Transportation of Dangerous goods by road may have serious consequences in case of an accident occur. The consequences of a road accident of a heavy goods vehicle carrying dangerous goods may affect not only the truck driver but also the nearby population present. Routing selection is a complicated issue influenced from a number of parameters that may vary during the day, a week or a month. The purpose of the research is to develop a preliminary tool concerning the Transportation of Dangerous Goods which will prove whether a risk analysis using real time data (traffic flows, meteorological conditions, etc.) can offer higher level of safety to the society and the personnel involved in the transportation. The final goal is to enhance safety by making the Dangerous Goods (DG) Risk transportation totally digitalized as a risk management process with real time data acquisition and real time risk assessment through an online platform linked with Global Positioning System (GPS). During the research the risk analysis conducted taking into account all critical parameters for two selected routes. All the necessary data derived from annual statistical data and “simulated” real time data. Data collected concerned all the critical parameters and constraints in order to compare the results to be comparable. Risk quantification was implemented using the DG Quantitative Risk Assessment Model (QRAM) and was illustrated in terms of F/N curves. The results of this research were compared with the ones existed till today which are calculated based on annual statistical data for the above-mentioned factors. The results obtained were compared by means of Societal Risk expressed by Expected Value (EV) and showed that specific factors affect the final routing selection because of the calculated risk.
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