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A special issue of Future Transportation (ISSN 2673-7590).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 20753

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Special Issue Editors

Prof. Dr. Andrew Morris

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Guest Editor

Transport Safety Research Centre, Loughborough University, Leicestershire LE11 3TU, UK
Interests: transport safety; human factors; driver behavior; vulnerable road user safety
Special Issues, Collections and Topics in MDPI journals

Dr. Jo Barnes

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Guest Editor

Transport Safety Research Centre, Loughborough University, Leicestershire LE11 3TU, UK
Interests: injury prevention; injury scaling; public transport; health impacts of transport and travel

Special Issue Information

Dear Colleagues,

Road transport is rapidly developing. Automated technologies are offering the capability of improving the safety and mobility of vehicles whilst reducing environmental impacts, and it has been suggested that risky driving behaviour, errors, and ultimately, crashes, will be prevented by “taking the driver out of the loop”. Adaptive driving support and information facilities may improve the driving experience, enabling drivers to make better use of their time in routine situations, whilst automated traffic management offers the opportunity to manage road infrastructure much more efficiently, thereby providing improvements to mobility and the environment. However, some transport and mobility challenges remain outstanding. Many of these safety challenges involve human factors and driver behaviour, particularly when considering driver interaction with new vehicle information systems, usability/user acceptance and user experience. Such issues are likely to become even more prevalent in the future due to the rapid global move towards vehicle automation. Therefore, this Special Issue offers readers an insight into some of the key emerging issues within transport and how human factor challenges associated with progress in these domains are being overcome. Key topics will include:

Vehicle automation.
Human–machine interaction.
Vulnerable road user safety.
Driver state and fitness to drive.
Driver workload and task demand.
Interaction of (partly) automated vehicles with vulnerable road users.
Human factors in mixed traffic conditions.
Older drivers/novice drivers.
Health impacts of future transport and travel.

We look forward to receiving your contributions.

Prof. Dr. Andrew Morris
Dr. Jo Barnes
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. Future Transportation is an international peer-reviewed open access quarterly 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 1000 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.

Keywords

vehicle automation
human–machine interaction
vulnerable road user safety
driver state and fitness to drive
driver workload and task demand
interaction of (partly) automated vehicles with vulnerable road users
human factors in mixed traffic conditions
older drivers/novice drivers
health impacts of future transport and travel

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Published Papers (11 papers)

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Research

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22 pages, 1781 KiB

Open AccessArticle

Micro-Mobility Safety Assessment: Analyzing Factors Influencing the Micro-Mobility Injuries in Michigan by Mining Crash Reports

by Baraah Qawasmeh, Jun-Seok Oh and Valerian Kwigizile

Future Transp. 2024, 4(4), 1580-1601; https://doi.org/10.3390/futuretransp4040076 - 10 Dec 2024

Viewed by 356

Abstract

The emergence of micro-mobility transportation in urban areas has led to a transformative shift in mobility options, yet it has also brought about heightened traffic conflicts and crashes. This research addresses these challenges by pioneering the integration of image-processing techniques with machine learning methodologies to analyze crash diagrams. The study aims to extract latent features from crash data, specifically focusing on understanding the factors influencing injury severity among vehicle and micro-mobility crashes in Michigan’s urban areas. Micro-mobility devices analyzed in this study are bicycles, e-wheelchairs, skateboards, and e-scooters. The AlexNet Convolutional Neural Network (CNN) was utilized to identify various attributes from crash diagrams, enabling the recognition and classification of micro-mobility device collision locations into three categories: roadside, shoulder, and bicycle lane. This study utilized the 2023 Michigan UD-10 crash reports comprising 1174 diverse micro-mobility crash diagrams. Subsequently, the Random Forest classification algorithm was utilized to pinpoint the primary factors and their interactions that affect the severity of micro-mobility injuries. The results suggest that roads with speed limits exceeding 40 mph are the most significant factor in determining the severity of micro-mobility injuries. In addition, micro-mobility rider violations and motorists left-turning maneuvers are associated with more severe crash outcomes. In addition, the findings emphasize the overall effect of many different variables, such as improper lane use, violations, and hazardous actions by micro-mobility users. These factors demonstrate elevated rates of prevalence among younger micro-mobility users and are found to be associated with distracted motorists, elderly motorists, or those who ride during nighttime. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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28 pages, 5176 KiB

Open AccessArticle

Pedestrian Interaction with a Novel Urban Light Rail Vehicle: Implications for Multi-Modal Crash Compatibility Standards

by Callum J. D. Bethell, Shubham Sharma, James Winnett and Darren J. Hughes

Future Transp. 2024, 4(4), 1177-1204; https://doi.org/10.3390/futuretransp4040057 - 14 Oct 2024

Viewed by 842

Abstract

This work investigates the risk to Vulnerable Road Users (VRUs) from a novel light rail vehicle using the pedestrian impact scenario outlined in CEN/TR 17420. At a 20 km/h impact speed, a maximum head impact criterion (HIC₁₅) value of 15.9 was obtained for a 50th-percentile anthropometric test device (ATD), with this value increasing to 120.2 at 30 km/h impact speed. Both results are within the CEN/TR 17420 prescribed limit of 1000. In both cases, the vehicle does not fully comply with CEN/TR 17420 recommendations due to insufficient lateral displacement of the ATD post-impact. A vehicle front-end design—which would be exempt from the CEN/TR 17420 impact testing—was designed and tested to the same framework. Despite being formally exempt from testing, the design also did not fully comply with CEN/TR 17420 lateral displacement requirements. Critical evaluation of the CEN/TR 17420 framework is presented, leading to recommendations about how updated frameworks should take a pragmatic approach in how they define VRUs, and the measurement criteria used for assessing VRU risk in collisions. Discussions are presented considering whether alternative frameworks, such as the Bus Safety Standard, should be applicable to assess the safety of the novel light rail vehicle. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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12 pages, 426 KiB

Open AccessArticle

Application of Hybrid Deep Reinforcement Learning for Managing Connected Cars at Pedestrian Crossings: Challenges and Research Directions

by Alexandre Brunoud, Alexandre Lombard, Nicolas Gaud and Abdeljalil Abbas-Turki

Future Transp. 2024, 4(2), 579-590; https://doi.org/10.3390/futuretransp4020027 - 28 May 2024

Viewed by 1060

Abstract

The autonomous vehicle is an innovative field for the application of machine learning algorithms. Controlling an agent designed to drive safely in traffic is very complex as human behavior is difficult to predict. An individual’s actions depend on a large number of factors that cannot be acquired directly by visualization. The size of the vehicle, its vulnerability, its perception of the environment and weather conditions, among others, are all parameters that profoundly modify the actions that the optimized model should take. The agent must therefore have a great capacity for adaptation and anticipation in order to drive while ensuring the safety of users, especially pedestrians, who remain the most vulnerable users on the road. Deep reinforcement learning (DRL), a sub-field that is supported by the community for its real-time learning capability and the long-term temporal aspect of its objectives looks promising for AV control. In a previous article, we were able to show the strong capabilities of a DRL model with a continuous action space to manage the speed of a vehicle when approaching a pedestrian crossing. One of the points that remains to be addressed is the notion of discrete decision-making intrinsically linked to speed control. In this paper, we will present the problems of AV control during a pedestrian crossing, starting with a modelization and a DRL model with hybrid action space adapted to the scalability of a vehicle-to-pedestrian (V2P) encounter. We will also present the difficulties raised by the scalability and the curriculum-based method. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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13 pages, 2386 KiB

Open AccessArticle

Studying the Impact of the COVID-19 Pandemic on Bikeshares as a Mode of Shared Micromobility in Major Cities: A Case Study of Houston

by Mehdi Azimi, Mustafa Muhammad Wali and Yi Qi

Future Transp. 2024, 4(1), 270-282; https://doi.org/10.3390/futuretransp4010014 - 7 Mar 2024

Cited by 4 | Viewed by 989

Abstract

A bikeshare system offers a convenient and cost-effective transportation service, providing shared bicycles for short-term use by individuals. It promotes affordability for users while fostering a healthier environment. By offering an alternative for those without access to private vehicles, it helps mitigate the rise in private car usage. Bike sharing also provides an important first-mile/last-mile commuting option. This study focuses on investigating the effects of the COVID-19 pandemic outbreak on bikeshare ridership, with a specific case study centered around Houston, Texas. The employed methodology involves a descriptive analysis and Negative Binomial regression modeling to uncover the relationship between the dependent variable (ridership) and the independent variables. The descriptive analysis revealed an overall increase in ridership during the COVID-19 period in 2020. Notably, longer duration trips were substantially higher in 2020 compared to 2019. Furthermore, the majority of trips occurred during off-peak hours, followed by evening and morning peak periods. Through regression analysis, this study found that the COVID-19 pandemic had a statistically significant positive impact on average daily ridership, with the number of COVID-19 cases positively influencing ridership levels. Additionally, the weekend indicator had a statistically significant positive impact on the average daily ridership. On the other hand, the temperature indicator did not show any significant impact on the average daily ridership, while precipitation had a statistically significant negative impact, leading to decreased ridership levels. The study highlights the significance of various factors in influencing bikeshare usage, contributing to a better understanding of urban transportation dynamics during such unprecedented times. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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19 pages, 3037 KiB

Open AccessArticle

Lived Experiences of People with and without Disabilities across the Lifespan on Autonomous Shuttles

by Seung Woo Hwangbo, Nichole E. Stetten, Isabelle C. Wandenkolk, Yuan Li and Sherrilene Classen

Future Transp. 2024, 4(1), 27-45; https://doi.org/10.3390/futuretransp4010003 - 5 Jan 2024

Viewed by 1610

Abstract

As an emerging, alternative mode of transportation, an in-depth understanding of autonomous shuttle (AS) experiences among all age groups, with and without disabilities, may impact acceptance and adoption of the AS, shape industry guidelines, and impact public policy. Therefore, this study analyzed qualitative data from older (n = 104), younger, and middle-aged (n = 106) adults and people with disabilities (n = 42). The data were obtained by asking participants four open-ended questions from an Autonomous Vehicle User Perception Survey. The result revealed seven themes (Safety, Ease of Use, Cost, Availability, Aging, AS Information, and Experience with AS) for older, younger, and middle-aged adults and six themes (all of the previously mentioned except for Aging) for people with disabilities. Frequency counts indicated priority attention, among all groups, to Safety and Ease of Use. This study provides valuable information pertaining to the experiences, concerns, and motivations of all potential users across age groups and disabilities—and may inform policymakers and industry partners to address their needs more adequately. These findings may contribute to improving and enhancing AS programming, design, and deployment in a safer, accessible, affordable, and tailored way. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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14 pages, 2765 KiB

Open AccessArticle

Investigating Runway Incursion Incidents at United States Airports

by Olajumoke Omosebi, Mehdi Azimi, David Olowokere, Yachi Wanyan, Qun Zhao and Yi Qi

Future Transp. 2023, 3(4), 1209-1222; https://doi.org/10.3390/futuretransp3040066 - 13 Oct 2023

Cited by 1 | Viewed by 4436

Abstract

According to the Federal Aviation Administration (FAA), the number of runway incursions is increasing. Over the last two decades, the number of runway incursions at U.S. airports has increased from 987 in 2002 to 25,036 in 2020. Runway incursions are a major threat to aviation safety, causing major delays and financial consequences for airlines, as well as injury or death through incidents such as aircraft collisions. The FAA promotes the implementation of runway safety technology, infrastructure, procedural methods, alterations to airport layouts, and training practices to reduce the frequency of runway incursions. In this paper, the relationship between airport geometry factors, mitigating technologies, and the number of runway incursions at large hub airports in the United States was investigated using a random effects Poisson model for analyses of panel data. Airport operations data from the FAA Air Traffic Activity System, runway incursion data from the FAA Aviation Safety Information Analysis and Sharing System from 2002 to 2020, and airport geometry data created using airport geometry features from the FAA airport diagrams were collected. Thirty large hub airports with FAA-installed mitigating technologies were investigated. The model identified significant variables that correlate with runway incursions for large hub airport categories defined by the National Plan of Integrated Airport Systems (NPIAS). The model results indicate that airports with significant numbers of runway-to-runway intersection points increase runway incursion rates and mitigating technologies Runway Status Lights (RWSLs) and Airport Surface Detection Equipment, Model X (ASDE-X), can help reduce runway incursions at severity levels A and B. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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14 pages, 955 KiB

Open AccessArticle

The Impact of Pedestrian Distraction on Safety Behaviours at Controlled and Uncontrolled Crossings

by Amy O’Dell, Andrew Morris, Ashleigh Filtness and Jo Barnes

Future Transp. 2023, 3(4), 1195-1208; https://doi.org/10.3390/futuretransp3040065 - 12 Oct 2023

Viewed by 2868

Abstract

To investigate differences in the safety behaviours of distracted and non-distracted pedestrians crossing roads, an unobtrusive observational study was conducted in Leicestershire, UK. Video recordings were taken of 1409 pedestrians crossing roads at controlled and uncontrolled crossing sites, both on a university campus and in urbanised town centre locations. On average, 42% of pedestrians were visibly distracted while crossing, and distracted pedestrians demonstrated significantly fewer safety behaviours than non-distracted pedestrians. They generally took longer to cross the road and made fewer looks towards the traffic environment, particularly at controlled crossings. Of all distraction activities, talking to another pedestrian had the most negative impact on safety behaviours. The findings highlight areas requiring further investigation, including distraction behaviours such as engaging with other pedestrians and supervising children. The results also identify that controlled crossings may benefit from targeted interventions to improve pedestrian safety. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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23 pages, 3883 KiB

Open AccessArticle

Comparing Enhanced Models for Evaluating the Economic Impact of Airports

by Ivaciane de Quadra Magalhães, Anderson Ribeiro Correia, Michelle Carvalho Galvão da Silva Pinto Bandeira, Mauro Zackiewicz and Luiz Antonio Tozi

Future Transp. 2023, 3(3), 1124-1146; https://doi.org/10.3390/futuretransp3030062 - 20 Sep 2023

Viewed by 2685

Abstract

Evaluating the economic impact of airports is crucial for understanding the benefits they bring to a region. However, when an area has more than one airport, it becomes essential to analyze each airport’s contribution to the local economy to make informed investment and policy decisions. Thus, studying economic models that can distinguish each airport’s impact on the region’s economy becomes essential. In this context, this paper aims to compare three different approaches to determine the economic contributions of airports in a given region and identify their social and economic benefits. The International Civil Aviation Organization recommends using input–output analysis in this context. The study considered three weight factors for the input–output basic model: circular buffer, displacement time, and Huff’s gravitational model. The analysis was performed using the three largest airports in São Paulo state, Brazil, due to their proximity and influence on the surrounding areas. The models were compared based on their efficiency and accuracy in reflecting the reality of the case study context. The study identified the most suitable model for establishing correlations between investments made in airport infrastructure and the generation of gross domestic product, employment, and added value. This study fills a gap in the existing literature by proposing improvements to the methods for evaluating airports’ economic and social benefits. In recent times, airport investors, both in the government and private sectors, have become increasingly demanding in their need for accurate analyses before making investments. Therefore, the results of this paper will provide valuable insights into the benefits of investing in airport infrastructure and help policymakers and investors make informed decisions. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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16 pages, 1021 KiB

Open AccessArticle

To Share or to Own? Understanding the Willingness to Adopt Shared and Owned Electric Automated Vehicles on Three Continents

by Tim Dijkhuijs, Fabian Israel and Dea van Lierop

Future Transp. 2023, 3(3), 1108-1123; https://doi.org/10.3390/futuretransp3030061 - 13 Sep 2023

Cited by 2 | Viewed by 1452

Abstract

Electric automated vehicles (AVs) are expected to become part of the transportation system within the coming years. The implications of their implementation are still uncertain. What is known is that human behaviour will be central to determining AV adoption. This research aims to gain insight into how potential users of privately owned (PAVs) and shared (SAV) electric automated vehicles are characterised across three different continents assessing the influence of cultural and geographic features, personal attitudes and characteristics and the perceived advantages and disadvantages of AVs. Using survey data collected among residents (N = 1440) in Greater Sydney, Australia; Greater Montréal, Canada; and the Randstad, the Netherlands, this paper explores individuals’ willingness to adopt PAVs and SAVs using statistical descriptive analysis and logistic regression models. The study supports the impact of personal characteristics (e.g., age and travel characteristics) and attitudes towards personal and societal gains on the willingness to adopt AVs. Furthermore, this paper provides cross-continental evidence for the regional socio-urban context, affecting the desire to adopt AVs in different forms. Policy-makers should consider these factors and tailor different strategies according to cultural norms in order to motivate a coherent and sustainable implementation of AVs into existing and future mobility landscapes. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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17 pages, 643 KiB

Open AccessArticle

Motivational Patterns and Personal Characteristics of Potential Carsharing Users: A Qualitative Analysis

by Avgi Vassi, Christos Karolemeas, Stefanos Tsigdinos and Efthimios Bakogiannis

Future Transp. 2023, 3(3), 1068-1084; https://doi.org/10.3390/futuretransp3030059 - 7 Sep 2023

Viewed by 1491

Abstract

In the last decade, in Europe and the US, carsharing has become a mainstream transportation mode offering a sustainable solution to serious urban problems such as pollution, economic crisis, congestion, and parking. In Greece, carsharing is currently entering its commercial phase. Planners and providers strive to gain an insight into the factors influencing the use of carsharing to effectively implement carsharing systems (CSS). In this context, understanding the motives and usage conditions are considered necessary. Based on a qualitative analysis (semi-constructed interviews, n = 52), this paper identifies motivational patterns as well as personal characteristics of potential users that can be further explored through quantitative research methods. During the data analysis process, participants’ responses were classified into categories that revealed not only the factors that motivated them but also unveiled the challenges they face when utilizing carsharing schemes. These factors were the following: familiarity, comfort, mindset, everyday life, usability, and economy. Next, these factors were analyzed further based on the personal characteristics of the respondents preparing the ground for quantitative research in future research initiatives. Notably, the present findings could be beneficial to operators, policymakers, and stakeholders endeavoring to appraise shared mobility schemes in Greece and Mediterranean countries in general. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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16 pages, 601 KiB

Open AccessSystematic Review

How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review

by Alexandra Loew, Christina Kurpiers, Martin Götze, Sven Nitsche and Klaus Bengler

Future Transp. 2024, 4(1), 283-298; https://doi.org/10.3390/futuretransp4010015 - 13 Mar 2024

Viewed by 1557

Abstract

This paper summarizes the research on countermeasures against driver fatigue based on a comprehensive systematic literature review. Driver fatigue, induced by task monotony during conditional automated driving (CAD, SAE Level 3), can increase the risk of road accidents. There are several measures that counteract driver fatigue and aim to reduce the risk caused by a fatigued driver in the context of CAD. Twelve selected articles focusing on driver fatigue countermeasures in CAD were analyzed. The findings and conclusions are presented, focusing on the countermeasures themselves and their implementation. The countermeasures were critically discussed, especially regarding effectiveness and applicability. They seem to be effective in counteracting driver fatigue. However, the measures are not easily compared because they were studied in various experimental settings and various driver fatigue measurements were used. Different countermeasures have proven to be effective in reducing fatigue during CAD. For this reason, further investigation is needed to gain further insights into their applications, advantages, and disadvantages. Further studies will be conducted to verify the best solution regarding their effectiveness and applicability. Full article

(This article belongs to the Special Issue Emerging Issues in Transport and Mobility)

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