hamid bigdeli rad

The Increase in Population in Big Cities and the Consequent Increase in Travel Demand Causes an Imbalance Between Supply and Demand, Creating Traffic Problems for Different Modes. Supply Development and Demand Management are Two Main Methods for Improving These Conditions. Supply Developments Attempt to Respond to Extra Demand by Increasing the Capacity of the Roads. Demand Management Reduces the Traffic Volume by Decreasing the Travel Demand. A Road Diet is one of the Most Used Methods of Demand Management. In This Research, the Effectiveness of These Two Approaches in Improving the Current Conditions is compared. In This Case, Three Scenarios of the Current Situation, Supply Development and Road Diet Have Been Simulated Using Aimsun Software in Imam Khomeini Street in Ardabil City. The Results Show that Supply Development is More Appropriate to Improve Traffic Parameters in A Short Time, And Road Diets Can Potentially Improve Safety.

Rapid urban growth has led to an increase in travel demand and private vehicle ownership, and the existing infrastructure has not been able to match the effects of demand and traffic congestion. As traffic density increases, passenger delays increase and network reliability decreases. In the analysis of transportation systems, estimation and analysis of travel demand have particular importance to achieve an efficient and effective transportation system. Estimating and correcting demand matrices is very important, and more reliable and practical results can be achieved by using more accuracy and details in their estimation. In the problem of matrix estimation and modification, especially in dense networks, the accuracy of models significantly increases by using simulation models. In this research, the goal is to optimize the time distribution coefficients of the demand matrix in 15-minute steps for the entire study period. A bi-level approach has been used to estimate the travel demand matrix from previous matrices, which are the static matrices of comprehensive studies. At the upper level, it produces coefficients by Gaussian mixture models and uses Teaching–Learning-Based Optimization algorithm to optimize. The objective function is to minimize the error through the RMSE value. Unused stations are used to validate the model, and the detection coefficient, R^2, in all intervals and stations is 0.91 and in the 3 peak periods, the value is 0.88, according to the optimization approach using previous matrices, to change the time distribution of trips (trips start), the results show the proper functioning of the presented bi-level process.

Metro has become a necessity as a solution to traffic and a heavy and important means of public transportation in today's world. The need for traffic management and planning is inevitable. Therefore, the purpose of train scheduling is to minimize the time of the trains from the origin to the destination, to satisfy the passengers and stakeholders, to minimize the delays in the stations and to maximize the use of the capacity of the lines, stations, and fleet. An approach by considering all the factors that affect the time of trains in the network can lead us to produce a plan to achieve the mentioned goals. In this research, which is a case study of an urban train between Tehran and Karaj using queuing theory with the M/G/C/C pattern, a schedule for the train head based on three scenarios of the maximum capacity of the train in which some passengers are standing on the low track, the capacity In the mode of all passengers sitting, and the other mode was considered in the mode between these two modes. It was investigated using the hourly pattern in the case study of line 5, 32% of the distribution is in the middle stations, currently the current schedule of the metro causes delays and Dissatisfaction is for a group of passengers, which the proposed timing reduces to some extent. The proposed time is between 6-30 minutes in different scenarios for different hours. The proposed time reduces the waiting time by 21%.

The Complexities of Operating DAR Services Mean That Computerized Planning and Scheduling Is Necessary for Systems of Realistic Size. This Research Studies an Electric Autonomous Fleet Size with Mix Dial-A-Ride Problem. The Goal of The Problem Is to Minimize a Weighted Objective Function Consisting of The Total Travelling Costs of All Vehicles, Users' Excess Ride Time Costs and Vehicles' Acquisition Costs While Satisfying Customer Service Level Constraints Along with Battery Level Management and Recharge Times Management Constraints. In This Variant of The Dial-A-Ride Problem, Recharging at Any of The Available Charging Stations Is Allowed. A Cluster-First, Route-Second Genetic Algorithm Is Proposed to Solve the Problem, Where the Clustering Is Performed by Choosing the Fleet Size and Assigning the Customers to The Fleet Using a Genetic Algorithm (GA), Then the Primary Routes Are Developed by A Routing Heuristic, Finally the Charging Stations Will Be Inserted to The Algorithm Using an Insertion Technique. The Performance of The Proposed Method Is Tested by Using Benchmark Instances of a Related Problem from The Recent Literature. The Proposed Method Has Achieved Solutions Comparable with The Current State-Of-Art Methods. The Computational Results Show That the Proposed Method Is Effective in Finding Comparable Solutions with The Current State-Of-Art Method. New Instances, Some of Which Include First-Mile Feeder Services, Are Generated Based on The Data from Uber Technologies Inc. Tests Performed on New Instances Demonstrate That the Minimum Possible Fleet Size Does Not Always Result in Minimum Costs. Moreover, The Tests Show That Integration of The Feeder Services into Dial-A-Ride Services Increases Ride-Sharing Ridership.
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In any transportation planning, including rural transportation, the characteristics of existing supply and demand must be identified. According to this knowledge, the main needs and problems of the villagers in the field of transportation can be identified. In urban transportation planning, travel models are usually built in four stages. In the first stage, travel production and absorption models, in the second stage, travel distribution models, in the third stage, vehicle mode choice models, and in the final stage, route selection and traffic assignment models. In this study, and according to the studies conducted on the difference in behavioral pattern as well as the difference in the way of planning in the village and city, modeling related to the stage of production and absorption of travel is done using backward elimination regression. This study was conducted by case study of a number of villages in Qazvin city and can be generalized to other villages that have similar characteristics. Finally, according to the developed models, it was found that in work trips, the variable of employment rate, in educational trips, the number of students, in shopping trips and ethnics and medicine and in the demand of total travel variable population have the greatest impact on the model. With the current situation demand, it is possible to develop a forecast demand model for different horizons by applying the population growth rate and employment. By estimating the demand for travel, in order to create and build road and rural facilities, road pavement and road maintenance can be planned.

In most countries of the world, saving human lives is one of the most important and first factors that have been considered by politicians. Among the causes of death, road accident is known as one of the 10 causes of death and casualties. Therefore, paying attention to reducing the number of accidents and also reducing the severity of accidents, is the goal of the country's officials, and their planning and prioritization is in the same direction. One of the most important parts of traffic accident analysis and prediction is selecting and using appropriate models. In this study, extensive research has been tried to give a good view to researchers to choose a suitable model. Also, the human factor in accidents has been studied and the parameters affecting this factor have been studied and the most important ones have been stated. Therefore, the purpose of this study is to examine in detail the most important factors (appropriate model and appropriate parameter) in the evaluation of accidents. Results are shown that Deep learning approach/Data mining/machine learning models had the highest power with 87.27%, followed by Poisson-lognormal and generalized additive models. It was also concluded that most models were used in suburban accidents, however, there were one model “microscopic simulations” that were used more in urban accidents. Deep learning approach / Data mining / machine learning has allocated the most up-to-date research with an average close to 2016 (2015.82). Random-parameters models are next with an average of 13.4. Duration models with the lowest mean (1998.2) are at the bottom of this classification and have the oldest research. Based on this information, it can be concluded that today researchers are more inclined to new models such as Deep Learning, which may be due to the high accuracy of these models.

Predicting the safety of the rail transport system is a fundamental problem in modeling and managing rail transport. In this paper, a profound learning-based safety prediction model for rail transport safety is proposed. Data were collected from the subway operating company and decisions were made on the factors of the forecasting model. These factors were used as DBN input. The structure of the input data determines the number of nodes in each layer. Sample data collected include types of accident-prone events, basic train information, and company operating information. Predictive factors were selected by analyzing these collected data. The DBN was then created based on the processed data. To show the accuracy of this model, a data set (Tabriz subway) has been investigated as a case study. Experiments on the data set show good predictive performance of the present model. These results show that deep learning is useful in learning the patterns of a rail system. Prediction and reality error between 0.08 and -0.08 are introduced. This is an acceptable error and cannot cause an incorrect level of security in the system. The dense safety range, both in the current situation and in the forecast model, is at the second level, i.e. relatively safety. This range is in the range of 0.8 to 0.89. Of course, the tendency of density after the second level is towards the first level to the third level. It is noteworthy that the forecast model (at high levels) shows higher values ​​than the existing safety.

Road accidents and the resulting casualties are one of the current challenges of human societies that have imposed great economic costs on the economies of countries. Given the information on traffic safety in previous studies, it is very important to determine traffic safety planning in anticipation of an increase in traffic accidents. The neural network models used in this field have gaps. In this study, in order to solve the neural network problems after diffusion, a new method that combines particle group optimization and support machine (PSO - SVM) combined to be used to predict traffic safety. First, the factors affecting traffic safety and evaluation indicators are analyzed, then the traffic safety forecasting model is created by PSO - SVM according to the effective factors. Finally, traffic safety data from 1997 to 2018 are used to investigate the predictive ability of the proposed method. Experimental results show that traffic safety prediction by PSO - SVM is superior to post - diffusion neural network. MAPE values for predicting the number of events by PSO-SVM and post-diffusion neural network were 0.0281 and 0.0498, respectively. Models have more fluctuations than observation data, so more accurate models can be created to adjust these models. Due to the fact that the error in the data related to the number of injured is less than the data on the number of accidents and casualties, the cause can be related to the number of more data

Achieving the sustainable development of the urban transport network requires systematic and efficient planning, and precise implementation. In this regard, consideration of non-motorized transport (walking and cycling) as a successful way to reduce the economic and environmental costs of urban transportation is debatable. For this reason, the present study studies the characteristics and factors affecting riding, pedestrians and bicycles. Case study of this study is data derived from a sample origin-destination questionnaire from residents of Qazvin, including personal and family characteristics, socio-economic characteristics, environmental characteristics and transport network characteristics. Therefore, in order to investigate the behavior of individuals in choosing the mode of travel, the modeling was carried out in three modes, namely: motor and non-motor transport (32053 views), second mode: walking and cycling (8203 views) and third mode: motor transport, walking and cycling (32053 views) is presented using discrete selection models. Depending on the models, it is observed. The results of the review of the choice of motorist non-motorized travel method, the same final model resulting from considering different modes of non-motorized transport (pedestrians and bicycles) as an option. If the intermediate model (selection mode between walking and biking) replaces the option to choose a motor transport option. The results also show that individual variables (age, gender, education, certification, and occupational status), socioeconomic (motor and non-motorized ownership and household size) as well as variables related to network and travel (destination, destination distance, travel distance , Travel purpose, time-out-day of travel and the number of trips in the travel chain) affect people's choices in choosing traveling manner.

Today, the use of intelligent transportation systems with the aim of smooth traffic and location of passengers and goods, as well as increasing safety and protecting the environment has been widely considered. Variable message signs, abbreviated VMS, are traffic control devices. They are used to inform drivers on time. In this study, locating was performed in two different ways. First, the cell transfer model was performed for Azadi Street in Tehran. Then, this was done on the desired area through an optimization model. According to the analysis and comparison of the two models, it was concluded that the optimal mathematical model determines a greater distance to determine the location of the variable message signs. It also further reduces the amount of input to the blocked area and the total travel time, indicating that this model is more suitable than the cellular transmission model. However, the difference between the two models was very small. The optimal location of the variable message signs was 515 m for the cellular transmission model and 725 m for the optimal mathematical model.

Road safety is recognized as one of the most important factors in transportation system of the world as well as in reducing road accidents. Currently, heavy expenses are spent for reducing road accidents and casualties, however, authorizes haven't so far achieved satisfactory and desirable results. It appears that adoption of global solutions might be effective in securing roads safety and making necessary planning and management in this regard. In the present study, researcher with the use of AHP Fuzzy method has tried to identify and determine the importance level of the effective factors on the safety of northern roads in Iran. For this purpose, a research population consisted of 125 traffic and transport mangers, practitioners and experts have responded to a 78-item questionnaire and finally, 23 factors were identified as the effective factors on safety of the northern roads of Iran. Research results indicated that with the adoption of AHP FUZZY method, the indicators of advertising in national media, reduced average age of vehicles and appropriate designing of road geometry respectively have the highest weight and importance with 0.126, 0.082 and 0.065 weights.

One of the most important parameters in assessing the satisfaction of passengers in a bus system is bus frequency or bus headway. In this study, optimization of the public transportation system’s frequency has been investigated, which aims to determine time interval between the next buses for a set of public transport lines determined by their travel plans. Origin-destination demand and restrictions on existing bus fleets should be considered by results. In this way, a model (MILP) was proposed for a pre-existing model which originally formulated as a non-linear two-level formula. The proposed formulation is capable of solving the real optimality of small scale problems using the MILP technique. In order to solve large scale, a metaheuristic method has been proposed that its accuracy is estimated by comparing exact results. Both an exact and approximate approach have been tested using existing cases, thus, the public transportation system of Qazvin has been used as case study. Although its public transport system has 22 lines, an improvement of about 6% was achieved using this model. This shows that, even in small cases, there are improvements in system efficiency. Since the general improvement of Qazvin bus system was not possible after a considerable amount of runtime, an alternative solution approach was proposed in this study. Therefore, a tabu search method has been proposed, which results in a competitive comparison with the exact model.

New roundabouts are innovation and revolutionary in roundabout design, with the risk of incidents in these roundabouts far less than traditional common roundabouts. These types of roundabouts control the traffic flow at the entrance and exit of the roundabout, with the guidance of drivers to isolated lines before entering the roundabout and guidance to the spiral lines inside the roundabout as channelized. Another advantage of these roundabouts is the much more balanced division of traffic flows than traditional ones. In Iran, in view of the many problems of capacity, flow and safety of intersections and intersections, this type of roundabout can be very useful in certain conditions. In this research, how these roundabouts are compared and also the comparison of different input capacities based on the origin - destination demand matrix for new roundabouts and common roundabouts of two lanes with the help of Aimsun traffic simulation software have been investigated. For this purpose, the values of traffic indicators of delay time, density, flow, stop time and travel time of computer simulations for new roundabouts and common roundabouts have been investigated and compared. According to the demand matrix of the origin-destination models loaded in the software and comparisons done, the optimal model for the highest capacity and the lowest delay time and travel time is presented. In this simulation, 8 to 16 percent increase in traffic flow and a decrease of 34 to 59 percent for travel time and delay time in the new roundabouts is shown in comparison with the common two-lane roundabouts.

Among the important issues, the question of justice and equality in the design of the network is being used. There have been various concepts of equality, including equality between generations, equality between landowners and equality between the users of the system. As well as ways for considering the measure in question is investigated, such as problem solving multi-objective or add conditions of equality as a restriction. In this study, the purpose of social justice that is considered urban development plan including toll of civilians and their spending in a way that conflicts of interests between any pair of area traffic network users does not exceed acceptable value. A parallel programming model to solve two problem of pricing and in terms of social justice networks is investigated. The results of two-state solution with and without observing the conditions of justice about the optimal toll rate has similar results. In the event that the optimal toll rate for non-compliance with the requirement of justice was equal to 1.85 currency, in the case of compliance with the conditions of social justice and equality, this rate was equal to 1.6 currency. Observation shoed that optimality of the objective function and answer are reduced, the general interest of the users of the network declined.

Tehran suburb city rail Exploitation Company (Tehran subway) presents public transportation services to more than 3 million people in a day. Therefore, the way these services are presented and customer satisfactions’ rate with the services presented to enjoy high importance. In the matters applied to the survey, first the expectations that users of this public transportation system have and the perception they had after using these services were examined by servqual services quality assessment model.The aim at this study is surveying the gap between the expectations and perceptions of customers from services presented by Tehran Subway Company.To provide necessary solutions to eliminating this gap or at least minimizing it with the aim of increasing subway service quality level by this model.The findings showed that the performance of Tehran Subway Company was under the expected rate of citizens from the credibility dimension, reliability dimension, empathy dimension, answering dimension and items marked of servqual model. Therefore, there is a need to take extensive practical measures for removing defects and mitigating this gap.