Road safety in low-income countries (LICs) remains a major concern. Given the expected increase traffic exposure due to relatively rapid motorisation of transport LICs, it is imperative better understand underlying mechanisms road safety. This turn will allow for planning cost-effective improvement programs timely manner. With general aim improving this paper discusses state knowledge and proposes number future research directions developed from literature reviews expert elicitation. Our...

The COVID-19 pandemic has been influencing travel behaviour in many urban areas around the world since beginning of 2020. As a consequence, bike-sharing schemes have affected-partly due to change demand and as well shift from public transit. This study estimates varying effect on London system (Santander Cycles) over period March-December We employed Bayesian second-order random walk time-series model account for temporal correlation data. compared observed number cycle hires hire time with...

The uptake of e-scooters as an alternative mode travel has risen sharply in recent years; however, their safety is less-understood compared to other modes travel. For the first time extant literature, we explore association between neighbourhood characteristics and e-scooter Greater London, UK. We found that, over study period, expected crash frequency was highest City followed by West End, then St. James's―both wards located borough Westminster central London. that frequencies increase with...

Traffic safety around schools is a major concern for policy makers and as such interventions are often targeted near schools. This paper shows the importance of accounting potential endogeneity proximity to school when attempting estimate its impact on traffic safety. In this research, we use Bayesian simultaneous econometric approach with heterogeneity in covariance disentangle true effect cyclist injury frequencies at signalised intersections an urban setting. We assess robustness...

In this paper, we review both the fundamentals and expansion of computational Bayesian econometrics statistics applied to transportation modeling problems in road safety analysis travel behavior. Whereas for analyzing accident risk networks there has been a significant increase application hierarchical Bayes methods, choice modeling, use estimators is rather scarce. We thus provide general discussion benefits using Markov chain Monte Carlo methods simulate answers point interval estimation...

Abstract Background Child pedestrian injury is a public health and equality challenge worldwide, including in high-income countries. However, child safety less-understood, especially over long time spans. The intent of this study to understand factors affecting England the period 2011–2020. Methods We conducted an area-level using Bayesian space-time interaction model association between number road crashes involving pedestrians English Local Authorities host socio-economic,...

Walking as a mode of travel alleviates congestion, pollution and concerns over physical fitness. However, safety might be barrier for some people to walking more often, so finding ways improve pedestrian is important. This paper conducts ward-level study Greater London such that factors which are associated with can identified interventions appropriately targeted. A wide range relating exposure, land use, built natural environment, socio-demographics, including markers deprivation were...

As the need to encourage modal shift from motorised vehicle use active modes becomes greater, it is important understand key factors influencing decision of how travel. This paper explores association between bicycle commuting and a range sociodemographic built natural environment characteristics across wards boroughs in Greater London, UK, with an aim identify which influence participation. We employed Bayesian multilevel heteroskedastic model heterogeneity variance, can address...

This study investigated the effects of prior assumptions in applications full Bayes methods road safety analysis. The effect choice was evaluated accuracy model parameters, hotspot identification, goodness fit, and a treatment effectiveness index before–after studies. Particular attention devoted to conditions with lack data, which were referenced as low-mean small-sample problem. In this research, informative, semi-informative, noninformative priors determined on basis past published A...

Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), is still major concern since crossing accidents are usually associated with devastating consequences. This paper investigates effect of various site attributes on outcomes using recent Canada wide data from 6-year period (2008–2013). The new sets allow adjusting previous models according latest...

A number of traffic safety studies have investigated temporal variations in road indicators such as crash frequency, confirming that exist. This paper examined whether speeding is more likely on weekend nights relative to all other times the day by directly comparing during weekends and weekdays. To this end, we analyzed a sample local streets, Montréal, for which speed data were collected automatically using analyzer sensors. We found that, interestingly, was less occur night hours, whereas...

This paper presents a new approach to address the problem of allocating federal resources and identifying upgrading projects for improving safety at-grade crossings in Canada. The proposed is unique two key aspects. First, risk-based network screening process adopted identify priority sites providing justifiable basis distributing total budget at regional level as well narrowing search space subject optimization step. Secondly, mathematical programming applied formalize resource allocation...