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Applied Sciences
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Innovations in Road Safety and Transportation
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Innovations in Road Safety and Transportation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 4335

Special Issue Editors

Prof. Dr. Mariano Pernetti

E-Mail Website
Guest Editor
Department of Engineering, University of Campania Luigi, 581100 Naples, Italy
Interests: road safety; passive safety systems; roadside barriers; crash cushion
Special Issues, Collections and Topics in MDPI journals
Prof. Massimo Losa

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Pisa, Largo L. Lazzarino, 1, 56122 Pisa, Italy
Interests: road safety; accident data analysis; surface pavement characteristics; tyre pavement interaction; road monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Transportation systems constantly change to ensure that more people and things can reach their destination in a lower time, more safely, and with the smallest amount of resources possible. Technological innovations hold a lot of promise toward these goals. One of these consists of self-driving vehicles, which move with minimal or null human input. They use integrated technologies, including but not limited to sensors, vehicle-to-everything communication, artificial intelligence, big data, and cloud computing. The benefits of autonomous vehicles include the following: (1) a reduction in costs per kilometer, (2) increased road capacity, (3) reduced travel and parking search time, (4) more travel comfort, (5) enhanced road safety, (6) possibility to perform activities other than driving, etc.

This innovation has gained considerable attention in research not only related to vehicles but also to infrastructures and human behavior. The potential safety and efficiency gains of autonomous vehicles strictly depend on infrastructure characteristics and vehicle heterogeneity. It is not possible to have proper infrastructure within a few years because the road network is, to a large extent, already developed, and reconstruction projects are conditioned by available funding, physical constraints, or social or environmental considerations. Vehicle homogeneity is also difficult to achieve within a few years. Over a long transition period, there will be a mix of autonomous vehicles with different automation levels and completely unautomated vehicles. The third level of automation is one of the more challenging, as vehicles would be able to drive themselves most of the time but would require a person to take over in road or traffic situations that the vehicles could not handle. This requires a quick intervention by a person that could be relaxing because they are not involved in driving activities.

This Special Issue will address some of the most essential issues currently affecting the benefits of self-driving vehicles. It welcomes high-quality original research and review articles that cover a broad range of topics related to this innovation. Research papers (case studies, reviews, and policy related) from different parts of the world are invited. Potential topics include, but are not limited to, the following:

  • Sensors and AI for autonomous vehicles.
  • Autonomous vehicle testing in complex environments.
  • Acceptance of self-driving cars.
  • Operational design domain for automated vehicles.
  • Road design rules to accommodate autonomous vehicles with different levels of automation.
  • Optimization procedures for upgrading existing infrastructure to accommodate autonomous vehicles with different levels of automation.
  • Effects of autonomous vehicles penetration rate.
  • Truck platooning.
  • Weather and pavement condition effects on the “behavior” of autonomous vehicles.
  • Roadside safety decreasing needs.

Prof. Dr. Mariano Pernetti
Prof. Dr. Massimo Losa
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. Applied Sciences 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.

Keywords

  • road safety
  • transport infrastructures
  • intelligent transportation systems
  • autonomous vehicles
  • operational design domain
  • truck platooning
  • driving simulation

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Published Papers (4 papers)

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Research

24 pages, 6371 KiB  
Article
Determining the Safety Level of State Roads: An Italian Case Study
by Mariano Pernetti, Arianna Antoniazzi, Misagh Ketabdari, Maurizio Crispino and Emanuele Toraldo
Appl. Sci. 2024, 14(15), 6663; https://doi.org/10.3390/app14156663 - 30 Jul 2024
Viewed by 973
Abstract
This study aims to establish an effective approach for evaluating the safety performance of road infrastructure. Road safety levels are typically quantified using safety performance indicators. However, due to the stochastic nature of accidents, many safety performance indicators cannot adequately and completely describe [...] Read more.
This study aims to establish an effective approach for evaluating the safety performance of road infrastructure. Road safety levels are typically quantified using safety performance indicators. However, due to the stochastic nature of accidents, many safety performance indicators cannot adequately and completely describe reality. Therefore, predictive methods based on regression models are widely used. This approach also allows for the identification of latent risk conditions in the infrastructure, even in the absence of accidents. Among available approaches, the Highway Safety Manual (HSM) methodology is chosen for its synthesis of validated highway research and best practices for incorporating safety into both new design and rehabilitation. For this study, a preliminary new version of HSM is used. The application of this method, which combines a predictive model with observed accidents through an empirical Bayesian approach, requires a calibration process that is crucial to tailoring this method to the specific study context. In this research, the predictive model is calibrated for single carriageway roads with one lane per direction across the Italian national network. Following calibration, the safety indicators are evaluated. The results obtained according to different indicators are compared to show the importance of adopting this method to counteract the regression to the mean of observed crashes. In fact, the method, supported by empirical Bayesian analysis, enables the identification of high-risk sections of the road network, selecting more sections that would be neglected by traditional indicators based solely on observed crashes. Finally, a possible approach to prioritizing sites for inspection based both on the excess of crashes and the Safety Potential (SAPO) is proposed. In addition, SAPO is adjusted to local conditions to account for the specific context and the decreasing trend of accidents over the years. Full article
(This article belongs to the Special Issue Innovations in Road Safety and Transportation)
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23 pages, 4861 KiB  
Article
Exact Mathematical Solution for Maximum Transient Offtracking Calculation of a Single-Unit Vehicle Negotiating Circular Curves
by Vladan Ilić, Miloš Lukić, Dejan Gavran, Sanja Fric, Filip Trpčevski, Stefan Vranjevac and Nikola Milovanović
Appl. Sci. 2024, 14(13), 5570; https://doi.org/10.3390/app14135570 - 26 Jun 2024
Viewed by 1123
Abstract
The low-speed turning maneuverability of vehicles is closely related to a well-known offtracking phenomenon which occurs when the rear wheels of a turning vehicle deviate towards the inside of a horizontal curve. Although numerous mathematical models and computer programs for vehicle swept path [...] Read more.
The low-speed turning maneuverability of vehicles is closely related to a well-known offtracking phenomenon which occurs when the rear wheels of a turning vehicle deviate towards the inside of a horizontal curve. Although numerous mathematical models and computer programs for vehicle swept path analysis have been developed in the past, only a few of them can calculate the maximum transient offtracking of a turning vehicle, yet with limited accuracy. The authors were motivated by this fact to find a new mathematical solution for maximum transient offtracking calculation of a single-unit vehicle when negotiating circular curves. In the first stage, a transcendental equation defining vehicle maximum transient offtracking position is derived and numerically solved by Python 3.10.12. In the second stage, the polynomial regression model predicting accurate numerical solutions of the transcendental equation with the desired level of accuracy was developed and tested. The new calculation method is simple enough to simply take the vehicle datum length, circular curve radii, and turn angle, while instantly producing the maximum transient offtracking value, without the need to draw any of the vehicle movement trajectories. Full article
(This article belongs to the Special Issue Innovations in Road Safety and Transportation)
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24 pages, 7688 KiB  
Article
Smartphone Sensors in Motion: Advancing Traffic Safety with Mobile Technology
by Ján Ondruš, Arnold Jančár, Marián Gogola, Peter Varga, Željko Šarić and Jacek Caban
Appl. Sci. 2024, 14(13), 5404; https://doi.org/10.3390/app14135404 - 21 Jun 2024
Viewed by 967
Abstract
This research investigates the feasibility of using smartphones as reliable instruments to measure vehicle deceleration under different conditions and compares their accuracy and reliability with traditional decelerometers. The research was conducted using a passenger vehicle (Audi A6 Avant) on different road surfaces—dry, wet, [...] Read more.
This research investigates the feasibility of using smartphones as reliable instruments to measure vehicle deceleration under different conditions and compares their accuracy and reliability with traditional decelerometers. The research was conducted using a passenger vehicle (Audi A6 Avant) on different road surfaces—dry, wet, and gravel—at several speed intervals (30, 50, 70, and 90 km/h). The vehicle was equipped with an XL Meter decelerometer and three different smartphones in different price ranges. Each device recorded deceleration data, which was then analyzed to evaluate accuracy and reliability. The findings show that while the smartphones show promising results on dry and gravel surfaces, their accuracy decreases at lower speeds and on wet surfaces due to the limitations of the sensors in detecting subtle deceleration values. The research also highlights that mid-range smartphones can perform comparably to higher-end models, suggesting that excessive investment in more expensive technology may not be necessary for scientific purposes. However, some differences in measurements are attributed to variations in device mounting and orientation sensitivity. In conclusion, this research supports the potential of integrating smartphone technology in vehicle testing for road safety, although it highlights critical limitations that need to be addressed for standardized use. Full article
(This article belongs to the Special Issue Innovations in Road Safety and Transportation)
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17 pages, 3615 KiB  
Article
Safety Impact Prediction of Redesigning National Roads Crossing Residential Areas: An Italian Case Study
by Maurizio Crispino, Kevin Camozzi, Misagh Ketabdari, Arianna Antoniazzi and Emanuele Toraldo
Appl. Sci. 2024, 14(12), 4984; https://doi.org/10.3390/app14124984 - 7 Jun 2024
Cited by 2 | Viewed by 660
Abstract
The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used [...] Read more.
The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the ‘with’ and ‘without’ scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention. Full article
(This article belongs to the Special Issue Innovations in Road Safety and Transportation)
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