VDOM) value for the central locking system of the car, which can be used to trigger three modes, namely Danger Mode, Caution Mode and Warning Mode. In this study, the VDOM system is designed to trigger reasonable, reliable and consistent door control under different speeds of motorcycles coming from the rear and will be effectively applied to the door control of semi-automatic cars in the future. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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10 pages, 1230 KiB

Open AccessArticle

Analysis of Drivers’ Eye Movements on Roundabouts: A Driving Simulator Study

by Amin Azimian, Carlos Alberto Catalina Ortega, Juan Maria Espinosa, Miguel Ángel Mariscal and Susana García-Herrero

Sustainability 2021, 13(13), 7463; https://doi.org/10.3390/su13137463 - 04 Jul 2021

Cited by 11 | Viewed by 2930

Abstract

Roundabouts are considered as one of the most efficient forms of intersection that substantially reduce the types of crashes that result in injury or loss of life. Nevertheless, they do not eliminate collision risks, especially when human error plays such a large role in traffic crashes. In this study, we used a driving simulator and an eye tracker to investigate drivers’ eye movements under cell phone-induced distraction. A total of 45 drivers participated in two experiments conducted under distracted and non-distracted conditions. The results indicated that, under distracting conditions, the drivers’ fixation duration decreased significantly on roundabouts, and pupil size increased significantly. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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18 pages, 47730 KiB

Open AccessArticle

Evaluating the Impact of Sight Distance and Geometric Alignment on Driver Performance in Freeway Exits Diverging Area Based on Simulated Driving Data

by Xizhen Zhou, Binghong Pan and Yang Shao

Sustainability 2021, 13(11), 6368; https://doi.org/10.3390/su13116368 - 03 Jun 2021

Cited by 6 | Viewed by 2287

Abstract

The decision sight distance (DSD) at freeway exits is a major factor affecting traffic safety. Based on the Hechizhai Interchange in Xi’an City (Shaanxi Province, China), this paper designs a simulation experiment. Through a simulator study and a questionnaire survey, this paper discusses the impact of the DSD, 1.25 times the stopping sight distance (SSD) and a circular curve deflection on a driver’s driving state (including steering wheel angle rate and steering wheel angle frequency domain). Thirty volunteers participated in this research. The result shows that (1) it is safer to drive on an exit that meets DSD. (2) If it only meets the 1.25 times the SSD requirement, the overloaded driving tasks and operation would be more likely to cause crashes. The driving state of the driver on the right circular curve is obviously better than that on the left circular curve, because changing lanes to the right on the left circular curve does not meet the driver’s expectations. (3) Left and right circular curve should be treated differently in the driving area and the constant sight distance requirements should not be applied. (4) The left circular curve should be more stringent to ensure driving safety. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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23 pages, 305 KiB

Open AccessArticle

Drunk Drivers’ Willingness to Use and to Pay for Designated Drivers

by Rong-Chang Jou and Li-Wun Syu

Sustainability 2021, 13(10), 5362; https://doi.org/10.3390/su13105362 - 11 May 2021

Cited by 7 | Viewed by 2636

Abstract

While drunk driving accidents, which are a serious problem in Taiwan, have decreased in recent years, cases of drunk driving continue to emerge endlessly, and are a source of traffic risks even when the accidents cause no injuries. In order to prevent drunk driving and reduce car accidents, the government has made laws stricter, and has vigorously promoted “designated drivers”. As the concept of designated drivers is not common in Taiwan, this study mainly explores drunk drivers’ understanding of designated drivers in Nantou County and Taichung City, and investigates the willingness of drunk drivers to use and to pay for designated driving services. This study conducted a questionnaire survey on the drunk drivers of the drunk driving and traffic safety training course held at the Motor Vehicles Office. Double-hurdle and tobit models were applied to investigate the issues mentioned above. According to the test results, the tobit model was superior to the double-hurdle model. The estimation results indicated that distance, age, income, family conditions, and drinking habits influence the willingness to use and to pay for designated drivers. Gender, age, family background, and experience in designated driving cause differences in the willingness to use designated drivers in the two regions. It is expected that the conclusion of this study could provide a direction and reference for the future improvement of designated driving services. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

14 pages, 951 KiB

Open AccessArticle

Integration of Theory of Planned Behavior, Sensation Seeking, and Risk Perception to Explain the Risky Driving Behavior of Truck Drivers

by Zhenming Li, Siu Shing Man, Alan Hoi Shou Chan and Jianfang Zhu

Sustainability 2021, 13(9), 5214; https://doi.org/10.3390/su13095214 - 07 May 2021

Cited by 19 | Viewed by 4541

Abstract

Truck-related accidents account for a substantial portion of traffic accidents. Risky driving behavior is a main cause of traffic accidents. Understanding the risky driving behavior of truck drivers is therefore important in reducing truck-related accidents. This study aimed to propose and validate a research model that integrated a theory of planned behavior, sensation seeking, and risk perception to explain the risky driving behavior of truck drivers. A total of 471 valid data were collected from Chinese truck drivers in this study. Structural equation modeling and mediation analysis were used to examine the influence of factors in the research model on the risky driving behavior of truck drivers. Results showed that sensation seeking and risk perception of truck drivers were influential in shaping their intention to drive riskily with the mediation of attitude toward risky driving. Risk perception and attitude toward risky driving also had a negative influence and positive influence on the intention, respectively. On the basis of the findings, practical recommendations for reducing the risky driving behavior of truck drivers were provided for concerned parties. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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17 pages, 2794 KiB

Open AccessArticle

Beside and Behind the Wheel: Factors that Influence Driving Stress and Driving Behavior

by Víctor Corcoba Magaña, Xabiel García Pañeda, Roberto Garcia, Sara Paiva and Laura Pozueco

Sustainability 2021, 13(9), 4775; https://doi.org/10.3390/su13094775 - 24 Apr 2021

Cited by 8 | Viewed by 3186

Abstract

A large percentage of traffic accidents are due to human errors. Driving behavior and driving stress influence the probability of making these mistakes. Both are influenced by multiple factors, among which might be elements such as age, gender, sleeping hours, or working hours. The objective of this paper is to study, in a real scenario and without forcing the driver’s state, the relationship between driving behavior, driving stress, and these elements. Furthermore, we aim to provide guidelines to improve driving assistants. In this study, we used 1050 driving samples obtained from 35 volunteers. The driving samples correspond to regular commutes from home to the workplace. ANOVA and ANCOVA tests were carried out to check if there are significant differences in the four factors analyzed. Although the results show that driving behavior and driving stress are affected by gender, age, and sleeping hours, the most critical variable is working hours. Drivers with long working days suffer significantly more driving stress compared to other drivers, with the corresponding effect on their driving style. These drivers were the worst at maintaining the safety distance. Full article

(This article belongs to the Special Issue Driving Behavior and Road Safety)

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