Pedestrian safety at signalized intersections: Modelling spatial effects of exposure, geometry and signalization on a large urban network

Modeling temporal correlation and heterogeneity in real-time conflict rates using Bayesian Tobit models for signalized intersections

The use of real-time traffic conflicts for safety studies provide more insight into how important dynamic signal cycle-related characteristics can affect intersection safety. However, such short-time window for data collection raises a critical issue that the observed conflicts are temporally correlated. As well, there is likely unobserved heterogeneity across different sites that exist in conflict data. The objective of this study is to develop real-time traffic conflict rates models simultaneously accommodating temporal correlation and unobserved heterogeneity across observations. Signal cycle level traffic data, including traffic conflicts, traffic and shock wave characteristics, collected from six signalized intersections were used. Three types of Tobit models: conventional Tobit model, temporal Tobit (T-Tobit) model, and temporal grouped random parameters (TGRP-Tobit) model were developed under full Bayesian framework. The results show that significant temporal correlations are found in T-Tobit models and TGRP-Tobit models, and the inclusion of temporal correlation considerably improves the goodness-of-fit of these Tobit models. The TGRP-Tobit models perform best with the lowest Deviance Information Criteria (DIC), indicating that accounting for the unobserved heterogeneity can further improve the model fit. The parameter estimates show that real-time traffic conflict rates are significantly associated with traffic volume, shock wave area, shock wave speed, queue length, and platoon ratio.

Traffic-Calming Measures and Road Traffic Collisions and Injuries: A Spatiotemporal Analysis

Traffic-calming measures (TCMs) are physical modifications of the road network aimed at making the roads safer. Although researchers have reported reductions in numbers of road crashes and injuries tied to the presence of TCMs, such studies have been criticized for their pre-/post- designs. In this study, we aimed to complement our knowledge of TCMs' effectiveness by assessing their impact using a longitudinal design. The implementation of 8 TCMs, including curb extensions and speed humps, was evaluated at the intersection and census tract levels in Montreal, Quebec, Canada, from 2012 to 2019. The primary outcome was fatal or serious collisions among all road users. Inference was performed using a Bayesian implementation of conditional Poisson regression in which random effects were used to account for the spatiotemporal variation in collisions. TCMs were generally implemented on local roads, although most collisions occurred on arterial roads. Overall, there was weak evidence that TCMs were associated with study outcomes. However, subgroup analyses of intersections on local roads suggested a reduction in collision rates due to TCMs (median incidence rate ratio, 0.31; 95% credible interval: 0.12, 0.86). To improve road safety, effective counterparts of TCMs on arterial roads must be identified and implemented.

Demographic and clinical profile of an inception cohort of road trauma survivors

BACKGROUND

Road trauma is a major public health concern, often resulting in reduced health-related quality of life and prolonged absenteeism from work even after so-called 'minor' injuries that do not result in hospitalization. This manuscript compares pre-injury health, sociodemographic characteristics and injury details between age, sex, and road user categories in a cohort of 1,480 road trauma survivors.

METHODS

This was a prospective observational inception cohort study of road trauma survivors recruited between July 2018 and March 2020 from three trauma centres in British Columbia, Canada. Participants were aged ≥ 16 years and arrived in a participating emergency department within 24 h of involvement in a motor vehicle collision. Data were collected from structured interviews and review of medical records.

RESULTS

The cohort of 1,480 road trauma survivors included 280 pedestrians, 174 cyclists, 118 motorcyclists, 683 motor vehicle drivers, and 225 passengers. Median age was 40 (IQR = [27, 57]) years; 680 (46%) were female. Males and younger patients were significantly more likely to report better pre-injury physical health. Motorcyclists and cyclists tended to report better physical health and less severe somatic symptoms, whereas pedestrians and motor vehicle drivers reported better mental health. Injury severity and hospital admission rates were higher in pedestrians and motorcyclists and lower in motorists. Upper and lower extremity injuries were most common in pedestrians, cyclists and motorcyclists, whereas neck injuries were most common in motor vehicle drivers and passengers.

CONCLUSIONS

In a large cohort of road trauma survivors, overall injury severity was low. Motorcyclists and pedestrians, but not cyclists, had more severe injuries than motorists. Extremity injuries were more common in vulnerable road users. Future research will investigate one-year recovery outcomes and identify risk factors for poor recovery.

One-year impact of a multicomponent, street-level design intervention in Mexico City on pedestrian crashes: a quasi-experimental study

BACKGROUND

Mexico City implemented the Pasos Seguros programme to prevent pedestrian injuries and deaths at dangerous road intersections, which included street-level design changes, such as visible pedestrian crossings, sidewalk widening, refuge islands, lane reductions, pedestrian signals and adjustment of traffic light timing at these intersections. Few studies in low and middle-income countries (LMICs) have evaluated the effect of such interventions on pedestrian safety.

AIM

Assess the effectiveness of the Pasos Seguros programme at reducing total, injury and fatal pedestrian-motor vehicle crashes.

METHODS

Two-group quasi-experimental design. Monthly pedestrian crashes were obtained from the road incident database from Mexico City's Citizen Contact Center. The programme's effectiveness was evaluated by comparing 12 months preintervention to 12 months postintervention implementation using a negative binomial regression with random intercept with a difference-in-difference estimation. A qualitative comparative analysis was used to find the configuration of intersection characteristics and programme components associated with a decrease in pedestrian crashes.

RESULTS

Total pedestrian crashes were reduced by 21% (RR 0.79; 95% CI 0.62 to 0.99) after implementation of Pasos Seguros programme. This reduction was observed for pedestrian injury crashes (RR 0.79; 95% CI 0.62 to 1.00) and for fatal crashes (RR 0.61; 95% CI 0.13 to 2.92) although not statistically significant for the latter. A decrease in pedestrian crashes was found at the most complex intersections where more of the programme components was implemented.

CONCLUSION

The Pasos Seguros programme successfully decreased total and injury pedestrian crashes. Similar interventions may improve walking safety in other LMIC cities.

Turning Movement Count Data Integration Methods for Intersection Analysis and Traffic Signal Design

Traffic simulation is widely used for modeling, planning, and analyzing different strategies for traffic control and road development in a cost-efficient manner. In order to perform an intersection simulation, random vehicle trip data are typically applied to an intersection network, making them unrealistic. In this paper, we address this issue by presenting two different methods of incorporating actual turning movement count (TMC) data and comparing their similarity for intersection simulation and analysis. The TMC of three intersections in Las Vegas are estimated separately for one hour using a developed vision-based tracking system and they are incorporated into Simulation of Urban MObility (SUMO) for estimating traffic measurements and traffic signal design. t-tests with a 95% confidence interval on the simulation variables demonstrate the importance of using a route-based creation method which injects vehicles into a simulation environment based on the frame-level departure time. The intersection analyses and comparisons are performed based on estimated traffic measurements such as travel time, density, lane density, occupancy, and normalized waiting time. Since the critical edge of each intersection network is identified based on a higher normalized waiting time, new traffic signal designs are suggested based on the actual critical turning movements and improvements in vehicle travel time are achieved to better accommodate the actual traffic demand.

Modelling bus-pedestrian crash severity in the state of Victoria, Australia

Understanding the relationship between bus-pedestrian crash severity and factors contributing to such crashes is important. However, there exists a dearth of research on the factors affecting bus-pedestrian crash severity. This study aims to fulfil this gap by investigating the factors affecting the severity of pedestrian injuries. A data set of bus-pedestrian crashes in the State of Victoria, Australia was analysed over the period of 2006 - 2019. Through the results of association rule discovery method, the factors that increase the risk of pedestrian fatality are darkness, pedestrian walking on carriageway with traffic, intersections, high speed zone, old pedestrian, young bus driver and weekend holidays. Furthermore, co-occurrence of factors that increase the risk of a pedestrian fatality were extracted. To reduce the injuries of bus-pedestrian crashes, we recommend improving the light conditions, reducing the jaywalking behaviour of pedestrians, implementing speed bumps in high speed zones and installing pedestrian detection systems on buses.13 years of bus-pedestrian crashes in Victoria, Australia was analyzed.Association rules discovery was used for modeling pedestrian fatality.Darkness, pedestrian movement, zone speed and age effect the rate of fatality.Pattern of pedestrian fatality in collision with bus was extracted.

Towards activity-based exposure measures in spatial analysis of pedestrian-motor vehicle crashes

BACKGROUND

Although numerous efforts have been devoted to exploring the effects of area-wide factors on the frequency of pedestrian crashes in neighborhoods over the past two decades, existing studies have largely failed to provide a full picture of the factors that contribute to the incidence of zonal pedestrian crashes, due to the unavailability of reliable exposure data and use of less sound analytical methods.

METHODS

Based on a crowdsourced dataset in Hong Kong, we first proposed a procedure to extract pedestrian trajectories from travel-diary survey data. We then aggregated these data to 209 neighborhoods and developed a Bayesian spatially varying coefficients model to investigate the spatially non-stationary relationships between the number of pedestrian-motor vehicle (PMV) crashes and related risk factors. To dissect the role of pedestrian exposure, the estimated coefficients of models with population, walking trips, walking time, and walking distance as the measure of pedestrian exposure were presented and compared.

RESULTS

Our results indicated substantial inconsistencies in the effects of several risk factors between the models of population and activity-based exposure measures. The model using walking trips as the measure of pedestrian exposure had the best goodness-of-fit. We also provided new insights that in addition to the unstructured variability, heterogeneity in the effects of explanatory variables on the frequency of PMV crashes could also arise from the spatially correlated effects. After adjusting for vehicle volume and pedestrian activity, road density, intersection density, bus stop density, and the number of parking lots were found to be positively associated with PMV crash frequency, whereas the percentage of motorways and median monthly income had negative associations with the risk of PMV crashes.

CONCLUSIONS

The use of population or population density as a surrogate for pedestrian exposure when modeling the frequency of zonal pedestrian crashes is expected to produce biased estimations and invalid inferences. Spatial heterogeneity should also not be negligible when modeling pedestrian crashes involving contiguous spatial units.