فصلنامه مهندسی حمل و نقل
سال نهم شماره 3 (پیاپی 36، بهار 1397)

Due to the considerable effects of bus travel time reliability on the efficiency of the bus system and its quality of service, in this paper, we attempt to analyses the travel time reliability using a GPS travel time data set of two bus routes in Tehran, Iran. To this end, we firstly review some of travel time reliability measures introduced in the literature. We then explore the variability of these measures in the course of a day. Our results indicate that the variability of travel time in the afternoon peak hours is more that in the morning peak hours. We also examine the distribution of travel time for different time intervals of the day. Based on empirical data, it can be concluded that the distribution of travel time is not only wide but also rightly skewed. Results also show that Burr, Log-logistic and Log-normal distributions are superior to other probability distributions in terms of fitting accuracy. Furthermore, travel time can be more precisely fitted using mixture probability distributions.

This paper describes the development of methods of calculating the amount of equity in the ýdistribution of public services in the cities. For this purpose, a combination of access and ýmobility, the Connectivity Power as the primary benefit of the public transportation system ýintroduced for citizen. Vertical equity approach was selected as the approach. The number of ýpeople without personal car was considered as an indicator of the need for public ýtransportation services were considered. The state of public transport facilities are distributed ýaccording to the needs of residents of each area in the three-year base period (there are regular ýbus lines corresponding to the condition of 5 years), the current year (the current situation of ýthe city bus system, a BRT line and stations active in a part of the Metro Line 1) and the ýfuture (5 years, completed BRT projects and full exploitation of subway line 1) deals. The ýurban areas in terms of providing power connection as well as the needs were arranged and ýthe two lists for each period were compared. Spearman's rank correlation coefficient to ýmeasure the status of each area and the Gini coefficient to measure the overall situation of the ýcity were used. The results show that although the situation is better than the base year, the ýsituation is fairly significant distance. Extremist complete bus lines and subway line 1 a ýsignificant improvement in terms of the balance of supply and demand situation will not ýimprove but the Gini coefficient. The priority areas were identified for development services.ý

Development of transportation infrastructures is one of the basic requirements of each country. The criteria such as speed, comfort, safety, reliability and ready to work transportation system are the most important indexes for the assessment of the systems by passengers and the goods owners for selecting the suitable transportation. Considering the high cost of investment for purchasing fleet and building the new tracks and ever- increasing demands, the best using of rail capacities is very important.
In this paper first the components affected on productivity in different section have been identified by reviewing the literature, field studies and interview with the experts in the different rail sections. These components have been determined in the areas of infrastructure, fleet, mobility, commercial and human resources. A questionnaire based on the effective criteria and components is prepared and distributed between the experts in this field. After collecting the questionnaires, the statistics test, the Cronbach's alpha, distribution normality, data statistical description have been made and by using the one- sample t test the correctness of the proposed hypothesis has been proved. Finally the prioritization of the factors effected on the best utilization of the rail fleet capacity have been submitted by using the linear assignment of multi- criteria decision making methods.

Pricing is one of the most common methods for demand management in transportation engineering. This method can also be efficient for curb parking demands in down town areas and central business districts. The aim of this study is to assess and predict the effects of curb parking cost elasticity on mode choice behavior of motorists. The stated preference method is used for data collection in central business district (CBD) of Qazvin city and the mode choice behavior of motorists was modeled due to different pricing scenarios. Using a Binary Logit, it can be concluded that the price value of motorists’ car, car ownership per household, hourly parking rate in CBD, maximum hourly parking rate which users are willing to pay, trip purpose and household size of users are significant in users’ mode choice utility due to pricing. The results indicated that by increasing the parking hourly rate by 1%, the probability of choosing private car decreases by 0.004% and also by increasing the user's maximum payment for parking by 1%, the probability of choosing private car increases by 0.016%.

The main aim of this study is the investigation of the effects of different types of information (visual, vocal and textual) on traveler's cognition and recalling. Second aim of this research is to compare the effects of different order of visual/textual information on travelers’ memory. To investigation of the effects of different types of information on traveler's cognition and recalling, three experiments, each at two different levels, are designed. The design and creation of two different levels for each experiment is intended to investigate the effects of the amount and verity of information received by travelers on their cognition and recalling ability in light of the traveler information systems. In the first level of experiments, travelers experience smaller numbers of events compared to the second level of experiment and they recall the small amount of information. In other words, the first level of each of the three experiments is simpler and easier than the second. The effects of different types of information are examined by defining the appropriate evaluation indicators and making statistical inferences. The results show that the travelers’ cognition and recalling ability is affected by the type of the information. Hence, the cognition and recalling of travelers which are guided by the visual, vocal and textual information, is significantly different. Also, the results show that the different orders of visual/textual information differently affect the ability of travelers’ acquisition and recalling. This means that contextual preparation by visual information can improve the travelers’ acquisition and recalling of the textual information.

The aim of this study is to propose a novel method to identify the bottlenecks in the railway networks. This method is based on two different approach. In the first approach, a new algorithm is proposed, aimed to incrementally assign the freight demands to the network. The specific novelty of this approach is the consideration of the railway capacity during the assignment process. By employing this approach, the critical bottlenecks of the railway networks can be identified. A second approach aims to determine the relative priorities of the bottlenecks and proposed to resolve them. In this approach, the method all or nothing assignment (Regardless capacity Blocks) is used to determine the load flow in different parts of the railway network. In order to prioritize the capacity bottlenecks the index titled "bottleneck intensity" is presented. The index indicates the potential load demand in the difference origins-destination. To evaluate the proposed method in this study, Iranian railway network examined. All demand and network capacity data were collected and using the proposed method capacity bottlenecks were identified and Prioritization.
The results of this study showed that the solution to increase the capacity in 10 first critical bottleneck absorbed potential demand equal 4.7 million tons in the railway network.

After disasters, preparation for performing an effective rescue mission can significantly reduce the costs and possible injuries of the event. Relief is regarded as one of the crucial steps in developing of disaster management systems. This research has tackled a multi-product multi-period inventory routing problem in order to develop an efficient strategy for temporal relief tasks. To solve the model, an improved fractal search algorithm was employed. Fractal search is a population-based and powerful optimization algorithm that explores the problem space based on the potential theory, growth of the random fractal and three physical laws. Based on instance problems, the efficiency of the proposed algorithm is compared to other methods in terms of running time, convergence rate, success rate, best and average standard deviation of the results, as well as the statistical superiority by test of Wilcoxon. Assessment of the results show that the proposed algorithm has a better performance based on running time, convergence speed, and success rate in temporal routing of rescue vehicles. The results show that by increasing of problem dimensions, better efficiency in the proposed strategy is detected. The proposed framework in this study can be used in relief scenarios and related inventory routing problems.

Expanding cities and population causes an increase of travel demands. Private vehicles cannot cope with responding to the travel demand of the large urban population. Therefore, it is interesting and unavoidable issue to use different urban public transportation systems for commuters in cities. Different parameters are involved in the public transportation system development. Some parameters are as follows: travel time, walking time to bus stop, travel convening, utility cost resulted from a public transportation system and maximum routes covering and crossing the downtown and the like. However, the most important parameters that causes in increasing the use of the public transportation system is travel time and travel cost for commuters. For this purpose, a multi-objective mathematical model is presented to minimize the travel time and travel cost while covering the routes with the minimum number of buses. Due to the NP-hardness of such a hard routing problem, a vector-evaluated particle swarm optimization (VEPSO) algorithm is proposed to solve a real case problem for the current routes of the Ardabil urban bus system. The associated results are compared with the multi-objective particle swarm optimization (MOPSO) algorithm. The comparison of the obtained results shows the efficiency of the VEPSO algorithm for the considered case study.

Presently aluminum and steel are used to construct aerodynamic brake panels in high- speed train, however the aim of this paper is to increase natural frequencies and reduce the weight of panels at the same time using composite materials. In this paper, composite graphite epoxy (AS4 / 3501-6) is used, due to its better vibration characteristics among other composites. According to simulations, the natural frequency of graphite epoxy panel in comparison to aluminum panel has increased from 84.205 Hz to 101.55 Hz which is a 20 percent rise. What is more the maximum stress on the composite graphite epoxy panel and maximum lateral displacement are 71 MPa and 2.952 mm respectively. These results indicate better performance of graphite epoxy panel in comparison to aluminum panel. Finally, the panel during opening from -5° to 73° in 3 seconds is considered and the results of dynamic analysis of brake panel, using ABAQUS software, including Transverse displacement and stress is presented. It is shown that when panel has completely opened to 90 degrees, stresses and displacements are in a good agreement with static results.

The occurrence of disruptions in urban rail cause train delays, extra passenger waiting times, and drop in service level and schedule adherence. Rail disruption management refers to the implementation of the control strategies to manage unexpected events and improve the system performance. In this study, a temporary line blockage is regarded as a source of disruption in train movements. A simulation-based optimization approach is proposed to minimize the total average waiting times and traveling times of passengers. Disruption management strategies include skip-stop and short-turn control policies. Simulation technique is used to model random variables in question, including train traveling time, random arrival rate of passengers, and the stochastic recovery time. The proposed approach also includes the variable neighborhood search algorithm to find the near optimal solutions. In order to validate the proposed methodology, several disruption scenarios in Tehran Metro Line 1 are investigated. The results of solving the real problems show the efficiency and proper use of simulation-based optimization method in the decision-making under disruption. The results have also shown that a combination of skip-stop and short-turn strategies gives travelers greater improvements in reducing the waiting and travelling times. The implementation of variable neighborhood search method on the real-world case study demonstrate that the combined strategy reduces the average traveling time for passengers about 14%.