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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: 31 December 2024 | Viewed by 11951

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Special Issue Editors

Dr. Nirajan Shiwakoti

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Guest Editor

School of Engineering, RMIT University, Carlton, VIC 3053, Australia
Interests: human factors in transport and logistics; adoption and deployment of connected and autonomous vehicles; passenger crowd dynamics and evacuation management; supply chain mangement and logistics
Special Issues, Collections and Topics in MDPI journals

Dr. Xiaomeng Shi

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Guest Editor

Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing 211189, China
Interests: active mode traffic; active traffic safety; human factors; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals

Dr. Kayvan Aghabayk

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Guest Editor

School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
Interests: transport safety; human behavior; public transport; pedestrian evacuation

Dr. Shuqi Xue

E-Mail Website
Guest Editor

School of Modern Posts, Xi'an University of Posts and Telecommunications, Xi’an 710121, China
Interests: transportation system optimization; traffic flow theory; pedestrian safety; passenger crowd dynamics and evacuation management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The safety of transport users when moving within the transport system is a top priority for the planning and design of the sustainable transport system. However, millions of people are killed or seriously injured on the world’s roads each year. Likewise, insecurity in public transit systems due to crime, bodily injury, and rude behaviour has led to fear among public transport users. Natural and human-induced disasters have raised the necessity of safe evacuation management of passengers at major transport hubs. The emerging transport modes such as micromobility and connected and autonomous vehicles (CAV) may lead to safety and security issues and instead becoming a net burden on society. The COVID-19 pandemic has called the resiliency of the public transport system to question. This topic aims to publish articles on the latest advancements in safety and security across all transport modes. We would like to invite researchers to contribute original research articles as well as review articles that fit within the scope of this Special Issue.

Dr. Nirajan Shiwakoti
Dr. Xiaomeng Shi
Dr. Kayvan Aghabayk
Dr. Shuqi Xue
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

17 pages, 1265 KiB

Open AccessArticle

Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-Vehicle Crashes

by Masayoshi Tanishita and Yuta Sekiguchi

Sustainability 2023, 15(17), 13191; https://doi.org/10.3390/su151713191 - 01 Sep 2023

Viewed by 859

Abstract

Single- and multi-vehicle crashes are a significant issue that has economic and social costs and has therefore gained attention. This study explored the factors associated with injury severity for both single- and multi-vehicle crashes using over 550,000 crash data in Japan from 2019 to 2021. The determinants of road infrastructure and traffic control were identified while considering driver, vehicle, environmental, and accident characteristics, using ordered logit and bias-reduced binomial regression models. Our findings are as follows. Traffic control variables had no significant effect on the injury of single-vehicle crashes. Guardrails were associated with higher severity in both single-vehicle and multi-vehicle crashes at intersections. The impact of the centerline varied between intersections and non-intersections for multi-vehicle crashes. The results of this study provide transportation agencies with important guidance for road infrastructure and transport control. Full article

(This article belongs to the Special Issue Transport Safety)

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29 pages, 757 KiB

Open AccessArticle

Latent Class Cluster Analysis and Mixed Logit Model to Investigate Pedestrian Crash Injury Severity

by Arsalan Esmaili, Kayvan Aghabayk and Nirajan Shiwakoti

Sustainability 2023, 15(1), 185; https://doi.org/10.3390/su15010185 - 22 Dec 2022

Cited by 1 | Viewed by 2175

Abstract

Traffic crashes involving pedestrians have a high frequency in developing countries. Among road users, pedestrians are the most vulnerable, as their involvement in traffic crashes is usually followed by severe and fatal injuries. This study aims to identify pedestrian crash patterns and reveal the random parameters in the dataset. A three-year (2015–2017) pedestrian crash dataset in Mashhad, Iran, was employed to investigate the influence of a rich set of factors on pedestrian injury severity, some of which have been less accounted for in previous studies (e.g., the vicinity to overpasses, the existence of vegetated buffers, and park lanes). A two-step method integrating latent class cluster analysis (LCA) and the mixed logit model was utilized to consider unobserved heterogeneity. The results demonstrated that various factors related to the pedestrian, vehicle, temporal, environmental, roadway, and built-environment characteristics are associated with pedestrian injuries. Furthermore, it was found that integrated use of LCA and mixed logit models can considerably reduce the unobserved heterogeneity and uncover the hidden effects influencing severity outcomes, leading to a more profound perception of pedestrian crash causation. The findings of this research can act as a helpful resource for implementing effective strategies by policymakers to reduce pedestrian casualties. Full article

(This article belongs to the Special Issue Transport Safety)

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15 pages, 1953 KiB

Open AccessArticle

Safety, Gender, and the Public Transport System in Santiago, Chile

by Carolina Busco, Felipe González and Nelson Lillo

Sustainability 2022, 14(24), 16484; https://doi.org/10.3390/su142416484 - 09 Dec 2022

Cited by 1 | Viewed by 2033

Abstract

This research evaluated gender differences in the perception of safety in public transport in Santiago, Chile using quantitative and qualitative approaches. With data from the National Urban Citizen Security Survey 2019 (ENUSC), a gender comparison was made regarding the perception of safety in four scenarios: inside buses, inside the metro, at bus stops, and waiting for buses at night. Four ordinal logistic regression models were estimated to analyze how sociodemographic factors and variables associated with the perception of crime influence rider perceptions of safety in public transport. To complement the results, four focus groups were developed to obtain a deep understanding of the participants’ experiences with safety in the Santiago public transport system. We concluded that there is a high perception of insecurity in public transport for both men and women. In general, perceived insecurity inside buses, inside the metro, and waiting for public transport at night is greater among women, older people, and national citizens. Other influencing variables are the perception of insecurity regarding crime in general, the fear of being a victim of a crime, or negative situations that occur in the neighborhood, such as the presence of robberies, alcohol, and drug consumption. We proposed new variables such as fear of harassment, traffic accidents, discrimination, contagious diseases, and street protests among others. To carry out a precise public policy on this matter, a permanent scan on security issues in public transport should be developed, considering a complete set of variables. This result can be applied in Chile and all Latin American countries. Full article

(This article belongs to the Special Issue Transport Safety)

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19 pages, 1651 KiB

Open AccessArticle

Risk Assessment Model and Sensitivity Analysis of Ordinary Arterial Highways Based on RSR–CRITIC–LVSSM–EFAST

by Jianjun Wang, Chicheng Ma, Sai Wang, Xiaojuan Lu and Dongyi Li

Sustainability 2022, 14(23), 16096; https://doi.org/10.3390/su142316096 - 01 Dec 2022

Cited by 1 | Viewed by 1201

Abstract

In this paper, in order to evaluate the traffic safety status of ordinary arterial highways, identify the sources of safety risks, and formulate safety development countermeasures for arterial highways to reduce accident risks, a combination method involving rank-sum ratio (RSR), criteria importance though intercriteria correlation (CRITIC), and least squares support vector machine (LVSSM) is adopted. The traffic safety risk index system and risk assessment model of ordinary arterial highways with two dimensions of risk severity and accident severity are established. Based on the global sensitivity analysis of the extended Fourier amplitude sensitivity test (EFAST), the resulting risk assessment model for ordinary arterial highways is proposed. Combined with the current traffic safety situation of ordinary arterial highways in Weinan City, Shaanxi Province, China, data collection and analyses were carried out from the perspectives of traffic operation status, personnel facilities management, road environment characteristics, and accident occurrence patterns. The results show that the risk level of ordinary arterial highways can be obviously divided into warning areas, control areas, and prompt areas. The proportion of roads through villages and the number of deceleration facilities belong to the highly sensitive indicators of the S107 safety risk, which need to be emphatically investigated. This analysis method based is on the RCLE (RSR-CRITIC-LVSSM-EFAST) risk assessment model and has high operability and adaptability. It can be adaptively divided according to the requirements of risk-level differentiation, and the road risk classification can be displayed more intuitively, which is conducive to formulating targeted improvement measures for arterial highway safety and ensuring the safe and orderly operation of arterial highway traffic. Full article

(This article belongs to the Special Issue Transport Safety)

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12 pages, 2499 KiB

Open AccessArticle

Effect of Situation Kinematics on Drivers’ Rear-End Collision Avoidance Behaviour—A Combined Effect of Visual Looming, Speed, and Distance Analysis

by Qingwan Xue, Xijun Ouyang, Yi Zhao and Weiwei Guo

Sustainability 2022, 14(22), 15103; https://doi.org/10.3390/su142215103 - 15 Nov 2022

Viewed by 1089

Abstract

Considering the large proportion of rear-end collisions occurring in our daily life and the severity it may lead to, the objective of this study was to investigate the effect of situation kinematics on drivers’ rear-end collision avoidance behaviour after brake onset. A wide range of lead vehicle deceleration scenarios were designed based on driving simulator experiments to collect drivers’ deceleration behaviour data. Different from measures (e.g., speed, the lead vehicle’s deceleration et al.) often adopted in previous studies, a visual looming-based measure at different time points was calculated combined with analysis of speed and distance to quantify situation kinematics in this study. The Spearman’s nonparametric rank correlation test was firstly conducted to examine the correlation between visual looming-based metrics and related deceleration behaviour. The mixed model was performed on drivers’ brake jerk and maximum deceleration rate, while the logistic model was then performed to predict the probability of the occurrence of rear-end collisions. Spearman’s nonparametric test showed that both deceleration ramp-up and drivers’ maximum deceleration rate increase significantly as the looming traces increase faster. Results of the logistic model indicated that the probability of occurrence of a potential collision might be higher if the situation at the brake onset is quite urgent and braking is moderate. It was demonstrated that both drivers’ deceleration ramp-up and maximum deceleration rate could be highly kinematic-dependent, and visual looming, driving speed, and distance can be useful information for drivers to take relative deceleration actions. Full article

(This article belongs to the Special Issue Transport Safety)

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15 pages, 1260 KiB

Open AccessArticle

A Bayesian Approach to Examine the Impact of Pavement Friction on Intersection Safety

by Mostafa Sharafeldin, Omar Albatayneh, Ahmed Farid and Khaled Ksaibati

Sustainability 2022, 14(19), 12495; https://doi.org/10.3390/su141912495 - 30 Sep 2022

Cited by 5 | Viewed by 1270

Abstract

The safety of intersections has been the focus of many studies since intersections are considered hazardous zones of road networks. Identifying the main contributing factors of severe traffic crashes at intersections is crucial to implementing appropriate countermeasures. We investigated the major contributing factors to crash injury severity at intersections, particularly pavement surface friction. Nine years of intersection crash data in Wyoming have been analyzed for this study. The random forest technique was employed to identify the importance of critical variables influencing crash injury severity risk. Subsequently, a Bayesian ordinal probit model was applied to examine the relationships between crash injury severity risk and these crash contributing factors. As per the random forest model’s results, pavement friction has a strong impact on crash injury severity risk along with using safety restraints, intersection type, signalized or unsignalized, reckless driving, and crash type. The results of the Bayesian model demonstrated that higher pavement surface friction levels and proper use of restraints reduced the likelihood of severe injury. Based on these findings, several countermeasures may be proposed, such as those pavement friction requirements, driver’s education, and traffic law enforcement to mitigate injury severity concerns at intersections. Full article

(This article belongs to the Special Issue Transport Safety)

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10 pages, 242 KiB

Open AccessArticle

The Role of Big Five Personality Traits in Explaining Pedestrian Anger Expression

by Kayvan Aghabayk, Sina Rejali and Nirajan Shiwakoti

Sustainability 2022, 14(19), 12099; https://doi.org/10.3390/su141912099 - 24 Sep 2022

Cited by 2 | Viewed by 1955

Abstract

Although the relationship between anger and personality characteristics in the literature is well-acknowledged for drivers, there is a lack of systematic investigation of pedestrians. The current study aimed to evaluate pedestrian anger expression (PAX) and its contributing factors, including demographics, travel habits, and the big five personality traits. To test the effects of different variables on PAX scales, data from 742 respondents were collected. The data were analyzed through a two-stage approach of clustering and a logistic regression model. Participants were clustered into two groups of low expression and high expression based on their responses to PAX items. An exploratory factor analysis identified significant constructs of PAX, including “Adaptive/Constructive Expression”, “Anger Expression-In”, and “Anger Expression-out”. It was found that males were more likely to show high anger expressions. Public transport usage and previous crash involvement could significantly increase the probability of high anger expression. On the other hand, life satisfaction and intention to avoid traffic were negatively associated with high anger expression. The results revealed that neuroticism, extraversion, and openness to experience could positively contribute to higher anger expression; however, agreeableness and conscientiousness were negatively associated with high anger expression for pedestrians. Full article

(This article belongs to the Special Issue Transport Safety)

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