Assessing the Risk of Bus Crashes in Transit Systems

Abstract

Although public transport buses may be considered a safe transportation mode, bus safety is a crucial issue from the perspectives of operators, passengers and local authorities owing to the relevant implications it generates. Therefore, assessing the risk of crashes on bus routes may help improve the safety performance of transit operators. Much research has identified patterns of bus crashes to understand the effects of many factors on the frequency and the severity of them. Conversely, to the best of our knowledge, the research measuring the risk of crashes in bus transit networks is seldom faced. This paper adjusts existing methods to assess the safety on bus transit networks by the integration of safety factors, prediction models and risk methods. More precisely, first, the methodology identifies several safety factors as well as the exposure risk factors. Second, this methodology specifies the risk components in terms of frequency, severity and exposure factors that may affect bus crashes and models their relationships in a risk function. Third, this methodology computes the risk of crashes for each route and provides a ranking of safety performance. A real case study demonstrates the feasibility of this methodology using 3,457 bus crashes provided by a mid-sized Italian bus operator. This experiment shows that transit managers could adopt this methodology to perform an accurate safety analysis on each route. Moreover, this methodology could be implemented in a road traffic safety management system in order to evaluate the risk of crashes on routes, monitor the safety performance of each route and qualify each route according to recent safety norms.

A New Methodology for Accidents Analysis: The Case of the State Road 36 in Italy

“…The KPIs considered are the following: Road accident rate is evaluated first as it returns an assessment of the road accident occurrence against an exposure measure (i.e., the traffic flow) [14]. Social Cost Index are appointed as second, being an estimate of the economic damage suffered by the community as a result of road accidents [15]. It can be simply computed by multiplying the number of deaths, injuries and accidents by the related average cost.…”

A Straightforward Framework for Road Network Screening to Lombardy Region (Italy)

“…For instance, an adjusted accident cost rate index was computed in this framework, which disregards the non-linear relationship that exists between crash occurrence and traffic volume. Nevertheless, a bivariate (frequency and severity) risk crash model with all available road factors and exposure factors will be formulated and developed, to provide a more refined crash risk indicator as it has been done in public transport, e.g., [46][47][48]. Second, the overall structure and the path definition can be further improved to account for different data sources and attributes to be included in the evaluation.…”