International Journal of Transportation Engineering
Volume:7 Issue: 2, Autumn 2019

Liberalisation process has just started in the Turkish rail market with the new law recently entered into force in order to comply with EU Directives. In the liberalised markets, service quality is the decisive factor that rail undertakings can use to create difference and achieve competitive advantages. The purpose of this paper is to analyse the customer perceived service quality for rail freight transport and to highlight the important service quality gaps that must be dealt in the process of market liberalisation. The analysis is based on the findings of the survey conducted by interviewing rail stakeholders to understand their perceptions on rail service quality. The results of the research revealed that the widest quality gap relates to “transit time” which is perceived as the most important dimension of the operational quality of the freight services. It was identified that forwarders’ service quality perception is lower than that of shippers.

In recent years, car-sharing systems have been announced as a way to increase mobility and to decrease the number of single-occupant vehicles, congestion, and air pollution in many parts of the world. This study presents a linear programming model to optimize one-way car-sharing systems for electric cars considering the depreciation costs of chargers and vehicles as well as relocation cost of vehicles. In this way, the objective function consists of imposed costs to the system due to the depreciation cost of vehicles, depreciation cost of chargers, and relocation cost of vehicles. Also, the rate of depreciation and the cost of relocation is considered constant in this study. The model was implemented on small and big test networks with 2 and 100 nodes with variable parameters and demand patterns. The results indicated that managing the fleet of vehicles by relocating the vehicles among stations increases the inventory at each station and minimizes the cost for meeting all requests. Also, the results indicated that the number of required vehicles decrease with an increase in charge levels and final cost increase with an increase in depreciation rate.

More than 60% of accidents in Iran occur within 30 kilometers of cities entrance roads. Therefore the number of accidents per kilometer in these regions, in contrast to the other parts of roads is very considerable. The city of Tehran, as the capital of Iran, is the cross point of major arterials of passenger and freight transportation. Thus the evaluation of road safety, entering and exiting the city in the 30 kilometers buffer, can be considered to improve countrywide road safety. To investigate the effects of roadway characteristics and traffic conditions, including number of traffic violations, on accident frequency within 30 km of Tehran entrance roads, Poisson and Negative Binomial regression model were calibrated in this study. Although the goodness of fit index in Poisson model is much greater than the Negative Binomial model, the accident data dispersion in this study implies that Negative Binomial model is more appropriate to show the influences of effective variables. According to results of modeling, the variables including average daily volume, share of heavy vehicles, average daily speed violations and number of direct accesses and interchanges have effective influence on accident frequencies. Controlling access to roads and using effective actions to reduce the speed and number of speed violation can be accounted as effective policies to reduce accident frequencies within 30 km of Tehran entrance roads.

Intersections are considered as the most critical parts of the bus rapid transit (BRT) system. Transit signal priority is one of the efficient solutions to reduce BRT fleet delays at intersections. The aim of this study is to propose a new algorithm to decrease the BRT fleet delays at actuated intersections, while reducing the negative impacts on different approaches. The adaptive strategy is applied in this study. In the proposed algorithm, named TSPAT (Transit Signal Priority for Actuated Timing), intersection phasing is rescheduled, based on traffic conditions such as phase conditions at the time of bus arrival, the queue length of other approaches, and prioritization record in a specific time length. To assess the merits of the proposed algorithm, a before-after study is executed by applying VISSIM traffic simulation software for an actuated intersection in Isfahan city, Iran. The simulation results show that by applying the algorithm, the average delay of BRT fleets is declined by 21 % and 51% in peak and off-peak hours, respectively. Furthermore, the average speed of BRT fleets is increased by 26% and 78%, during peak and off-peak hours, respectively. The utilization of TSPAT algorithm can improve the desirability of the public transportation system along the BRT routes.

Hub facility location problem looks to find the most appropriate location for deploying such facilities. An important factor in such a problem is the pool of potential locations from which the optimal locations must be selected. The present research was performed to address two key identifying the factors contributing to the selection locations for hub establishment, and presenting an efficient methodology for assessing the efficiency and effectiveness of each node, followed by selecting optimal nodes for establishing potential hubs. The paper begins with a review on related literature, leading to identification and classification of the most important factors and criteria for a hub based on the required features in transportation systems. Subsequently, in order to assess all nodes, the identified factors were grouped into input and output criteria, with the extended Data Envelopment Analysis used to assess the efficiency of the nodes. Moreover, the assessment accuracy was enhanced by weighting the input and output criteria using Analytic Hierarchy Process. A significant achievement of this research was the innovative combination of Analytic Hierarchical Process and Data Envelopment Analysis by presenting a scientific model in the form of a heuristic pair-wise comparison matrix followed by adopting power eigenvector methodology. The result of this hybrid approach highlighted the nodes upon which unavailability the efficiency of other nodes was significantly affected, and new rankings of the nodes upon such unavailability. In order to validate the findings, Iranian Airport Dataset (IAD) was used.

The purpose of this study is solving a sustainable vehicle routing problem (VRP) which in this problem special features such as mixed close–open VRP, multi-depot VRP and some others which will be discussed in this section are considered for achieving closer to real life applications. Fleets of vehicle studied in this paper are heterogeneous and for each vehicle separated compartments with different capacity for each type of wastes is took into consideration. Vehicles have different limitation on traveling time, different fixed and variable cost and amount of pollutants that is emitted from them. For achieving a sustainable VRP economic, environment and society aspects should considered simultaneously which in this paper objective functions (1) to (3) respectively are about mentioned purposes; first one minimizes the cost of collecting wastes from customer’s location, second one minimizes the pollutants which are emitted from vehicles while they are collecting wastes and finally third one minimizes violation from time limitations which are exist on each customer’s location. A new mathematical mixed integer programming model is developed for solving this problem and problem is solved by CPLEX solver and augmented ɛ-constraint method. Moreover, AHP technique for making decisions is applied in order to help us to choose the best decision. Finally, sensitivity analysis is done on some important parameters.