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Showing 3 results for Road Safety

Mahmoud Saffarzadeh, Maghsoud Pooryari,
Volume 3, Issue 2 (6-2005)

This paper specifies the relationship among various factors contributing to road accidents including geometrical design characteristics, environmental and traffic specifications, by multiple regression analysis. The main objective of this paper is identification of problems associated with the safety issue of road networks by application of accident prediction models. Data from previous accidents were used to develop the models. Results of this study showed that the rate of road accidents is to a large extent dependent on the rate of traffic volume. Type of road and land-use are other important factors influencing the number and intensity of accidents. The mountainous roads in this respect require special attention regarding their safety factors. The quantitative rate of road safety upgrading has also been specified by adding traffic lanes in road networks.
M. Effati, M. A. Rajabi, F. Samadzadegan, Sh. Shabani,
Volume 12, Issue 3 (9-2014)

Road transportation by way of automobiles is a very convenient means of transportation. Today, the most detrimental consequence of developing transportation systems in a country is traffic accident that places a huge financial burden on society. This paper investigates the role of information systems in transportation safety that leads to improved planning and operation of the transportation system through the application of new technologies. Current methods for identification of segments of roads with high potential of accident are based on statistical approaches. Since there are not accident records for newly built roads, these methods cannot be used for regional roads that are recently built. This paper presents a GIS based Neuro-Fuzzy modeling for identification of road hazardous zones. The results of proposed approach are compared with statistical methods. It is shown that this method is a cheaper but at the same time robust means of analyzing the level of hazard associated with each road segment under consideration, specially when data are uncertain and incomplete.
Gaetano Bosurgi, Nicola Bongiorno, Orazio Pellegrino,
Volume 14, Issue 5 (7-2016)

This study proposes a prediction model about the trajectories a vehicle, in isolated conditions, along a curve of a road. As we know, the road environment induces stress on users and, under certain conditions, influences driving behavior. It is of advantage then, to isolate and identify those conditions from among the numerous variables, which are actually the most significant so as to prevent or mitigate the occurrence of dangerous maneuvers. On the basis of an experiment performed using an instrumented vehicle, we collected a data base to which we subsequently applied Neuro-Fuzzy techniques for the selection of the most representative variables. We then used these data to prepare a nonlinear dynamic Hammerstein-Wiener’s model able to predict the track paths along curves. The findings were encouraging since almost all the results obtained from the validation checks proved satisfactory. This research is the first step in the identification of complex systems and could be applied in road safety measures and design of new and existing roads.

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