International Journal of Transportation Engineering
Volume:9 Issue: 3, Winter 2022

One of the types of unsignalized intersections is roundabout, which usually has an advantage in terms of efficiency and safety in low to medium traffic conditions. In general, roundabouts are created as a solution to solve traffic problems at intersections, as well as to create ease and safety in weaving movements. As the volume of traffic increases and according to the dimensions and geometric design of the roundabout, its efficiency gradually decreases. Considering the issue of road traffic due to its globalization, it is necessary to develop a transportation network that can be efficient now and in the future. To this aim, proper design and analysis of various infrastructures are performed. One of these infrastructures created in the road network to increase the efficiency of intersections by reducing delay is roundabout. At present, a strong model for Iran's traffic conditions is not available to determine the performance of roundabouts; Therefore, in this research, an attempt has been made to prepare a model to determine the performance of roundabouts based on geometric characteristics. Among the available global models, it has been observed that the geometric characteristics of roundabouts play an important role in roundabout capacity. Therefore, concerning this issue as a basis, a model for roundabout entry capacity has been produced for heterogeneous traffic conditions in Iran. According to the research results, the entry capacity model, which is described by the variables 1- circulating flow, 2- central island diameter, and weaving width, is the best in terms of statistics has been the best model statistically. It was observed that with each meter increase in the diameter of the central island, the entry capacity of the roundabout increased by 6%. Also, with each meter of weaving width, the entry capacity has increased by 35%.

Nowadays, a significant part of goods and passengers are transported on suburban highways with mainly high-speed vehicles. Hence, these highways are very prone to accidents with different injuries. Due to the high fatality or severe physical/mental injury rates caused by car crashes, analyzing these accident-prone areas and identifying the factors affecting their occurrences is crucial. The specific objective of the study was to compare Chi-square Automatic Interaction Detector (CHAID), Classification and Regression Tree (CART), C4.5 and C5.0 decision tree data mining classification algorithms in building classification models for the fatality severity of 2355 fatal crash data records during 2007-2009 occurred in the roadways of 8 states in the USA. The results were evaluated using the accuracy metrics such as overall accuracy, kappa rate, precision, recall, and F-measure. The investigations confirmed that C5.0 had the best performance with the overall accuracy, and kappa rates of 94% and 92%, respectively. Additionally, classified fatality severity levels of the crashes were proposed for each algorithm to generate risk maps on the roads, to create potential accident risk spots. Decision tree models can be used for real-time data to find invariants in the tree over a period of time, which would be beneficial for policymakers.

One of the pivotal aspects traffic engineering comprehends is the study of the behavior of vehicle drivers in a traffic stream because it contributes much towards safe driving and the prevention of accidents on roads. It provides supportive enlightenments to Engineering, Enforcement, and Education (EEE) measures in identifying and developing solutions for problems relating to safety on roads in India. A study is on truck drivers plying their vehicles on two-lane undivided rural roads (National Highways). This study is to model and analyze their behavior Vis a Vis their experience under prevailing roadways and traffic conditions in India. We used the modified Manchester Driver Behavior Questionnaire (DBQ) with site-specific and local conditions on a group of truck drivers plying their vehicles on a two-lane undivided carriageway at NH-161, NH-16, NH-844, and NH-319 in India, to analyze the driving practice of commercial vehicle drivers for this study. We applied the concept of factor analysis and Analysis Of Variance (ANOVA) for modelling. Models demonstrated a strong relationship between driving experience Vis a Vis the number of violations. It showed that increased driving experience decreased the quantum of errors and lapses. The study revealed that drivers having driving experience of 2-5 years are more prone to traffic violations than others as such they require free or/and forced educative grooming for safety while driving under the EEE concept. Drivers, having less experience, showed fewer proclivities for committing mistakes than others as they, being new to driving, concentrate more on safe driving.

In order to study the mechanical properties of stone mastic asphalt mixtures (SMA) which are used in roads pavement, the current study added various proportion of shingles (bituminous tiles with mineral aggregate coating) roofing (RAS), that are commonly used in sloping roofing, to SMA mixture containing 0.3% of added fibers. The percentage of 1, 2, 4, and 6% shingle particle wastes were respectively added to the SMA mixture samples on which Marshall Stability, moisture damage, dynamic creep and fatigue tests were performed. The comparison of the results revealed an agreement between the results from samples containing up to 4% of waste and normal samples. In addition, the mentioned samples were capable of providing the restrictions determined in the regulations. Thus, based on the results, it is suggested to use shingle wastes according to the suggested percentage. However, increasing the number of wastes will lead to a downward trend due to the disruption of uniform texture in the mixture.

According to previous studies, 60% to 70% of the total rural road accidents would occur at the city entrance zones in Iran. Therefore, the characteristics of these zones could be considered as effective parameters in rural road accidents. In all prior studies, a 30-km buffer of the cities' entrances has been assumed as the border of the entrance zone. The 30-km buffer could not be considered as the boundary of the influenced area (BIA) of the cites´ entrance for all types of the roads and cities, merely based on aggregate rural road accidents´ data and a traditional definition of the city entrance zone. Determining the BIA for various rural roads with different characteristics using the modelling approach is the innovative aspect of this research. Furthermore, according to their specifications, implementing safety improvements in these areas, not only reduce the number of rural road accidents and fatalities, but also prevent the loss of road safety costs due to the economic problems of Iran. Thus, this study aimed to develop linear and logistic regression models to predict the BIA of rural roads in Iran. The results of this study indicated a fit index value of 0.737 for the linear regression model, and 0.379 and 0.346 for the ordered probit (OP) and multinomial logit (ML) models, respectively. The analysis of significant variables at 95% confidence level, revealed that the access points' density, and the length of adjacent land uses are the most significant variables affecting the BIA.

The present study investigates the Iranian drivers’ characteristics and tries to determine which factors can affect the drivers’ speed selection behavior. Therefore, drivers’ who choose speeds higher than the 85th percentile speed were examined, mainly because of the importance and effectiveness of higher speeds in crash occurrence in Iranian roads. For this purpose, a driving simulator was used to conduct the research and gathering the drivers’ selected speed while driving in scenarios. Six scenarios were used in the driving simulator based on the visibility conditions, and 70 participants were evaluated through the driving simulator. Using the t-test, speed data differences in six scenarios have proved. Results showed that age, education level, and gender affect drivers' perception of speed and speed selection. The age of the participants affected the selected speed negatively, which means that increases in the drivers' age can cause selecting speeds lower than the 85th percentile of speed. The higher education level in the present study was the PhD, and results indicated that participants who were categorized in the higher level of education tried to decrease their speed more than others. Also, results indicated that drivers who selected speeds higher than the 85th percentile of speed experienced at least one accident during the driving task in the driving simulator.

One of the new ways to improve the performance of roads is to make them smarter. To use intelligent transportation systems(ITS), various measures have been taken in different countries, and Iran has also been pushed in this direction. One of the problems regarding needs assessment, installation, and implementation of intelligent transportation systems is the priority of their purchase and implementation. This is especially evident in the main corridors of the country, which include several main roads. The prioritization of practical projects of intelligent transportation systems is considered in budget shortfall and is the basis for decision-making of those involved. To prioritize intelligent transportation systems projects, the selection of criteria and ranking techniques are very important. The purpose of this study is to prioritize ITS projects in one of the main corridors of the country (Tehran-Bandar Imam) The reason for choosing the corridor was its long length, the existence of different hierarchies of roads, as well as the needs of different intelligences. In this regard, the intelligent projects defined in this corridor have been prioritized using the criteria of execution time, benefit/cost, and ease of implementation, proposing a new index. The new prioritization index is designed according to the average of solutions. The results showed that among the proposed intelligent system projects, the use of versatile video surveillance cameras, new speed cameras, variable message boards, and automatic accident detection system, respectively, had a higher priority than other projects. The research results are used to select practical projects in budget constraints.