186 results match your criteria: "Centre for Accident Research and Road Safety - Queensland (CARRS-Q)[Affiliation]"

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

Int J Inj Contr Saf Promot

December 2024

Addis Ababa Institute of Technology, School of Civil Engineering, Addis Ababa University, Addis Ababa, 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.

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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.

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

Traffic Inj Prev

December 2024

Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Queensland University of Technology (QUT), Brisbane, Queensland, Australia.

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.

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

Accid Anal Prev

December 2024

Centre for Accident Research and Road Safety - Queensland (CARRS-Q), School of Psychology, Faculty of Health, Queensland University of Technology, Australia.

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.

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Is it all about mobile phones? Exploring drivers' perceptions of government information and road rules on distracted driving.

Accid Anal Prev

December 2024

Department of Values, Technology, and Innovation, Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands.

Article Synopsis
  • Distracted driving is a global safety issue, and while governments aim to create comprehensive information and road rules, these efforts may not be effective in preventing distractions on the road.
  • A study involving 35 drivers in Queensland revealed that participants felt government information on distracted driving was lacking, poorly communicated, and overly focused on mobile phone use, leading to confusion around other potential distractions.
  • The findings indicate that government messaging can shape drivers' perceptions of risk, often downplaying certain distractions and potentially encouraging unsafe driving behaviors, highlighting the need for improved policies and communication from authorities.
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How do perceptions of procedural justice, police legitimacy, and legitimacy of laws influence intentions to drug drive?

J Safety Res

September 2024

School of Criminology and Criminal Justice and Griffith Criminology Institute, Griffith University, Messines Ridge Road, Mt Gravatt, QLD 4122, Australia. Electronic address:

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.

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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.

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

Accid Anal Prev

February 2024

Queensland University of Technology (QUT), Centre for Accident Research and Road Safety-Queensland (CARRS-Q), 130 Victoria Park Road, Kelvin Grove, QLD 4059, Australia. Electronic address:

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.

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Validation and interpretation of a multimodal drowsiness detection system using explainable machine learning.

Comput Methods Programs Biomed

January 2024

Centre for Accident Research and Road Safety - Queensland (CARRS-Q), Queensland University of Technology (QUT), Australia; Road Safety Research Collaboration, School of Law and Society, University of the Sunshine Coast (USC), Australia.

Article Synopsis
  • Drowsy driving poses significant safety risks, prompting research into detection systems; however, many existing studies neglect important factors like robustness and explainability of machine learning models.
  • This study aimed to improve drowsy driving detection by using multiple validation methods and by explaining how machine learning classifiers make decisions through techniques like SHAP analysis.
  • Results showed that using a participant-independent validation approach led to effective detection rates (70.3% sensitivity, 82.2% specificity) with the random forest classifier, highlighting key physiological features for identifying drowsiness.
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Exploring temporal instability effects on bicyclist injury severities determinants for intersection and non-intersection-related crashes.

Accid Anal Prev

January 2024

Centre for Accident Research and Road Safety-Queensland (CARRS-Q), and School of Civil and Environmental Engineering, Queensland University of Technology, Brisbane, Australia. Electronic address:

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.

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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.

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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.

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

J Safety Res

June 2023

Queensland University of Technology (QUT), Centre for Accident Research and Road Safety - Queensland (CARRS-Q), 130 Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia; Australian Centre for Health Services Innovation (AusHSI), Queensland University of Technology (QUT), Kelvin Grove, Queensland, 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.

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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.

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

Accid Anal Prev

August 2023

Queensland University of Technology (QUT), Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Kelvin Grove, Queensland 4059, Australia; Delft University of Technology, Safety and Security Science Section, Department of Values, Technology and Innovation, Faculty of Technology, Policy and Management, 2628BX Delft, Netherlands.

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.

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"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.

Accid Anal Prev

June 2023

Delft University of Technology, Faculty of Technology, Policy and Management, Section of Safety and Security Science, Jaffalaan 5, 2628 BX Delft, The Netherlands; Queensland University of Technology (QUT), Centre for Accident Research and Road Safety - Queensland (CARRS-Q), 130 Victoria Park Road, Kelvin Grove 4059, Australia. Electronic address:

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.

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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).

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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.

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Effectiveness of interventions for mobile phone distracted pedestrians: A systematic review.

J Safety Res

February 2023

Queensland University of Technology (QUT), Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Brisbane, Australia; Australian Road Research Board (ARRB), Brisbane, Australia.

Introduction: Mobile phones are used universally due to their versatility and easy-to-use features; this includes when users are walking and when crossing streets. At intersections, using a mobile phone is a secondary task that can distract from the primary task of scanning the road environment and ensuring it is safe to traverse. Such a distraction has been shown to increase risky pedestrian behavior compared to non-distracted behavior.

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What contributes to drug driving? An exploratory investigation into the influence of problematic substance use, roadside testing and alternative transport options.

Accid Anal Prev

May 2023

Delft University of Technology, Faculty of Technology, Policy and Management, Section of Safety and Security Science, Jaffalaan 5, 2628 BX Delft, The Netherlands. Electronic address:

Despite a strong reliance on enforcement approaches to prevent drug driving in Australia, this behaviour is still prevalent. The objective of this study was to investigate the influence of problematic drug use (i.e.

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Is distraction on the road associated with maladaptive mobile phone use? A systematic review.

Accid Anal Prev

March 2023

Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Queensland University of Technology (QUT), Brisbane, Australia; Delft University of Technology, Faculty of Technology, Policy and Management, Section of Safety and Security Science, Jaffalaan 5, 2628 BX Delft, The Netherlands.. Electronic address:

Maladaptive Mobile Phone Use (MMPU) (also known as Smartphone Addiction, Nomophobia, Fear of Missing Out, or Problematic Mobile Phone Use) is a growing mental health problem. However, the health and safety consequences of MMPU remain unexplored in many real-life contexts. A potential setting where MMPU may have some negative repercussions is on the road.

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Introduction: Unsignalized intersections are critical components of the road network where traffic collisions occur frequently.

Method: This study aims to design a Vehicle-to-Vehicle (V2V)- and Vehicle-to-Infrastructure (V2I)-based unsignalized intersection collision warning system (UICWS) to improve driver performance and enhance driver safety at unsignalized intersections. A multi-user driving simulator experiment was conducted with 48 participants divided into 24 pairs.

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Injury severity studies typically rely on police-reported crash data to examine risk factors associated with traffic injuries. The police crash database includes essential information on roadways, crashes and driver-vehicle characteristics but may not contain accurate and sufficient information on traffic injuries. Despite sizable efforts on injury severity modelling, very few studies have employed hospital records to classify injury severities accurately.

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Right-turn crashes (or left-turn crashes for the US or similar countries) represent over 40 % of signalized intersection crashes in Queensland, Australia. Protected right-turn phasings are a widely used countermeasure for right-turn crashes, but the research findings on their effects across different crash types and intersection types are not consistent. Methodologically, the Empirical Bayes and Full Bayes techniques are generally applied for before-after evaluations, but the inclusion of heterogeneous models within these techniques has not been considered much.

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