Methodology for the application of predictive method for road safety analysis in urban areas. The case study of Brescia

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Real-time evaluation and management of extreme traffic load risk on main road’s bridges

The risk induced by extreme traffic loads on bridges was rarely investigated and the existing methods require computationally expensive elaborations that are not compatible with a real time risk management. Traditional approaches to reduce risk suggested the optimisation of bridge maintenance plans. Conversely, approaches that real-time evaluate and manage the risk are missing. Moreover, the integration of emerging prediction models, such as Artificial Neural Networks, was never explored. This study fills the previous gaps by proposing a three-block methodology. It adopts Weight-In-Motion systems to collect site-traffic load data, formulates a probabilistic Risk Prediction Model to estimate frequency and severity of bridge failure events according to Eurocodes, and simulates an Intelligent Transportation System (ITS) architecture to apply real time management actions. The methodology was tested on 2.5M+ vehicles raw WIM data gathered along the ring road of Brescia (Italy). Bridge failure events resulted significantly more frequent than that prescribed by Eurocode, and factors of compliance with Traffic Code mass limits prescriptions had the more significant effect on risk predictions. The findings suggest a greater attention when permits for extremely overweighed vehicles are issued, as well as the implementation of enforcement strategies and ITS-based architectures for the real time risk management

Use of eye tracking device to evaluate the driver’s behaviour and the infrastructures quality in relation to road safety

Eye tracking allows to obtain important elements regarding the drivers’ behaviour during their driving activity, by employing a device that monitors the movements of the eye and therefore of the user's observation point. In this paper it will be explained how analysing the behaviour of the drivers through the eye movements permits to evaluate the infrastructures quality in terms of road safety. Driver behaviour analysis have been conducted in urban areas, examining the observation target (cars, pedestrians, road signs, distraction elements) in quantitative terms (time of fixing each singular target). In particular, roundabout intersections and rectilinear segment of urban arterials have been examined and the records related to seven drivers’ behaviour were collected, in order to have a significant statistical variability. Only young people has considered in this study. The analyses carried out have made it possible to assess how different types of infrastructure influence the behaviour of road users, in terms of safety performance given by their design. In particular, quantitative analyzes were carried out on driving times dedicated to observing attention rather than distraction targets. From a statistical point of view, the relationship that exists between the characteristics of the driver, weather conditions and infrastructure, with driving behavior (traveling speed and attention / inattention time) was analyzed by ANOVA method

Evaluating bus accident risks in public transport

Public transit buses may be considered a safer transportation mode as opposed to others (e.g., private cars). However, safety is a crucial issue regarding transit buses from the perspectives of operators and passengers due to the relevant implications it generates. Therefore, evaluating the accident risk on bus routes provides an opportunity to improve the safety performance of transit operators. Previous research identified patterns of bus accidents and shed light on understanding the effects of many factors regarding frequency and severity of bus accidents. However, no studies have investigated accident risks in bus transit, while considering frequency, severity and exposure factors in a single function. This paper proposes a new methodology for evaluating the accident risk for each transit bus route. At first, the methodology identifies the risk components in terms of frequency, severity and exposure factors that may affect bus accidents. Next, it integrates these terms, to build a risk bus accident function providing a ranking of safety performance for each route. The feasibility of this methodology is demonstrated in a real case study using 3,457 bus accidents 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 may be implemented in a road traffic safety management system for bus transit operators interested in the monitoring of safety performance, in the evaluation of the risk of accidents on routes, and in the certification process according to recent safety norms

Assessing the Risk of Bus Crashes in Transit Systems

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 recisely, 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

Macroscopic Models for Pedestrian Flows

International audienceIn this paper we present macroscopic models for pedestrian flows that recently appeared in the literature. The first one was proposed by Colombo, Rosini, 2005. In a 1D setting, this model properly describes the movements of pedestrians, the onset of panic and the dynamics of a panicking crowd. Furthermore, its assumptions were experimentally confirmed by an empirical study of a crowd crush, see Helbing, Johansson, Al-Abideen, 2007. Then, we consider a 2D model that aims at describing similar phenomena while taking care of more complex geometries. Numerical integrations show that some realistic features are capture