amirabbas rassafi

Autonomous vehicles promise a significant potential to maintain the mobility of various individuals even as their driving abilities decline. However, attitudes can act as a significant barrier to their acceptance, as shown for other technologies. This study examined how personality traits predict attitudes in a sample of 108 individuals aged 18 to 72. 21 personality questions identified introversion and extroversion, and 15 attitude questionnaire items were identified. Concerns about autonomous vehicles, eagerness to adopt autonomous vehicles, and willingness to relinquish driving control were assessed. Structural equation modeling shows that lack of concern has a significant impact coefficient of 0.576 (more introverted than extroverted) on the willingness to accept technology. Also, lack of concern has a significant impact coefficient of 0.486 (more extroverted than introverted) on the willingness to relinquish driving control. The eagerness to adopt autonomous vehicles on the willingness to relinquish driving control did not show a significant difference in intensity between extroverted and introverted samples. Furthermore, the mediating role of the eagerness to adopt autonomous vehicles in the relationship between lack of concern about autonomous vehicles and the willingness to relinquish driving control was significantly greater in introverted samples than in extroverted samples. These results indicate that in order to convince consumers to accept self-driving car technology, there is a need for various information dissemination campaigns based on a precise understanding of individuals' personalities.

The expansion of the internet and development in the business world have led to the emergence of new businesses, including taxi hailing. The purpose of this study is to examine these attributes (10 attributes are selected here) and prioritize them. In this study, unlike the traditional approach of dealing with discrete choice models, which focuses on choosing the best (most important) alternative among alternatives, the role of the worst (least important) alternative is also considered. The probit model is employed for modeling, and its results are compared with the logit model.The results of this research show that although the coefficients of the features in the two models are not the same, and the performance evaluation criteria show the superiority of the probit model over the logit model, but the overall result in the rating of the features is not different.The results of this research indicate that although the coefficients of attributes in the two modeling approaches are not the same, and evaluation criteria demonstrate the superior performance of the probit model over the logit model, the overall conclusions regarding the ranking of attributes do not differ between them.When dealing with taxi hailing services, issues related to security and confidence are more important. In other words, users pay the most attention to aspects that bring about a sense of security and mental satisfaction when choosing taxi hailing services.Furthermore, this study indicates that issues such as compliance with health cares and social distancing are among the least important attributes.

Waste disposal is a pressing issue for humanity and has the potential to become a major crisis in the future. One of the best-proposed solutions is to reuse usable materials found in waste, which requires proper waste separation. Experts suggest that separation at the source is crucial, making a functional Reverse Logistics System (RLS) essential. This research aims to provide a structure that can practically redesign the RLS.

Specialists believe that BlockChain Technology (driving force of emerging technologies), has many potential capabilities, which can create many favorable effects in industries. In this research, BlockChain Technology has been used to redesign the RLS with a futuristic approach. That, the mutual collaboration of citizens and the waste collection company is necessary.

A system designed based on this structure is forward-looking and backed by a very effective driving force technology, capable of implementing any policy to increase the separation of waste at source and concluding smart-contracts. It is flexible against sudden increase or decrease in supply without causing audio and visual pollution in traditional systems. Additionally, it is very transparent, safe, and practical. With the proper allocation of the fleet, it can collect all segregated waste.

In this system, with a futuristic approach, waste segregation at the source increases significantly. Resource usage is reduced. The waste disposal problem is being managed. A circular economy is formed. The comfort of citizens increases. The damage to the environment is much less. And action has been taken to transform into smart cities.

One of the most important problems of urbanization is caused by the types of intra-city movement. Air pollution, traffic, sound pollution and mental and physical discomfort are some of the unfortunate consequences in this field. In this research, the factors influencing the decision-making of the citizens of Qazvin city in choosing a sustainable mode of transportation have been studied. Then, by using the discrete choice test method, people's decision to choose one of the sustainable transportation methods has been questioned through the questionnaire of the factors affecting citizens' trips with sustainable transportation methods. Safety was recognized as the most important factor for citizens. First, the results of the model in terms of their significance and then the final effects of each of the methods in the mentioned scenarios have been examined and the results indicate that 47% of people tend to choose a shared car, 24% tend to choose a bus, 19% tend to choose a bicycle and 10% tend to choose a walking method. Also, the willingness to pay has been calculated to improve each of the factors in this research, and it can be argued that parking and safety have a value of 0.065 and 0.06 respectively for people compared to the cost and travel time. It is more important.

The rapid growth of urbanization and the global population have resulted in climate change, air contamination, and various human health problems. Thus, estimating air pollution indices has become important to environmental science studies. With relevant data increasingly available, machine learning frameworks have been proposed as a particularly useful method to predict air pollution. Based on four years of Tehran’s neighborhood air pollution data analysis, this paper proposes three machine learning approaches to predict NO2 and CO concentration: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory Networks (LSTM), and Multiple Linear Regression (MLR). This paper compared the ability of the ARIMA, LSTM, and MLR machine learning methods to forecast the daily concentrations of NO2 and CO at Punak air quality monitoring station, from 2017 to 2020. By applying four performance measurements, the ARIMA model displays the worst performance among the three models in all datasets with RMSE values of 47.39 and 1.29, and 0.012 and 0.01 for NO2 and CO respectively. The LSTM and MLR models achieve the best forecasting result with RMSE = 17.6 and 6.41, MAE = 10.59 and 4.33, = 0.458 and 0.46, and RRSE =1.06 and 1.10 for NO2 forecasting and RMSE = 0.42 and 0.32, MAE = 0.24 and 0.25, 0.96 and 0.98, and RRSE = 0.43 and 0.44 for CO forecasting.

Considering the effects of the spread of the Internet in everyday life and the tremendous changes it created in the emergence of new businesses and the marginalization of some traditional businesses, the necessity of studying in this field became more apparent. One of these new businesses is Taxi-hailing, which was quickly accepted by the public. In this study, ten attributes of Taxi-hailing have been examined, and people's preferences in choosing the attributes of this transportation mode have been asked through a questionnaire. One of the specific points of how this study is examined is that, unlike the traditional mode of dealing with discrete choice models, which focuses on choosing the best (most important) alternative among alternatives, the role of the worst (least important) alternative is also considered in this type of modeling. This scaling method is called best-worst, and among the three cases in this scaling method, case 1, which studies attributes, is used in this study. In each questionnaire of this study, 12 questions were asked for each person regarding the attributes of taxi hailing. In each question, according to the stated preference, the respondents were asked to select one of them as the best (most important) and choose one as the worst (least important). The results showed that among the attributes studied, security and reassurance are the most important in choosing this transportation mode, and the respondents chose accessibility in second place. Compliance with health issues and social distancing was ranked last as the least important attribute.

Understanding travel behavior is one of the most critical challenges in transportation planning. Planners can gain profound insights into travel behavior by exploring people’s perceptions and attitudes. Qualitative research as an independent approach or in a combination of a quantitative research can provide a deep understanding of people’s perceptions in transportation. This study used both qualitative and quantitative techniques to inspect citizens’ perceptions towards travel behavior. The interview results of the qualitative approach indicated that environmental concerns were mainly rooted in spiritual ethics. In addition, the respondents identified comfort, time, safety, and environmental concerns as the critical determinants in travel mode choice. The characteristics of individuals and transportation alternatives as well as environmental concerns were considered to affect mode choice in the quantitative study. The results, extracted from an Integrated Choice and Latent Variable (ICLV) model, showed that environmental concerns influenced people to choose public transportation. Furthermore, the findings indicated that young and middle-aged people preferred to use public transportation. Still, the preference was about quadruple for the middle-aged group.

The increasing demand for private cars and the unbalanced and dense growth of land-uses in the north of Tehran metropolis have caused fuel supply stations (gas stations) to always face the demand queue. On the other hand, the exorbitant price of land in these areas does not make the construction of a new location cost-effective. Demand management policies such as increasing the cost of using the facility are the possible solution to solve such problems. In this paper, the gas station users' data in the north of Tehran were collected using the stated preference method and analyzed using SPSS statistical analysis software to define the agent features and build agent-based modeling. The survey results were used to define the characteristics of factors and interactive rules in NetLogo simulation software. Then, the existence of a fast-passing line (with five different pricing scenarios) was simulated compared to the normal condition. The results showed that although the price increase scenarios (scenarios 4 and 5) are more welcome by relying on the statistically-based stated preference method, the agent-based simulation shows the popularity of cheap scenarios (scenarios 1 and 2) based on the interactive behavior of people are more valid. This indicates that the stated preference method's responses cannot be reassured in cases where interactive behaviors exist. Also, due to the imbalance of supply and demand due to the region's context, creating a tolled high-speed passing line is an effective solution to adjust the queue length and reduce waiting time.

Nowadays, improving public transport alone is not enough to solve urban traffic congestion, and a proper land-use planning scheme should accompany it. One of the approaches to solve this problem is mutual interaction between land-use and transportation called Transit-Oriented Development (TOD). Since Qazvin, as a historical city that was Iran's medieval capital in the Safavid dynasty (1555-1598), was selected as a pilot to implement TOD by the Ministry of Roads and Urban Development (MRUD), knowing the various aspects of this issue is essential. This paper presents the best-generated plan for land use modification around the concerned TOD stations adjacent to Qazvin city's historical areas. In this regard, a mathematical model with four objectives is developed to preserve historical context and signify optimized mixed-use using the Genetic Algorithm (GA) based on Python programming. First, maximize the density of commercial, residential, and mixed land use. Secondly, minimize the TOD skyline border to preserve the zone's historical identity. Thirdly, minimize land-use changes as much as possible to save the regions' context, and finally, increase the density of the land use allocation based on the TOD rules. In station 6, the most change related to residential decreased by about 30 percent, but at station 19, the most remarkable change related to commercial decreased about 10 percent.

The high-occupancy lanes are one of the urban traffic management strategies which attract many developing countries in recent years. High-occupancy Toll (HOT) lanes have been implemented in the United States and Europe, but never in developing countries. Thus, such a study is necessary in Iran. In general, the most trips are single-occupancy vehicle (SOV), which increases the number of vehicles in the streets. In this regard, for reducing SOV, especially in high-occupancy lanes, and increasing the capacity, HOT was used in developing countries. The main purpose of the present study was modeling and evaluating the factors influencing the mode choice in the presence of HOT lanes. Many studies evaluated the use of high-occupancy lanes, while in the present study the factor of entrance and departure to / from the field of study and calculating the saved time in different routes and converting it to monetary value to pay tolls were used for the first time. Due to the lack of these facilities in Iran, the data were collected using the stated preference method. Therefore, 1000 observations were investigated and a binary logit model was used to analyze the data. The results indicate that by increasing price (due to increasing saved time), individual willingness decreased for using high occupancy lanes. In addition, nearly 26% of drivers were willing to use HOT lanes when was free of charge, while the percentage of selecting HOT is almost zero when the price is high. Furthermore, in 180000 Rials, the selection percentage reached below 5%. Additionally, the results of the model showed that based on the entrance and departure to / from Chamran Highway, individuals desire to use HOT lanes. In addition, when individuals live in the shortest distance from the field of study, there is a 31% desire to use HOT lanes, while increasing to 25 km, tendency reaches almost zero percent. It is also worth noting that women were more inclined to use HOT lanes.

Studying pedestrian movement behavior is a necessary tool before the construction design in order to predict the social and collective behavior in different situations. Considering the complexity of human behavior using simulation is indeed a significant step for managers and designers in different fields including transportation planning. Agent-based modeling is one of the most popular techniques in this area. This paper aims to present a novel hierarchical agent-based simulation of pedestrian evacuation from a dynamic environment using reinforcement learning which is the closest to human behavior among the other machine learning algorithms. In the approach agents autonomously decide through a three-layer hierarchical model which includes goal, node, and cell selection layers. All the approach was originally coded in NetLogo software. The proposed model was successfully applied to simulate the pedestrian evacuation process from the platforms of the Shahed Metro station in Tehran during a destructive event. The results showed that practical capacity of the evacuation from the metro platform is 1.9 and 3.4 in the case of 2 and 4 exit doors respectively. The results from the approach can be used by building designers (non-structural design) and managers to optimize the quality of evacuation; also the proposed model has the potential of being used to analyze the evacuation time in the case of emergency (fire, earth-quake, terrorist attack and etc.)

The development of technology along with the development of facilities for modern and comfortable life brings some disadvantages as well as environmental problems, it consists of five categories of air pollution, water, soil, heat and noise pollution. In the meantime, the issue of noise pollution in cities is a global problem in most countries, In most developing countries, they are also striving for rapid industrial development to improve the countrychr('39')s economic and social conditions. Of course, In the absence of proper control, this growth along with improving the quality of life in these countries will lead to environmental pollution, including the most important of which is noise pollution, in the absence of proper control. Noise pollution is of particular importance due to the potential for physiological and psychological effects on humans. There has been significant growth in noise pollution from man-made sources over the past 100 years, which now doubles every 10 years. Therefore, evaluation of problem and functional planning to control noise pollution and its harmful effects is an essential issue for the community. Noise pollution that is different from other types of pollution due to its source and emission characteristics. Sources of noise pollution in urban areas can be divided into two groups: Fixed sources and moving sources. Fixed sources include: industrial, construction and demolition, commercial, local and recreational. Moving resources include ground and air transportation. In urban areas, the engine and exhaust system of cars, light trucks, buses and motorcycles is an important source of noise pollution, that have major environmental impacts. Traffic noise pollution is the most important source of environmental noise pollution in cities. The main objective of the paper is to find the relationships between noise and traffic characteristics, and also to examine the impact of each one separately, so that we can find out the importance of each variable in noise pollution we will find suitable solutions to reduce the noise pollution. In this study, which was carried out at one of the important intersections of Qazvin, data including equivalent sound level, the volume of vehicles by type, traffic light timing at picked up time, distance from picked up point to intersection center, number of beeps at the time of picked up which is heard, that data was estimated at 94 points, Points were located at 10 m distance on the edge of the street and If there was an open space, points were expanded, and there were two picked up for each point .The results of modeling showed that the most important variables affecting the sound equivalent level includes the volume of vehicles, especially heavy and semi-heavy vehicles (with the impacts of 0.025, 0.125, 0.526, 0.489 for cars, motors, semi-heavy vehicles and trucks, respectively,) the green time of the approach 1 and the number horns honked in this period (with the impact of 0.05 dB per second, and .08 dB per honk, respectively), are the variables that influence the equivalent sound level at this intersection.

Comparing and evaluating the road safety performance is desirable in trans-national levels, because each country can achieve a better and deeper understanding of its road safety status. In this study, a subset of multi-criteria decision-making methods, called the outranking methods, including PROMETHEE and ELECTRE methods was used to evaluate the road safety performance. In these methods, the Analytical Hierarchy Process method is used to obtain the weights of the indicators, which are used as input weights in the PROMETHEE and ELECTRE models. The methods were used for Iran and a set of developing countries in order to examine the situation in Iran compared to the others. Then, the results being compared with the number of road fatalities per hundred thousand people for these countries as the reference point. According to the results it was found that, among the five road safety pillars, the pillar of road safety management is the most important and the pillar of post-crash response is the least important one. Also, the lead agency sub-pillar is the highest importance in the road safety management pillar and the child restraint sub-pillar is the least importance in the safer road users pillar from expert's point of view. Among the 15 countries studied in this study, Poland found the highest rank and is known as the best-performing country. In between, Iran ranked 13th, reflecting Iran's relatively poor performance against other countries.

Expanding public transportation is not enough to solve the urban sprawl problem resulted from an auto-orientation perspective. So urban planning experts paid attention to integrated and coordinated planning of urban development with public transportation, which reached to sustainable urban development. The purpose of this study is to review the researches in transit-oriented development (TOD) and present practical solutions to implement TOD in Iran cities. In this paper, urban sprawl has been introduced, and three significant solutions (Smart Growth, New Urbanism, and Transit-Oriented Development) have been checked to prevent it. Then the researches in TOD allocation by various methods and modifying land uses around transit stations have been investigated. Moreover, the effects of TOD on city structure and the decisions of individuals in choosing a place of residence have been examined. Also, methods for assessment of TOD impacts and the prosperous cities, which implement the TOD, have been introduced, and finally, the practical solutions for implementing TOD in Iran cities have been presented. Based on a review of the previous studies incorporated in this paper, the practice and integration of TOD through land use and transportation showed that TOD could be the alternative solution in addressing the problems of developing the urban area.

Motor vehicle crashes are currently among the ten major mortality factors all around the world. Iran follows a similar pattern and has a high annual rate of fatal crashes. The majority of these fatal crashes occur on rural routes, particularly on two-lane roads. In this study, the effective factors on the occurrence of accidents on Birjand-Qayen route (South Khorasan Province, Iran) is studied. In order to investigate the effects of being in two-lane segments, horizontal curves with more than 2% slope, and segments with insufficient lighting, on the fatal crash count and crash severity, standard Poisson regression model (fatal crash count per km as the dependent variable) and standard ordered logit model (severity of crashes as the dependent variable) were calibrated using the 2013-2016 data. Zero-inflated negative binomial and zero-inflated Poisson models were also applied to investigate the effect of true zero in fatal crash count modeling. Furthermore, a panel analysis of crash severity ordered logit model was carried out to consider the spatio-temporal effects. The results of the fatal crash count modeling showed that three or four-lane segments (compared to two-lane segments) reduce the number of fatal crashes, whereas curved segments with more than 2% slope (compared to straight segments) increase this number. Moreover, according to the crash severity model results, segments with sufficient lighting as well as three-lane or four-lane segments (compared to two-lane segments) reduce the severity of crashes; whereas crash severity in curved segments with more than 2% slope (compared to straight segments) is increased.

Extensive studies have been conducted on urban travel behavior, but rarely have addressed the travel behavior of special trip generators such as dormitory students. One of the most important student travel activities is non-mandatory (shopping or recreation) ones. The purpose of this study is to investigate the influence of the factors (both tangible and intangible) on the destination choice of such activities for future policy-making in line with appropriate distribution of demand in the city. Therefore, a questionnaire was designed and distributed among the students residing in Imam Khomeini International University dormitories. The results showed that taking individual perception in addition to their taste variation into account would enhance the ρ2(0) index of the mixed hybrid logit model by 0.175 than the standard logit model (with no latent variable and no consideration of taste variations). Furthermore, it was found that increasing the distance to a zone and the absence of direct accessibility to a particular zone via public transportation (buses or taxies) reduced the utility of traveling to that zone. Moreover, the presence of the central business district (CBD) of city in a particular zone and increasing the individuals’ perceived attractiveness of a zone (as the latent variable) increased the utility of traveling to that zone. The results of the mean marginal effect of “Attractiveness” variable show that the probability of five investigated zones increases by 12.2–49.3%. Therefore, this study concludes that both tangible and intangible factors are needed to better understand students' destination choice behavior for using in future policy-making.

Assessment of road safety performance of countries and their comparison is essential in guiding future decisions. The objective of this study is to search for effective safety pillars in road safety capacity strengthening based on the experiences of the leading countries. In this study, we first try to use the results of a structural equations model with partial least squares approach to select the index as the representative index of each road safety pillar. Then, using the data envelopment analysis method, the ratio of the fatality rate to the sum of five calculated weights for a set of developing countries is calculated and the analysis of the efficiency and ranking of the countries takes place. Through the data envelopment analysis, the inefficiency of the 15 countries was calculated and ranked accordingly. The results of structural equation model showed that Iran has had a fair amount of activity in the field of road infrastructure safety. According to the results of this analysis, Iran is in the 15th position after South Africa, which indicates the poor road safety status and the quantitative and qualitative inadequacy of activities undertaken in some of the country's road safety pillars. In this analysis, the three countries of Romania, Poland and Turkey had the lowest inefficiency, each of which could be a benchmark for the activities of other countries. The results showed that only the country of Poland was identified as a pattern of activities in Iran.

At the onset of the yellow phase, drivers often come across a dilemma situation where they are unable to stop comfortably before the stop line or clear the intersection (without excessive acceleration) prior to the onset of the red signal phase. yellow time is designed to inform drivers about passing time and preventing extreme changes in cars' speed in timing of intersections with traffic lights. However, studies have confirmed that drivers face high level of uncertainty during yellow time. drivers visually sample their surroundings while driving so they are able to change their behavior based on other vehicles’ movements, the roadway environment and traffic signal data. This implies that drivers’ behaviors are affected by surrounding factors such as other vehicles’ headway or intersection conditions. In the dilemma zone, drivers’ decisions are influenced not only by their own condition (e.g., distance to the stop line, speed, red time)but also by the surrounding environment at an intersection. The primary goal of  the research described here was to develop a comprehensive knowledge of the stopping characteristics of dilemma zone drivers at signalized intersections. Physical, traffic, timing and phasing of intersections and weather conditions are assessed factors. The research performed here involved macroscopic evaluation of driver behavior; thus, characteristics of individual drivers were not investigated as it was not feasible to determine information such as age, experience, route familiarity, and sex of each driver. This study investigates actual data of traffic cameras and central smart program in four intersections in Qazvin in which traffic lights are set up. Peak, normal sunny and rainy conditions and drivers' behavior in yellow and red times are studied using binary and mixed logit model. A field study was performed using a video-based data collection system to record several attributes related to the behavior of the last vehicle to go through and the first vehicle to stop in each lane during each yellow interval. The researchers concluded that a driver’s decision to stop or go through when presented with a yellow indication is complex but can be predicted reasonably well based on several factors. Pedestrians in streets and headway are the most effective factors on drivers' pauses in yellow or red phase. High speed of cars and also waiting time (red phaseare the most influential factors on drivers motion in yellow or red phases. The results of model show binary logit model has a higher accuracy than the combined logit model for assessing driver behavior.

Traffic assignment is the last stage of the classical transportation planning process in which, the travel demand of each O–D pair is allocated to the network links, and links’ flows are estimated. To solve such a problem, some assumptions should be made about travellers’ decision-making behavior. One of the most popular approaches in this regard is the deterministic assignment that assumes all drivers are fully informed about the condition of the network and they always select the best (usually the shortest) route. These assumptions do not thoroughly match to the reality. To deal with this problem, the concept of stochastic user equilibrium has been introduced. The conventional stochastic user equilibrium assignments models are typically based on random utility theory. In this paper an alternative approach for stochastic user equilibrium assignment called random regret theory has been used in which a random regret-minimization (RRM) model is developed. RRM considers the regret of an option just with respect to outperformed options and furthermore does not lead to a closed-form stochastic user equilibrium (SUE) model, though based on that a formulation of SUE is proposed in a variational inequality form. In this study the definition of regret is modified and based on that a closed form SUE model is developed. This model is examined by two network examples.

Walking, as an important transportation mode, plays a large part in urban transportation systems. This mode is of great importance for planners and decision-makers because of its impact on environmental and health aspects of communities. However, this mode is so complex in nature that makes it difficult to study or model. On the other hand, chaos theory studies complex dynamical nonlinear systems that are sensitive to their initial conditions. A small change in initial conditions and/or parameters, may cause a big variation in the results. That is the situation that could happen in many fields of transportation. In the current study, the pedestrian behavior in crosswalks was studied in terms of chaos theory. The well-known social force model was chosen to model pedestrian movement in crosswalks, and based on the model, sensitivity analysis with respect to its parameters was carried out. Pedestrian road crossing behavior based on Helbing social force model was simulated in Matlab codes. Then pedestrian crossing behavior was investigated to detect the chaotic behavior. It was concluded that the speed of a pedestrian when the other pedestrians are closer than 100 cm and when the number of crossing pedestrians is more than 6 is chaotic. Moreover, increasing the number of pedestrians or decreasing the distance between pedestrians increase the occurrence of chaos. Chaotic behavior of speed causes turbulence in pedestrian crossing path, and that makes the path longer. Finally, some solutions for taking the system out of chaos, and consequently making its performance better, were proposed.

Stimulating the following vehicles by the leading ones repeatedly is created by the different reasons such as a sudden drop in the speed of the leading vehicle and lane changing maneuvers that result in stop and go traffic. It leads to several negative effects, such as reduction in safety, and increase in travel delay. When follower driver of platoon receives the last released wave of downstream to upstream in the traffic oscillation, he or she makes different reactions with respect to the released wave. They result in forming different behavioral patterns and behavior diversion from equilibrium driver. The behavior change analysis of the driver-vehicle unit is an indispensable factor for increasing and decreasing frequent repetitions in traffic oscillation. In this paper, employs vehicle trajectory data from Next Generation Simulation (NGSIM) program. The vehicle trajectory data of two freeway sites of the NGSIM program, Interstate 80 (I-80) and US highway 101 (US-101), were used in transportation and traffic research (NGSIM, 2006). Platoons of vehicles identified through a traffic disturbance classify in deceleration phase based on driver behavior. When the follower vehicle receives a deceleration wave, the follower’s reaction may be to create a high or low speed drop. Driver behavior in deceleration phase leads to congestion classify into four behavioral patterns: under reaction and over reaction based on maneuvering errors of follower driver. Follower vehicles react different responses to deceleration wave in deceleration phase. The reactions result in low and more speed drop between Newell driver, low and more delay time of moving vehicles. A high speed drop, more safe spacing, results in the development of under reaction pattern. Also, a low speed drop, lower safe spacing, results in over reaction. In this paper, behavior diversion parameter and time of deceleration phase are assessed, based on observed behavioral patterns and using data envelopment analysis. Follower vehicles with different numbers in traffic stop and go traffic is considered as decision making units, leading to different decision-making units in the vehicle platoon. Using data envelopment analysis method, efficient units for trajectory data are analyzed, which is based on any behavior that indicates the delay in the vehicle platoon. More performance of behavior diversion parameter and time as result of any decision making unit are identified based on any diffused deceleration wave and follower spacing of receiving deceleration wave that results in the lowest delay time of vehicle platoon of deceleration phase. The results of the analysis show that the most effective decision making unit of overreaction behavioral pattern is created in the vehicle platoon at the same spacing and velocity values but the amount of different acceleration wave and behavioral changes. Based on under reaction pattern, the greatest delay in the platoon is proportional to the different speeds and spacing but the same deceleration wave which represents the most inefficient driving situation of a vehicle following the vehicle platoon. Present results can help traffic engineers in simulating vehicles movements of freeways to evaluate vehicle moves of F level of service for calculating delay and speed drop of vehicle platoon.

Nowadays with the increase of transportation demand and according to the fact that there is a limit to financial budget to optimally assign to transportation infrastructure, safety is considered as a crucial issue faced by transport experts and also the people. One of the short time solutions to enhance safety level is to attend to drivers’ behavior in road selection. In other words, road users are usually forced to select. According to the development of multi attribute decision making methods, it is possible to assess complex problems. However, in actual fact, much more problems are introduced in uncertainty environment. In the other words, experts’ judgments are often incomplete and unreliable. In such situations, the present MADM methods are not able to evaluate. So, the present research study aims at introduce a novel method dealing with uncertain conditions namely Evidential reasoning (ER) approach, and assess the roads located in the north of Iran including Haraz, Firouzkuh, Kandwan, and Kiasar in terms of safety.

In signalized intersections and at the onset of the yellow phase, drivers often come across a dilemma situation where they are unable to stop comfortably before the stop line or clear the intersection (without excessive acceleration) prior to the onset of the red signal phase. yellow time is designed to inform drivers about passing time and preventing extreme changes in car's speed in timing of intersections with traffic lights. However, studies have confirmed that drivers face high level of uncertainty during yellow time. drivers visually sample their surroundings while driving so they are able to change their behavior based on other vehicles’ movements, the roadway environment and traffic signal data. This implies that drivers’ behaviors are affected by surrounding factors such as other vehicles’ headway or intersection conditions. In the dilemma zone, drivers’ decisions are influenced not only by their own condition (e.g., distance to the stop line, speed, red time)but also by the surrounding environment at an intersection. The primary goal of the research described here was to develop a comprehensive knowledge of the stopping characteristics of dilemma zone drivers at signalized intersections. Physical, traffic, timing and phasing of intersections and weather conditions are assessed factors. The research performed here involved macroscopic evaluation of driver behavior; thus, characteristics of individual drivers were not investigated as it was not feasible to determine information such as age, experience, route familiarity, and sex of each driver. This study investigates actual data of traffic cameras and central smart program in four intersections in Qazvin in which traffic lights are set up. Peak, normal sunny and rainy conditions and driver's behavior in yellow and red times are studied using binary logit model. A field study was performed using a video-based data collection system to record several attributes related to the behavior of the last vehicle to go through and the first vehicle to stop in each lane during each yellow interval. The researchers concluded that a driver’s decision to stop or go through when presented with a yellow indication is complex but can be predicted reasonably well based on several factors. Pedestrians in streets(Coef.=-0,61241; p-value=0,0177), time passed in red phase(Coef.=-0.53836; p-value=0,0177), and headway(Coef.=-1,89062; p-value=0,0854) are the most effective factors on driver's pauses in yellow or red phase. High speed of cars(Coef.=,172; p-value=0,0087) and also waiting time (red phase) (Coef.=,864; p-value=0,0095) are the most influential factors on drivers motion in yellow or red phases. I addition, in the situations in which drivers distance to intersection is less than one meter at the beginning of yellow phase and speed is higher than 20 m/s, passing probabilities are 74 and 90%, respectively. One of the innovations of this study is evaluating the effect of rain on the behavior of drivers. The results of model show the possibility that the drivers pass the traffic light in yellow or red phase will be increased by rising the amount of rainfall. Our results are able to inform officials about driver's behavior at intersections with traffic lights and facilitate their control and surveillance.

Once pedestrians decide to cross the streets, it is inevitable that they will conflict with motor vehicles. While crossing the streets, pedestrians may get into collisions by inaccurate judgments about the selected time to collision and speed of approaching vehicle. Thus, the aim of the current study is to investigate and identify factors affecting on pedestrians’ risk intensity based on mixed index ranking selected time to collision and speed of approaching vehicle when crossing intersections in urban streets. For this purpose, time to collision and speed of approaching vehicle for 800 pedestrians were collected by using an observational survey of six signalized and un-signalized intersections located in Qazvin city. The critical combination of these two parameters were considered as an indicator of risk. After rating the risk intensity, the ordered logit model was used for modeling. Results of this study showed that the average time to collision selected by male pedestrians (9.5 seconds) is less than women pedestrians (6.6 seconds), but the average speed of approaching vehicle selected by their (25 k/h) is similar for every two gender. The speed of approaching vehicle as the most important criteria in prioritizing pedestrians risk intensity were identified. More than 70 percent of the pedestrians while speed of approaching vehicle was 40 km/h, they taking risk. It is also indicated that factors such as gender, age, pedestrian speed, using mobile, time to collision and speed of approaching vehicles have significantly affect pedestrians risk taking behaviors. Elasticity analysis showed that the speed of approaching vehicle is the most effective variables in risk taking of pedestrians.

Traffic crashes are a social problem around the world and the weather condition is one of the major environmental factors in the road crashes. This study predicted single-vehicle severity crashes in different weather conditions. Crashes data from Ahar-Kaleybar highway at three levels of damage (225 crashes), injury (85 crashes) and fatality (14 crashes) severities evaluated. This data is from 2009 to 2012. Ordered logit model was selected for analysis. The final model consists of five independent variables of temperature above 20℃, snowfall; rainfall exceeds 6 mm and autumn and winter seasons. All of these variables have significant value, more than 0/95.The model also shows that the probability of occurring a damage crash is 70/7 percent. While probability of injury and fatality crashes are 25/5 percent and 3/95 percent respectively.