Suchergebnisse

A quantitative risk analysis (QRA) regarding dangerous goods vehicles (DGVs) running through road tunnels was set up. Peak hourly traffic volumes (VHP), percentage of heavy goods vehicles (HGVs), and failure of the emergency ventilation system were investigated in order to assess their impact on the risk level. The risk associated with an alternative route running completely in the open air and passing through a highly populated urban area was also evaluated. The results in terms of social risk, as F/N curves, show an increased risk level with an increase the VHP, the percentage of HGVs, and a failure of the emergency ventilation system. The risk curves of the tunnel investigated were found to lie both above and below those of the alternative route running in the open air depending on the type of dangerous goods transported. In particular, risk was found to be greater in the tunnel for two fire scenarios (no explosion). In contrast, the risk level for the exposed population was found to be greater for the alternative route in three possible accident scenarios associated with explosions and toxic releases. Therefore, one should be wary before stating that for the transport of dangerous products an itinerary running completely in the open air might be used if the latter passes through a populated area. The QRA may help decisionmakers both to implement additional safety measures and to understand whether to allow, forbid, or limit circulation of DGVs.

Introduction/purpose: The paper presents a model for the selection of a route for the transport of dangerous goods using DEA (Data Envelopment Analysis) models and fuzzy logic systems. The presented model is used to define the risk on road sections during the transport of dangerous goods as well as to select the optimal route for the realization of the transport task. Methods: The model consists of two phases. The first phase includes the application of DEA models in which formed input and output models are connected in the output DEA final form which shows routes with a satisfactory level of traffic safety and at the same time eliminates routes with low traffic safety. The second phase involves the application of fuzzy logic systems, and as a way out of the fuzzy system, preference is given to one route. Route evaluation is based on six criteria, namely: route length, number of access points, AADT (annual average daily traffic), the number of traffic accidents with fatalities, the number of traffic accidents with the injured and the number of traffic accidents with material damage. When the values of the input criteria are entered, a calculation and evaluation is performed, and, as an exit from the fuzzy system, preference is given to one of the entered routes (the route with the lowest level of risk). The criteria used were defined on the basis of expert assessments. Results: A user program that represents decision support in traffic service. Conclusion: The user platform was created for the Matlab R2015a software package with the ability to be adapted to specific problems.

AbstractA quantitative risk analysis (QRA) concerning dangerous goods vehicles (DGVs), including also vehicles for the transport of liquid hydrogen (LH2TVs), running through unidirectional motorway tunnels was performed. An event tree was built, and a wide parametric analysis based on different geometric and traffic characteristics of tunnels was carried out. The effects of the annual average daily traffic (AADT) per lane, the tunnel length (L), the percentage both of heavy goods vehicles (HGVs) and DGVs (for a given 7% of LH2TVs) were investigated. The results in terms of social risk, as expressed by F/N curves and the expected value (EV), show an increased risk level with the presence of the hydrogen transported, and with certain F/N curves that might also lie above the acceptability limit. This means that additional safety measures should be implemented in order to reduce the risk level or that, alternatively, appropriate strategies of traffic control systems should be taken. A statistical modeling for developing a predictive method of the EV is also performed. The outcomes show that the regression coefficients have the signs expected. In particular, the EV increases with the tunnel length (L), the AADT, and the percentage both of HGVs and DGVs. However, the magnitude of estimated coefficients indicates that the expected value EV increases more with the traffic (AADT per lane, HVGs, or DGVs) than the tunnel length. The application of the approximate method might help the Tunnel Management Agencies (TMAs) in making quick decisions, at a preliminary stage, about temporarily allowing, forbidding or limiting the circulation of DGVs and/or LH2TVs through tunnels; and subsequently investigating in greater depth the potential hazards due to the transport of hydrogen in the worst cases individualized.