حمید بیگدلی راد

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%.

Control of traffic performance just via right of way regulations, causes the forming of long queues along the entry approaches of roundabout while results in decreasing the capacity of roundabout and also increasing the delay time of network. The idea of signalization of roundabouts can be useful as a counteraction for this problem, especially during peak hours. In this case, determining the type of control, phasing and timing of the traffic signals and also defining a pattern in signalization of roundabouts in order to select the best alternative of traffic signals operation in roundabout and reach to optimal results, is the one of the problems that seems to be facing traffic engineers when signalizing roundabouts. In this paper, to evaluate the performance of traffic signals at roundabouts with high flow rates and in order to find the suitable scenario for signalization of roundabout to improve the traffic condition, Valiasr-square which is one of the densest roundabouts in Tehran, as main case study model and Ferdosi-square, as validation case study model, are modeled and simulated in traffic simulator software AIMSUN. According to the results obtained for valiasr-Square includes a 32% reduction in delay time, 17% reduction in density, 13% increase in flow, 48% increase in speed and 17% reduction in total travel time while installation of traffic signal in its optimal scenario, it can be said that the use of traffic signals at roundabouts with high traffic volumes is a good choice to get more traffic flow and fewer delays.

The development of roads to meet the demand of cities has lost its efficiency in the modern world. Experts have found a solution to traffic problems, managing travel demand and increasing the efficiency of the transportation system. One of the ways to increase the efficiency of the transportation system is to use intelligent transportation systems. In this research, the causes of dissatisfaction of bus passengers are determined by a questionnaire, so that appropriate smart solutions can be selected based on that; Then, information is collected through Tehran Bus Company and field observations, and the current state of the network is calibrated using the information available in the pedestrian simulator software and according to the field observations. Finally, scenarios are defined to reduce delays and, as a result, reduce bus travel time. The proposed scenarios are simulated in the software. In this study, the impact of ITS as a tool to reduce bus travel time has been investigated. By intelligently removing stops at undemanding stations, using variable message signs (VMS) for drivers to increase speed, and eliminating cash fare payment, travel time can be saved by 9.8, 4.4 and 4.1 percent, respectively. The results obtained from this research show that by combining the two scenarios of intelligent elimination of stops at stations with no demand and the use of VMS signs to increase the speed, the bus travel time on the desired line from 317 seconds per kilometer to 261 seconds per kilometer. (17.7 percent) decreases.

Millions of vehicles are moving on the roads worldwide, and billions of dollars are spent each year to meet transportation needs as the main artery of the world economy today. The role of the road and, consequently, asphalt as a factor in accelerating movement and reducing depreciation costs is undeniable. The investigation of various methods used to determine the passenger car equivalent (PCE) indicates that most of these methods are focused on traffic characteristics affected by the presence of heavy vehicles. The most important of these parameters are traffic speed and the formation of a group of vehicles along the route, the speed of heavy vehicles, especially on steep slopes, the dimensions of vehicles, and the maneuvering capabilities of these vehicles in reducing and increasing slope, which are among the parameters used in determining the PCE. This study aims to analyze effective indicators and determine the PCE of various vehicles on the main roads of the country. The results show that the PCE for two-axle trucks and minibusses have the lowest coefficients among heavy vehicles. After that, the coefficients increase in the order of buses, two- and three-axle trucks, some vehicles, two-part heavy vehicles, and four-axle trucks and above. This order has been observed in different topographic conditions, different slopes, and different volumes.

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.
.

The purpose of this research is to investigate the impact of self-driving cars on changes in travel. To do the work, first, the data related to persons, households, land use, and skim matrices between the studied areas of Washington DC were entered into Activitysim software. The information obtained from the models without the presence of self-driving cars was examined, then the way the self-driving car traveled was added to the software, and the information resulting from the effects of these cars on the changes in trips, which is derived from the changes in the variables of the specific age group, the travel time in the accessibility, choosing more distant destinations for non-mandatory tours and the frequency of non-mandatory tours, in considered. The results in the one-dimensional analysis of the variables show that among the selected variables, the variable of non- mandatory activities of people in the frequency model of non- mandatory tours with 11.7% and the variable of travel time in accessibility model with 5.5% have the greatest effect on the changes in the number of trips. Also, the presence of self-driving cars has the greatest impact on shopping and leisure trips. Another goal of this research is to build a quick response model. After examining the interactive effect of the variables, it was found that the travel time variables and the activities of the working people, the age group under 18 years, and the retired are the most important variables influencing the changes in the number of trips.

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

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.

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.