International Journal of Transportation Engineering
Volume:11 Issue: 3, Winter 2024

High rate of fatalities in road transportation has raised a world-wide effort to utilize appropriate strategies in order to reduce road accidents. In this regard professional drivers are of great concern due to their large size vehicles and high rate of passenger occupancy. Additionally, comparing to other users of network, planning for behavioral change among them is much more achievable due to their organizational and hence occupational dependency. This research proposes a validated questionnaire in order to measure the dangerous behavior of professional drivers of passenger cars, bus and trucks of intercity road network. Additionally, a structural equation model was developed that explored the causal relationship of dangerous behavior on accident. Further the model indicates that supervising drivers (through penalties) was able to mediate and indeed, reduce the effect of dangerous behavior on accidents previously experienced by respondents. In this study, Data collection was conducted among 603 drivers from 6th-21th September 2022, in Kermanshah, Iran. Results of this study suggests that behavioral change of drivers and adequate supervision on them reduce number of accidents on intercity road network.

Today, with the growing population and increasing demand for the use of private cars, managing the demand without the use of smart electronic devices, will be complicated and somewhat impossible. One of the methods of demand management is the use of intelligent traffic control systems and pricing accordingly. In this research, in addition to investigating the use of intelligent radio frequency identification systems (RFID), geographic information systems (GIS), and global positioning systems (GPS) in road transportation, a model has been presented to obtain appropriate values. The toll rate and pricing based on the car's useful presence time in the high-traffic area are introduced using smart systems and the use of the Laspeyres index economic relation is presented as an innovation in this research. From the results of this research, we can mention the reduction of vehicle density in the region, improvement of vehicle control in the city, and encouraging people to use the public transportation system.

As policymakers suggest using Transportation Demand Management (TDM) strategies, understanding the roots of the differences between the predicted and actual results of these policies' implementation is an area of interest for research. Among diverse reasons studies identify for this gap, this study focuses on model capabilities, using copula-based joint models for modal shift and mode choice. The study offered a hypothetical bundle of TDM strategies to 577 commuters who regularly drove to their workplaces during peak hours. Their stated mode choices were gathered. Thereupon, two successive steps were captured from their decision-making process: first, the decision to give up driving or not, and second, the substitute chosen mode if leaving driving was adopted. The joint effect of changing/not changing the travel mode from a private car and picking an alternative while facing a package of TDM strategies was tested with the copula approach. A binary logit is used to model the mode change decision, and the mode choice is modelled using a multinomial logit. Finally, among several copula functions, Frank Copula with the highest maximum likelihood estimation, and the positive value of dependency parameter, with an adjusted ρ2 of 0.158 was chosen as the best model. The findings of this study highlight the importance of considering people's previous mode decisions while trying to increase transit and decrease private use with TDM policies, which was not addressed in the literature using a dependent joint structure.

Annually, traffic problems ranging from congestion, air and noise pollution, abundant accidents, unacceptable increases in travel time, and various types of damages are the advance of most countries, especially in developing countries. Environmental pollution, casualty, and financial costs, as well as accidents, increased fuel consumption, the extent of resources allocated to build the network, and the huge cost of construction of various transport systems, as well as other side costs, destroy large amounts of human and economic resources in the country. It becomes. Therefore, the prediction of traffic for a pre-construction route as well as analyzing and estimating the capacity and prediction of future demand, due to the expansion and improvement of the network and preventing the creation of problems developed from increasing demand and lack of facilities, and can have problems The existing network minimizes the country's roads. Functional criteria are determined by defining the concept of level-of-service (LOS). In this research, the analysis of highway capacity was obtained using the data from the Shahid Sadr class-bridge in Tehran, based on the 415, HCM2016 regulations and headway methods, and then the results were compared using Synchro and Aimsun software.

This paper presents an approach for the optimization of horizontal road alignment with a focus on parameters affecting its cost and lifespan. The study area is the Bandar-e Anzali 16Km bypass highway, situated in north Iran, which holds significant economic, cultural, and environmental importance. The goal is to find the efficient and cost-effective alignment that adheres to design standards. The proposed methodology employs a multi-objective optimization technique using genetic algorithms in MATLAB. Various cost parameters, safety indicators, and environmental constraints are considered as decision variables to formulate the target performance. The genetic algorithm efficiently explores the design space, providing optimal solutions that fulfill all requirements and constraints. The output model ensures a balanced and practical approach to road design. The route design data was collected and the important variables affecting the route design were determined. Then, the optimal balance was evaluated using the genetic algorithms method. After analyzing the generated data, we propose the optimal horizontal alignment as the final recommended option, with four horizontal arcs and a length of 14.99km. The results demonstrate the effectiveness of the genetic algorithm-based method in achieving an optimal alignment for the Bandar-e Anzali bypass highway. The proposed solution reduces road construction costs and enhances safety while considering environmental impacts. This study highlights the importance of considering multiple parameters and utilizing advanced optimization techniques to achieve sustainable and cost-effective road designs. The proposed approach provides decision-makers with valuable tools to explore a wide range of design options and select the favorable alignment for construction.

Bitumen and asphalt mixture, cellulose fibers have attracted more attention of researchers due to their lower price and availability; the purpose of this research is to investigate the possibility of using cheap waste materials from paper factories to replace expensive modifiers, which can increase the life of asphalt pavement and reduce the need for its frequent repairs . In this research, the physical properties of the bitumen modified with cellulose fibers and black liquor have been investigated. The results showed that the increase in stiffness of the bitumen containing cellulose micro fibers and liquor. The increase in bitumen stiffness has decreased the degree of penetration and increased the softening point in the modified bitumen. The viscosity of the modified bitumen also increased with increasing stiffness. The results also showed the improvement of the high-temperature performance  of all the samples modified with cellulose micro fibers and liquor. However, the improvement of the low temperature of the modified bitumen is limited to the use of 4 to 6% cellulose microfibers. Increasing the resistance to rutting of the modified bitumen showed the positive effect of using cellulose micro-fibers in order to modify the properties of the base bitumen; Therefore, by using the wastes of paper factories, it is possible to achieve favorable results in reducing the common failures of asphalt pavements, including rutting at high temperature and cracking at low temperature, and reducing the costs of modifying bitumen and asphalt mixtures.