Child pedestrian injuries at tram and bus stops

Identifying the latent relationships between factors associated with traffic crashes through graphical models

Traffic safety field has been oriented toward finding the relationships between crash outcomes and predictor variables to understand crash phenomena and/or predict future crashes. In the literature, the main framework established for this purpose is based on constructing a modelling equation in which crash outcome (e.g., frequencies) is examined in relation to explanatory variables chosen based on the problem at hand. Despite the importance and success of this approach, there are two issues that are generally not discussed: 1) the latent relationships between factors associated with crashes are oftentimes not the focus of analysis or not observed; and 2) there are not many tools to make informed decisions on which variables might have an impact on the crash outcome and should be included in a safety model, particularly when observations are limited. To address these issues, this paper proposes the use of graphical models, namely a Markov random field (MRF) modelling, Bayesian network modelling, and a graphical XGBoost approach, to disclose relationship topologies of explanatory variables leading to fatal and incapacitating injury pedestrian crashes. The application of graph learning models in traffic safety has a high potential because they are not only useful to understand the mechanism behind the crash occurrence but also can assist in devising accurate and reliable prevention measures by identifying the true variable structure and essential factors jointly acting towards crash occurrence, similar to a pathological examination.

Smooth and safe tram journeys: tram driver perspectives and opportunities using a haptic master controller in a virtual reality environment

Tram drivers operate a master controller to control the acceleration and braking of the tram. Operation should ensure passenger comfort and safety through smooth tram motion and the avoidance of jerkiness that may cause passengers to fall in the carriage. This work investigates current driver practices and strategies for tram driving in normal operations through interviews and the capacity of a new haptic master controller to support drivers in achieving smooth and safe tram journeys. A haptic feedback algorithm based on viscosity was implemented on the master controller to provide drivers with feedback on the rate at which they were accelerating and braking the tram. This aspect was tested in a virtual tram within a simulated inner city virtual reality environment. Results indicate that the haptic master controller and coupled viscosity feedback algorithm did not increase smoothness of driving during the simulated experiences. Despite this, the drivers indicated a preference for the provision of further haptic information to support driving tasks and the overall journey safety and smoothness. Practitioner Summary: This research comprises two studies. The first investigates strategies currently used by drivers to operate a tram smoothly in order to elicit design requirements for a haptic tram master controller. The second study evaluates the impact of a novel haptic master controller on journey smoothness within a virtual environment.

Injuries Due to Wedging of Bicycle Wheels in On-road Tram Tracks

BACKGROUND

In cities with trams as public transportation, tram tracks are often on public roads, creating a shared road situation with other road participants like cyclists. Beside the risk of direct collisions, this situation can also lead to bicycle wheels getting wedged in tram tracks, causing cyclists to fall.

OBJECTIVES

The aim of this study was to gain more insight in the injury pattern of this trauma mechanism and to draw attention to the risks of the infrastructural situation with on-road tram tracks.

PATIENTS AND METHODS

A one-year, prospective, observational cohort study was conducted. All patients admitted after presentation to the emergency department of a level 1 trauma center, who got injured because their bicycle wheels got wedged in tram tracks, were included. Data were collected on patient demographics, type of injury and treatment.

RESULTS

Ten patients were included. Six were male. The mean age was 38 years. Six patients required surgery, mostly because of extremity injuries. Mean duration of admission was 4 days. Mean injury severity score was 13. One patient died as a result of the injuries sustained in the accident.

CONCLUSIONS

Tram tracks on public roads are potentially dangerous and can lead to serious injuries and even mortality amongst cyclist. Operative intervention is frequently needed.

Predicting cycling accident risk in Brussels: a spatial case-control approach

This paper aims at predicting cycling accident risk for an entire network and identifying how road infrastructure influences cycling safety in the Brussels-Capital Region (Belgium). A spatial Bayesian modelling approach is proposed using a binary dependent variable (accident, no accident at location i) constructed from a case-control strategy. Control sites are sampled along the 'bikeable' road network in function of the potential bicycle traffic transiting in each ward. Risk factors are limited to infrastructure, traffic and environmental characteristics. Results suggest that a high risk is statistically associated with the presence of on-road tram tracks, bridges without cycling facility, complex intersections, proximity to shopping centres or garages, and busy van and truck traffic. Cycle facilities built at intersections and parked vehicles located next to separated cycle facilities are also associated with an increased risk, whereas contraflow cycling is associated with a reduced risk. The cycling accident risk is far from being negligible in points where there is actually no reported cycling accident but where they are yet expected to occur. Hence, mapping predicted accident risks provides planners and policy makers with a useful tool for accurately locating places with a high potential risk even before accidents actually happen. This also provides comprehensible information for orienting cyclists to the safest routes in Brussels.

A joint-probability approach to crash prediction models

Many road safety researchers have used crash prediction models, such as Poisson and negative binomial regression models, to investigate the associations between crash occurrence and explanatory factors. Typically, they have attempted to separately model the crash frequencies of different severity levels. However, this method may suffer from serious correlations between the model estimates among different levels of crash severity. Despite efforts to improve the statistical fit of crash prediction models by modifying the data structure and model estimation method, little work has addressed the appropriate interpretation of the effects of explanatory factors on crash occurrence among different levels of crash severity. In this paper, a joint probability model is developed to integrate the predictions of both crash occurrence and crash severity into a single framework. For instance, the Markov chain Monte Carlo (MCMC) approach full Bayesian method is applied to estimate the effects of explanatory factors. As an illustration of the appropriateness of the proposed joint probability model, a case study is conducted on crash risk at signalized intersections in Hong Kong. The results of the case study indicate that the proposed model demonstrates a good statistical fit and provides an appropriate analysis of the influences of explanatory factors.

MDCT evaluation of injuries after tram accidents in pedestrians

Multidetector computed tomography (MDCT) is especially suited for emergency diagnostics in multiple trauma patients. The objectives of this study were to investigate the types and frequencies of injuries associated with tram accidents in pedestrians. Eighteen consecutive pedestrian patients with multiple traumas after tram accidents were evaluated with MDCT in our Level I Trauma Center. The mean age in our patient cohort was 36.9 years with a range from 14-92 years. There was a trend for accident events occurring more commonly during the winter months in middle-aged men, often under the influence of alcohol. Patients were divided into two groups with unilateral or complex injury patterns. In both groups, leading diagnoses were head (83.3%) and thorax injuries (66.6%). Abdominal injuries (44.4%) were less common and mainly found in the complex injuries group. The most serious injuries occurred in the complex injuries group when the victim was caught under or between tramcars. A wide range of injuries is associated with tram accidents in pedestrians, which can be classified into two main injury patterns, unilateral and complex. The life-limiting injuries in this setting involved the head with a mortality rate of 22.2% (four patients) in our cohort.

Incidence and characteristics of school bus crashes and injuries

OBJECTIVE

Studies of school bus crashes have focused on the biomechanics of catastrophic collisions, with very few examining crash incidence.

METHODS

Crashes in the state of Iowa were examined from January 2002 through December 2005. School bus crashes were identified through the Iowa Crash Data, a comprehensive database of all reported crashes in the State of Iowa. School bus mileage data were provided by the Iowa Department of Education. School bus crash, fatality, and injury rates were calculated and differences in crash and injury characteristics between school buses and other vehicles were examined.

RESULTS

The school bus crash, fatality and non-fatal injury rates were 320.7, 0.4 and 13.6 per 100 million bus miles travelled, respectively. School bus crash fatality and injury rates were 3.5 and 5.4 times lower than overall all vehicle crash fatality and injury rates, respectively. Drivers of other vehicles were more likely to have caused the crash than the bus driver (P<0.001).

CONCLUSIONS

School buses experience low crash rates, and the majority of crashes do not lead to injury. Buses are among the safest forms of road transportation, and efforts to educate drivers of other vehicles may help reduce crashes with buses.