1,721,164 research outputs found
Safety implications of higher levels of automated vehicles: a scoping review
No full textAutomated vehicles (AVs) promise to improve road safety, reduce traffic congestion and emissions, and enhance mobility. However, evidence regarding their safety benefits has not been systematically investigated and documented. In this study, we utilise a scoping review approach to investigate and synthesise the existing literature on higher levels of AVs’ safety implications. This aids future relevant studies by identifying the research gaps and reporting the methodological approaches used. The review focused not only on peer-reviewed articles but also on grey literature to provide a comprehensive overview of the current research state. In total, 5724 articles were identified, and 4167 records were screened after duplicates and dual publications removal, from which 27 were found eligible for review. Ultimately, 24 studies met all the inclusion criteria and were considered for the review. The reported evidence was focused on changes in road safety levels after the deployment of AVs in transport networks. The data was extracted and charted by one reviewer using tables to create a descriptive summary of the results and address the scoping review's questions and objectives. In general, the findings suggest that AVs hold the potential to improve the overall safety on roads, although the existing evidence is not mainly based on real data but assumptions regarding vehicles’ capabilities and behaviour. The limited number of studies and the fact that all of them were published or conducted after 2014 indicate that the research on AVs’ safety impacts is just emerging.Accepted Author ManuscriptTransport and Plannin
Application of surrogate safety measures in higher levels of automated vehicles simulation studies: A review of the state of the practice
No full textObjective: Surrogate safety measures (SSMs) are developed and applied as alternatives or complements of safety analyses mainly due to important road crash data availability and reliability limitations.
Automated vehicles (AVs) have recently emerged as a prominent solution to mitigate transport externalities and increase road traffic safety. Due to the novelty of the technology and the lack of real-world data, traffic simulation combined with SSMs is the most common approach
to quantify their impact. This study aims to provide an overview of the state of the practice and, more specifically, examine the applicability of applied SSMs on higher levels of AVs (HAVs).
Methods: The methodological approach consists of a comprehensive literature search, which aims to provide an overview of the applied SSMs, followed by a critical assessment of the findings.
Results: In total, 17 studies and 11 different SSMs were identified and reviewed. Findings suggest that available SSMs are suitable measures to appropriately estimate the relative safety performance of HAVs and indicate their potential implications due to their expected rule-based driving behavior. However, in some cases, it was noticed that they could not efficiently capture the technological capabilities of HAVs, e.g., shorter headways and faster reaction times, which may lead to false alarms.
Conclusions: Despite the available evidence, there are still significant gaps and certain limitations, as no comparisons between different measures exist, or the validity of the applied measures could not be assessed based on historical road crash data. This work aims to help researchers and practitioners choose the most appropriate SSMs to evaluate HAVs’ safety performance. Finally, several research gaps are identified, and recommendations for potential future research directions are presented
Proactive Approaches in Quantitative Micro- and Macroscopic Crash Analysis Focus on Model-Based Safety Evaluation of Traffic Policy Measures
No full textnot availabl
Proactive Approaches in Quantitative Micro- and Macroscopic Crash Analysis Focus on Model-Based Safety Evaluation of Traffic Policy Measures
No full textnot availabl
“Everything somewhere” or “something everywhere”: Examining the implications of automated vehicles’ deployment strategies
No full text“Everything somewhere” or “something everywhere” is the classic dilemma concerning the development and implementation of the future generation of vehicles, i.e., automated vehicles (AVs). Both strategies include diverse policy options that could significantly impact road networks’ planning, design, operation, and utilization. Until now, no significant research has been conducted concerning their implications. In this paper, we aim to examine how ready the current physical infrastructure is by identifying the requirements of each strategy and then applying them in a com-mon type of intersection. The study’s findings demonstrate that AVs’ performance can be affected by policy implementation decisions and adds further weight to the argument of AVs separation or no-separation from no-AVs traffic. Furthermore, the insignificant improvements in traffic performance imply the low readiness of the current road networks in urban areas to accommodate the new technology. This study contributes to determining that research on the readiness of the road infrastructure and the deployment of AVs in urban areas is inevitable. It also identifies that roads’ geometric design can dramatically affect AVs’ operation and the difficulties of implementing dedi-cated lanes in urban areas due to space availability.Transport and Plannin
Automated Vehicles: Contribution of Flexible Pavement Layers' Characteristics to Rutting Performance
No full textDesign and implementation of appropriate road infrastructure for automated driving technologies in the era of coexisting automated vehicles (AVs) and human-driving vehicles (HDVs) is one of the crucial issues among researchers and road practitioners in recent years. From the pavement structure point of view, it is necessary to investigate the pavement performance subjected to the various loading distribution scenarios induced by different lateral movement patterns of AVs. This study considers two potential wander modes (i.e., zero and uniform) for AVs in both segregated (i.e., lanes with 100% AVs) and integrated scenarios (i.e., shared lanes for AVs and HDVs). It is known that the pavement layers' thickness and material influence pavement performance. This study used a finite element method (FEM) to consider the AVs' loading distributions and simulate the rutting performance of a full-depth flexible pavement structure constructed by different layers' thicknesses and materials. The results of this study showed that the contribution of the layers' thickness and material depends on the implemented lane distribution scenario and the AVs' wander mode. For instance, improving the layers' material and increasing thickness could decrease the pavement rutting damage in segregated scenarios compared with the reference scenarios (i.e., only HDVs). However, in the case of integrated scenarios, this is only influential when using zero-wander mode for the AVs
Riding the Edge – Unveiling the Key Factors behind Injury Severity in Single-Vehicle Motorcycle Crashes
Full text linkMotorcyclists are among the most vulnerable road users, with single-vehicle crashes often resulting in severe or fatal injuries. Although some earlier studies focus on motorcyclists, crash statistics show significant space for motorcyclist safety improvement. This study examines the factors influencing crash severity by analysing police-reported crash data in the Republic of Croatia from 2017 to 2022, incorporating rider characteristics, roadway and environmental conditions, and crash circumstances. A data-driven approach was applied to assess the relative importance of these factors in determining single-vehicle motorcycle crash injury severity. This study utilised two different modelling approaches – multinomial logistic regression and random forest modelling to investigate the factors influencing crash severity. The results highlight that rider age, road type, speed conditions and alcohol consumption significantly influence crash outcomes. Older riders and crashes occurring on county and local roads were more likely to result in severe or fatal injuries. At the same time, inappropriate speed and collisions with roadside objects further increased the likelihood of fatal outcomes. The findings suggest the necessity of targeted interventions, including enhanced speed management, infrastructure improvements, stricter enforcement of alcohol regulations and advanced rider safety programs. To complement this research, future research should integrate more detailed behavioural and vehicle-specific data to refine injury severity predictions. This study provides valuable insights for policymakers and transportation safety professionals seeking to mitigate the severity of motorcycle crashes and enhance overall road safety
Pavement rutting performance analysis of automated vehicles: contribution of flexible pavement layers' characteristics
No full textDesigning and implementing appropriate pavement structures in the era of coexisting automated vehicles (AVs) and human-driven vehicles (HDVs) is a significant concern for researchers and road practitioners. This necessitates investigating the pavement performance subjected to the various loading distribution scenarios induced by different lateral movement patterns of AVs. It is known that the pavement layers’ thickness and material influence pavement performance. This study used a finite element method (FEM) to model AVs’ loading distributions and simulate the rutting performance of a full-depth flexible pavement structure constructed in different layers’ thicknesses and materials. The results revealed that the layers’ thickness and material contribution depend on the lane distribution scenario and the AVs’ wander mode. In some AV scenarios, improving the layers’ material and increasing the thickness could help reduce the pavement rutting damage compared to HDV scenarios, with the extent of this effect influenced by AVs’ wander mode.This work was supported by the Special Research Fund (BOF) of Hasselt University with the BOF number of ‘BOF19OWB26’
Impacts of load distribution and lane width on pavement rutting performance for automated vehicles
No full textOver the recent years, considerable attention has been drawn to intelligent driving technologies and particularly to automated vehicles (AVs). The deployment of AVs would provide the opportunity to have more control over the dynamics of the vehicle, including its lateral movement, which can affect the pavement’s long-term rutting performance. The controlled lateral movement of the AVs may also imply a reduced lane width. This paper evaluates the impacts of dedicating a reduced lane width to AVs on pavement rutting performance, considering two lateral movement modes for AVs; zero wander and uniform-wander. A finite element model was developed using ABAQUS software. The rutting simulation results of this study showed that the abrupt changes in the loading schemes of the zero- and uniform-wander modes cause considerable accumulated rutting in the edges of the loading areas. This is significantly greater than the total rutting induced by the human-driven vehicles (HDVs) following the normal-wander mode, which causes a compensated rutting behaviour by a gradual increase in loading time. Furthermore, the comparison between rutting depths in different lane widths reveals that when dedicating the narrower lane for AVs with a uniform-wander distribution, the pavement’s total rutting depth would remarkably increase compared to the wider lanes.This study was supported by the Special Research Fund (BOF) of Hasselt University with the BOF number of “BOF19OWB26”
Exploring the Factor Structure of a Modified Motorcyclist Behavior Questionnaire: Croatian Context
No full textRoad crashes, particularly those involving vulnerable road users, such as motorcyclists, are a major public concern worldwide, especially on rural roads. To understand the factors contributing to the heightened risk experienced by motorcyclists, a survey was conducted among motorcycle riders. The Motorcycle Rider Behavior Questionnaire (MRBQ), a widely used self-report instrument, was employed to gather insights into motorcyclists' perspectives, behaviors, and attitudes regarding road safety. This study focused on the factor structure of the MRBQ within the context of Croatia. Principal component analysis (PCA) with varimax rotation was performed to examine the underlying factors of motorcyclist behavior. Five distinct factors were identified: violations (e.g., speeding and reckless riding), errors (e.g., risky maneuvers and inattention), stunts (e.g., wheelie), safety equipment (e.g., use of protective gear), and substance use (e.g., riding under influence). These factors explained 40.44% of the variance among the analyzed items. These findings contribute to the understanding of motorcycle rider behavior patterns. Future research will explore the relationship between these factors and motorcyclists' involvement in risky situations and crashes.This study was supported by the Special Research Fund (BOF) of Hasselt University with the BOF number “BOF21BL03”. Special thanks to all motorcyclists who took the time to participate in this research
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