نشریه مهندسی ترافیک
پیاپی 57 (تابستان 1393)

Nowadays, according to the importance of safe transportation in permanent economic development, using new approaches which lead to improving the safety and quality of roads is vital. Many experts believe that intelligent transportation systems are the suitable solution to achieve this goal. One of the transportation system’s intelligence component is determination of the roads safe speed limits which directly affect the roads traffic volume and safety. In this paper the determination of safe speed limits and the effective indexes are discussed by introducing a heuristic approach for defining safe speed limits dynamically based on the roads conditions. This approach aims to reduce accidents caused by the drivers’ unawareness of the roads conditions or the drivers’ inexperience in determining safe speed. In this approach the safe speed is determined with considering the difference between the roads current and the ideal conditions. Finally, a numerical example is applied to describe the proposed approach.

This study try to introduce a model based on neural networks with high accuracy for predicting a model for accidents based on human factors. Most of previous researches of accidents focused on the roles of the road and the vehicles, but this article mainly searched about human factors’ roles in accidents. Designed model of this paper is based on drivers’ traffic violations as the most important part of human factors. For selecting the effective variables in designing the model, accidents have been chosen based on severity (property damage only (PDO), injury and fatal accidents) in a specific period. Finally, the optimum model was selected by evaluating the network parameters (R and Mean squared error) and was validated by new data not entering in the process of training the model. The results of the optimum network parameters demonstrate high accuracy of the neural network.

Congestion pricing is the popular demand management policies in metropolises to eliminate unnecessary travel or change mode choice from private vehicle to public transportation. The purpose of this paper is investigating the effects of disincentive congestion pricing and incentive improvement public transportation policies to mode choice and detecting important factors affecting the users, behaviors. Data collected from 251 questionnaires in the odd and even areas in Tehran and including of two parts of revealed and stated preference. Revealed preference data consist of the existingtransportation facilities and state preference data represents user-selected options in dealing with the new requirements of politics. The ρH index for combined NL model is 1.14 and indicating that the combined weight model has a better description of the data. The policy of reducing travel time compared to other demand management policies has more impact on the choice of users of public transport.

In this study, driving aggression measured for Iranian men and women and then the contribution of anger related factors were examined for explaining traffic violation. For this reasons, we administrated Driving Anger Scale (DAS) and Driving Anger Expression (DAX). We also examined the relation between driving experience, gender, number of tickets and number of accidents in last three years. A sample of 185 drivers having three years of experience of driving responded to 33 items of DAS and 18 items of DAX. The results indicate that differences between men and women driving aggressiveness are minimal. The results show that dimension of driving aggressiveness in Iran is higher than other countries such as Finland, Netherland. Amateur driver had more tendencies to show aggressive behaviors. No correlation had been found between number of accidents, tickets and aggressive driving. The results show that other factors like as driver›s characteristics influence driving aggression.

One of the defects of bus systems in Iran is that the lines are designed like subway systems and prevents cities to use bus line , s flexiblity. In this study, bus network of Qom would be redesigned by using inovative way. In this method the lines would be designed by combining lines and routes. Then new bus lines were modeled in TransCad software. Analysing of outputs shows that parametrs like attracting travelers, travel speeds had been enhanced and travel time decreased significantly.

One of the most significant factors in every accident is high speed of cars. Traffic calming is reduction of cars, speed and consequently decreasing severity of crashes. In this research, traffic calming is studied and some equations are examined for speed change prediction by collecting speed data of four sample areas. Paper›s focus is on extrusions and rumble strips. Equations are evaluated by using regression methods and result of four samples areas are compared with each other. At the end, outputs of models in speed reduction are presented.

All of modes of public transportation systems must provide safety and facilitate the movement of passengers. Furthermore the subsystems must locate in proper spaces to optimize the performance of whole system. Many parameters are investigated by experts for integrating public transportation system. In this stud, function of subsystems integration of public transportation are researched, especially the bus stations in terms of coverage and access of users. Weighting of the criteria and sub criteria is based on the combination of analytic hierarchy model and analyzing the data by using Geographic Information System. Finally, this paper is determined appropriate distribution of bus stations in the region 4, especially in important places.