Effect of eHMI-equipped automated vehicles on pedestrian crossing behavior and safety: A focus on blind spot scenarios.

Blind spot collisions are a critical and often overlooked threat to pedestrian safety, frequently resulting in severe injuries. This study investigates the impact of automated vehicles equipped with external human-machine interfaces (eHMIs) on pedestrian crossing behavior and safety, focusing on scenarios where AVs create mutual blind spots between pedestrians and adjacent traffic. A virtual reality experiment with 51 participants simulated crossing situations in front of yielding trucks with obstructed pedestrian visibility, featuring three eHMIs: 'Walk,' 'Don't Walk,' and 'Caution! Blind Spots'.

Estimating the differences in police and hospital records of people injured in traffic crashes in Dire Dawa City administration, Ethiopia.

The management of road safety relies on data from road traffic crashes to identify priorities, monitor trends and evaluate interventions. Both police and hospital records are important sources of information on crashes that result in injury; however, both are known to be incomplete, with the quality and completeness of data being lower in low- and middle-income countries. The aim of this study is to estimate the magnitude of the underreporting of crashes in Dire Dawa City, Ethiopia, as a case study that may be applicable elsewhere.

Influence of road safety policies on the long-term trends in fatal Crashes: A Gaussian Copula-based time series count model with an autoregressive moving average process.

Time series analysis plays a vital role in modeling historical crash trends and predicting the possible changes in future crash trends. In existing safety literature, earlier studies employed multiple approaches to model long-term crash risk profiles, such as integer-valued autoregressive Poisson regression model, integer-valued generalized autoregressive conditional heteroscedastic model, and generalized linear autoregressive and moving average models. However, these modeling frameworks often fail to fully capture several key properties of crash count data, especially negative serial correlation, and nonlinear dependence structures across temporal crash counts.

Hazard perception performance and psychological factors of distracted drivers: what are the associations?

Objective: Distracted driving is a major contributor to crashes involving younger drivers. A considerable amount of evidence emphasizes the link between driver distraction, poorer driving performance and increased crash risk. However, limited research has examined the effects of mobile phone use on hazard perception performance, especially younger drivers.

Shared intention and shared awareness for conditional automated driving: An online, randomized video experiment.

Objectives: In conditional automation for automated vehicles (AVs), drivers are tasked with remaining vigilant and ready to assume control should the system encounter a malfunction. However, little to no information is provided to the driver either about the AV's intended maneuvers or the AV's awareness of potential threats in the surrounding environment. To address this research gap, the present study proposes 2 human-machine interaction (HMI) concepts: Firstly, the shared intended pathway (SIP), which presents a forecast of the AV's intended maneuvers and, secondly, object recognition bounding boxes (ORBBs), which place transparent blue squares around other road users likely to contribute to a crash.

Predicting risky driving behaviours using the theory of planned behaviour: A meta-analysis.

The current meta-analysis explored the efficacy of the theory of planned behaviour (TPB) in predicting high-risk driving behaviours. Specifically, we examined speeding (in relation to exceeding the limit as well as speed compliance), driving under the influence, distracted driving, and seat belt use. We searched four electronic databases (i.

How do perceptions of procedural justice, police legitimacy, and legitimacy of laws influence intentions to drug drive?

Introduction: There is a need for improved drug driving enforcement to promote greater driver compliance with drug driving laws. In Australia, Roadside Drug Testing (RDT) suffers from operational challenges that undermine its effectiveness in reducing drug driving.

Objective: To identify potential improvements to RDT, this study investigated the extent to which drivers perceive RDT to be procedurally just and that the policing of drug driving and the associated laws are legitimate.

Understanding nonuse of mandatory e-scooter helmets.

Objectives: Head injuries resulting from e-scooter use have led to calls for helmet use to be promoted or mandatory. Helmet use is mandatory for e-scooters in Australia but observational studies have reported significant levels of nonuse, particularly by riders of shared e-scooters. The aim of this study is to understand whether nonuse in the mandatory context is a consistent behavior for an individual or is situationally-influenced, and what are the factors associated with nonuse.

Are train horns improving road safety? Road users' perspective.

Train horns are used as a control at railway level crossing for safety. Despite their wide use, limited information exists on their actual safety benefits. This study used focus groups with road users to understand their perceptions of the usefulness of train horns.

Passing distance, speed and perceived risks to the cyclist and driver in passing events.

Introduction: Up to 38% of crashes between motor vehicles and cyclists involve overtaking and close passes, contributing to a fear of cycling for both current and potential riders. Consequently, most research has focused on the cyclist's perceptions of risk in passing events; but the driver's perceptions may be more influential determinants of passing distances and thus, objective crash risk.

Method: In an online cross-sectional survey, participants viewed 24 video clips of naturalistic passing events (external view akin to being a following driver) on urban roads in Queensland, Australia and judged distance and safety for both the portrayed cyclist and the passing driver.

Clearing the way for participatory data stewardship in artificial intelligence development: a mixed methods approach.

Participatory data stewardship (PDS) empowers individuals to shape and govern their data via responsible collection and use. As artificial intelligence (AI) requires massive amounts of data, research must assess what factors predict consumers' willingness to provide their data to AI. This mixed-methods study applied the extended Technology Acceptance Model (TAM) with additional predictors of trust and subjective norms.

Learning about crash causation from countermeasure evaluation: The example of the Queensland minimum passing distance rule.

Close passes by motor vehicles endanger both the safety and comfort of bicycle riders. Governments in many countries have introduced laws requiring drivers to maintain at least a minimum distance between their vehicle and the cyclist they are passing, despite relatively poor understanding of the causes of bicycle overtaking crashes at the time. Queensland was the first state in Australia to introduce such a law, with a two-year trial commencing in April 2014.

Exploring temporal instability effects on bicyclist injury severities determinants for intersection and non-intersection-related crashes.

Cycling is a sustainable and healthy mode of transportation with direct links to reducing traffic congestion, lowering greenhouse gas emissions, and improving air quality. However, from a safety perspective, bicyclists represent a risky road user group with a higher likelihood of sustaining severe injuries when involved in vehicle crashes. With various determinants known to affect bicyclist injury severity and vary across locations, this study investigates the factors affecting bicyclist injury severity and temporal instability, considering the location of crashes.

The 'invisible gorilla' during pedestrian-AV interaction: Effects of secondary tasks on pedestrians' reaction to eHMIs.

In road traffic, mental overload often leads to a failure to notice new and distinctive stimuli. Such phenomenon is known as 'inattentional blindness'. Safe and efficient interaction between automated vehicles (AVs) and pedestrians is expected to rely heavily on external human-machine interfaces (eHMIs), a tool AVs are equipped with to communicate their intentions to pedestrians.

Recovery of driving skills after endoscopy under propofol sedation: a prospective pilot study to assess the driving skills after endoscopic sedation using driving simulation.

Background: Patients are recommended not to drive for at least the first 24 h after endoscopy with propofol sedation. However, the evidence underlying these recommendations is scarce. We hypothesized that after endoscopic procedures performed under propofol sedation, the subject's driving ability was restored in less than 24 h.

Identifying foci for safety messages targeting child injury from driving quad bikes: A critical beliefs analysis of parental beliefs in Australia.

Introduction: In Australia, between 2017-2021, 16% of quad bike fatalities involved children. Trauma statistics highlight that public awareness of the risks associated with children driving quads is required. Consistent with the Step approach to Message Design and Testing (SatMDT) and, in particular, Steps 1 and 2, this study sought to identify critical beliefs influencing parental intentions to allow their children to drive a quad bike and develop message content.

Examining the performance of engineering treatment evaluation methodologies using the hypothetical treatment and actual treatment settings.

The selection of treatment evaluation methodology is paramount in determining reliable crash modification factors (CMFs) for engineering treatments. A lack of ground truth makes it cumbersome to examine the performance of treatment evaluation methodologies. In addition, a sound methodological framework is critical for evaluating the performances of treatment evaluation methodologies.

Sharing roads with automated vehicles: A questionnaire investigation from drivers', cyclists' and pedestrians' perspectives.

Despite the promised benefits, the introduction of Automated Vehicles (AVs) on roads will be confronted by many challenges, including public readiness to use those vehicles and share the roads with them. The risk profile of road users is a key determinant of their safety on roads. However, the relation of such risk profiles to road users' perception of AVs is less known.

E-scooter riders and pedestrians: Attitudes and interactions in five countries.

Electric scooters (e-scooters) have become a popular phenomenon internationally; however, their use has raised concerns about pedestrian safety. This study describes the possible effects of the emergence of e-scooters on pedestrians. We focus on the interaction, conflicts, crashes, and attitudes between pedestrians and e-scooter riders and pedestrians' perceived safety in the presence of e-scooters.

"It is a different type of policing than in the bush": Police officers' perceptions of the differences in enforcement of the phone use while driving legislation in rural and urban areas.

Mobile phone use while driving continues to be a significant road safety concern, despite the severe legal countermeasures to reduce this behaviour. Phone use while driving-related crashes have been demonstrated to be an issue in rural areas, yet research into the impact of legal sanctions on phone use while driving has primarily focussed on urban areas. Therefore, this study aimed to investigate differences in enforcement of phone use while driving between rural and urban environments as reported by police officers.

Effects of design consistency on run-off-road crashes: An application of a Random Parameters Negative Binomial Lindley model.

Run-off-road crashes are one of the most common crash types, especially in rural roadway environments contributing significantly to fatalities and severe injuries. These crashes are complex and multi-dimensional events, and factors like road geometry, driver behaviour, traffic characteristics and roadside features contribute to their occurrence, separately or interactively. Sudden changes in road geometry, in particular, can influence driver behaviour, and therefore, in developing a micro-level crash risk model for run-off-road crashes, one of the challenges is incorporating the effects of driver behaviour (disaggregated information) that may arise from the variations in road geometry (aggregated information).

Leveraging cross-view geo-localization with ensemble learning and temporal awareness.

The Global Navigation Satellite System (GNSS) is unreliable in some situations. To mend the poor GNSS signal, an autonomous vehicle can self-localize by matching a ground image against a database of geotagged aerial images. However, this approach has challenges because of the dramatic differences in the viewpoint between aerial and ground views, harsh weather and lighting conditions, and the lack of orientation information in training and deployment environments.