A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersections.

The severity of right-turn crashes (or left-turn crashes for the roads in the US) at signalised intersections tends to be high because of the relatively high conflicting speeds and angle of impact. However, right-turn crash injury severity at signalised intersections was not sufficiently studied. In particular, the effects of signal control strategies on crash injury severity are not known.

A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration.

Crash risk models relying on total crash counts are limited in their ability to extract meaningful insights regarding the context of crashes and to identify effective remedial measures. In addition to the typical classification of collisions noted in the literature (e.g.

Leading pedestrian intervals - Yay or Nay? A Before-After evaluation of multiple conflict types using an enhanced Non-Stationary framework integrating quantile regression into Bayesian hierarchical extreme value analysis.

A pedestrian was estimated to be killed every 85 min and injured every 7 min on US roads in 2019. Targeted safety treatments are particularly required at urban intersections where pedestrians regularly conflict with turning vehicles. Leading Pedestrian Intervals (LPIs) are an innovative, low-cost treatment where the pedestrian and vehicle usage of the potential conflict area (a crosswalk) is staggered in time to give the pedestrians a head start of a few seconds and reduce the "element of surprise" for right-turning vehicles.

Influence of segmentation approaches on the before-after evaluation of engineering treatments: A hypothetical treatment approach.

The segmentation of highways is a fundamental step in estimating crash frequency models and conducting a before-after evaluation of engineering treatments, but the effects of segmentation approaches on the engineering treatment evaluations are not known very well. This study examined the effects of segmentation approaches on the before-after evaluation of engineering treatments. In particular, this study evaluated four segmentation approaches by applying the Empirical Bayes technique to a dataset for which the ground truth was known.

A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: An application of hierarchical crash frequency model.

Right-turn movements (equivalent to left turn movements for countries that drive on the right) at intersections are among the most complex driving maneuvers and require a high level of attention for turning across (potentially) oncoming traffic by accepting a safe gap. Not surprisingly, right-turn-involved crashes are one of the most frequent collision types at intersections (e.g.

Transferability of multivariate extreme value models for safety assessment by applying artificial intelligence-based video analytics.

Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set of external sites, can reduce their appeal for large-scale traffic safety evaluations. Therefore, this study investigates the transferability of multivariate peak-over threshold models for estimating crash frequency-by-severity.

A systematic mapping review of surrogate safety assessment using traffic conflict techniques.

Safety assessment of road sections and networks have historically relied on police-reported crash data. These data have several noteworthy and significant shortcomings, including under-reporting, subjectivism, post hoc assessment of crash causes and contributing factors, limited behavioural information, and omitted potential important crash-related factors resulting in an omitted variable bias. Moreover, crashes are relatively rare events and require long observation periods to justify expenditures.

Applying a joint model of crash count and crash severity to identify road segments with high risk of fatal and serious injury crashes.

Both crash count and severity are thought to quantify crash risk at defined transport network locations (e.g. intersections, a particulate section of highway, etc.

Understanding the discretionary lane-changing behaviour in the connected environment.

Discretionary lane-changing (DLC) is one of the complex driving manoeuvres that requires surrounding traffic information for efficient and safe manoeuvring. The connected environment not only provides such information but also increases situational awareness, which is useful for DLC decision-making. However, the literature is devoid of any concrete evidence of such impact of the connected environment on DLC decision-making.

A bivariate random effects spatial model of traffic fatalities and injuries across Provinces of Iran.

From 2005-2015, Iran has experienced a 41.3 % decrease in road fatalities and an 11.1 % increase in non-fatal injuries.

Incorporating behavioral variables into crash count prediction by severity: A multivariate multiple risk source approach.

The frequency and severity of traffic crashes have commonly been used as indicators of crash risk on transport networks. Comprehensive modeling of crash risk should account for both frequency and injury severity-capturing both the extent and intensity of transport risk for designing effective safety improvement programs. Previous research has revealed that crashes are correlated across severity categories because of the combined influence of risk factors, observed or unobserved.

Do Differences in Social Environments Explain Gender Differences in Recreational Walking across Neighbourhoods?

Within a city, gender differences in walking for recreation (WfR) vary significantly across neighbourhoods, although the reasons remain unknown. This cross-sectional study investigated the contribution of the social environment (SE) to explaining such variation, using 2009 data from the How Areas in Brisbane Influence healTh and AcTivity (HABITAT) study, including 7866 residents aged 42-67 years within 200 neighbourhoods in Brisbane, Australia (72.6% response rate).

Effects of globally obtained informative priors on bayesian safety performance functions developed for Australian crash data.

The precision and bias of Safety Performance Functions (SPFs) heavily rely on the data upon which they are estimated. When local (spatially and temporally representative) data are not sufficiently available, the estimated parameters in SPFs are likely to be biased and inefficient. Estimating SPFs using Bayesian inference may moderate the effects of local data insufficiency in that local data can be combined with prior information obtained from other parts of the world to incorporate additional evidence into the SPFs.

Physical activity-related health and economic benefits of building walkable neighbourhoods: a modelled comparison between brownfield and greenfield developments.

Background: A consensus is emerging in the literature that urban form can impact health by either facilitating or deterring physical activity (PA). However, there is a lack of evidence measuring population health and the economic benefits relating to alternative urban forms. We examined the issue of housing people within two distinct types of urban development forms: a medium-density brownfield development in an established area with existing amenities (e.

The potential for walkability to narrow neighbourhood socioeconomic inequalities in physical function: A case study of middle-aged to older adults in Brisbane, Australia.

Residents of disadvantaged neighbourhoods have poorer physical function than their advantaged counterparts, although the reasons for this remain largely unknown. We examined the moderating effects of walkability in the relationship between neighbourhood disadvantage and physical function using 2013 cross-sectional data from 5115 individuals aged 46-72 living in 200 neighbourhoods in Brisbane, Australia. The relationship between neighbourhood disadvantage and physical function differed by levels of walkability: positive associations as levels of walkability increased for those living in more disadvantaged neighbourhoods, and no difference for those living in more advantaged neighbourhoods.

Applying fractional split model to examine the effects of roadway geometric and traffic characteristics on speeding behavior.

Objective: The speed selection behavior of drivers has been reported to vary across driver demographics, psychological attributes, and vehicle-specific factors. In contrast, the effects of roadway geometric, traffic characteristics, and site-specific factors on speed selection are less well known. In addition, the relative degree of speeding has received little attention and thus remains relatively unexplored.

"Mate! I'm running 10 min late": An investigation into the self-regulation of mobile phone tasks while driving.

The adaptive behaviour of mobile phone distracted drivers has been a topic of much discussion in the recent literature, but the mechanisms of behavioural adaptation are still unclear. This study investigated the influence of driving demands, secondary task characteristics, and personal characteristics on behavioural adaptation of mobile phone distracted drivers. In particular, distracted drivers' self-regulation at strategic, tactical, and operational levels was investigated through a driving simulator experiment.

User satisfaction with train fares: A comparative analysis in five Australian cities.

In the public transport industry, travellers' perceived satisfaction is a key element in understanding their evaluation of, and loyalty to ridership. Despite its notable importance, studies of customer satisfaction are under-represented in the literature, and most previous studies are based on survey data collected from a single city only. This does not allow a comparison across different transport systems.

Should I Text or Call Here? A Situation-Based Analysis of Drivers' Perceived Likelihood of Engaging in Mobile Phone Multitasking.

This study investigated how situational characteristics typically encountered in the transport system influence drivers' perceived likelihood of engaging in mobile phone multitasking. The impacts of mobile phone tasks, perceived environmental complexity/risk, and drivers' individual differences were evaluated as relevant individual predictors within the behavioral adaptation framework. An innovative questionnaire, which includes randomized textual and visual scenarios, was administered to collect data from a sample of 447 drivers in South East Queensland-Australia (66% females; n = 296).

Risk factors of mobile phone use while driving in Queensland: Prevalence, attitudes, crash risk perception, and task-management strategies.

Distracted driving is one of the most significant human factor issues in transport safety. Mobile phone interactions while driving may involve a multitude of cognitive and physical resources that result in inferior driving performance and reduced safety margins. The current study investigates characteristics of usage, risk factors, compensatory strategies in use and characteristics of high-frequency offenders of mobile phone use while driving.

Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers.

The use of mobile phones while driving remains a major human factors issue in the transport system. A significant safety concern is that driving while distracted by a mobile phone potentially modifies the driving speed leading to conflicts with other road users and consequently increases crash risk. However, the lack of systematic knowledge of the mechanisms involved in speed adaptation of distracted drivers constrains the explanation and modelling of the extent of this phenomenon.

Self-regulation of driving speed among distracted drivers: An application of driver behavioral adaptation theory.

Objective: The adaptive behavior of mobile phone-distracted drivers has been a topic of much discussion in the recent literature. Both simulator and naturalistic studies suggest that distracted drivers generally select lower driving speeds; however, speed adaptation is not observed among all drivers, and the mechanisms of speed selection are not well understood. The aim of this research was to apply a driver behavioral adaptation model to investigate the speed adaptation of mobile phone-distracted drivers.

Neighborhood disadvantage, individual-level socioeconomic position and physical function: A cross-sectional multilevel analysis.

Introduction: Understanding associations between physical function and neighborhood disadvantage may provide insights into which interventions might best contribute to reducing socioeconomic inequalities in health. This study examines associations between neighborhood-disadvantage, individual-level socioeconomic position (SEP) and physical function from a multilevel perspective.

Methods: Data were obtained from the HABITAT multilevel longitudinal (2007-13) study of middle-aged adults, using data from the fourth wave (2013).

Associations between individual socioeconomic position, neighbourhood disadvantage and transport mode: baseline results from the HABITAT multilevel study.

Background: Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP), and usual transport mode.

Methods: This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia.

Impact of mobile phone use on car-following behaviour of young drivers.

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18-26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld.