Journal of Transportation Engineering
Year:2017 | Volume:8 | Issue:2|Papers Count:8

Transportation systems are among the most important sectors in each country. With population growth, demand increases for transport of goods. In such situations importance of the proper design of transportation networks is undeniable. Inter-city transport is completely essential for distributing goods around the country. The proper design of an efficient public transport system is crucial. Using Hub networks become popular in such situations. Therefore, with respect to important applications in public transport, in this paper we investigate the multi-product multi-objective p-hub median location problem. Also, considering the importance of environmental issues and pollution of transport networks in this study a multi-objective model is intended to minimize greenhouse gas emissions. Due to the scarcity of financial resources in the economy, methods of Finance in the proposed model are also included. Data from the statistics of country road transport in 1392 is obtained. To solve the problem, the Gams 24.1.3 optimization software and meta-heuristic algorithms, i.e. Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA) are applied. The results show that ICA overcomes SA.

Road traffic management consists on improving the traffic fluency on road networks, assigning dynamically the traffic flows, and reducing the number of traffic congestions states as well as their negative effects, i.e. blocking the emergency vehicles, delays, waiting time, drivers’ stress of emergency vehicles, air and noise pollution. the proposed algorithm consists in improving the traffic flow, i.e. the road network can support more vehicles without decreasing the average speed of vehicles, while taking into account the real-time road traffic information; and on the other hand, in reducing the number of traffic congestion situations by avoiding the massive use of the same road at the same time (i.e. providing the suggestion of itineraries with a lower travel times). This allows adjusting intelligently and promptly the road traffic in the network according to the real-time changes.This paper proposes a multi-agent system for path traffic management from swarm intelligence. The objective is to increase the quality of the entire path network, especially in case of congestions and jams, taking into account real-time traffic information and travel time of drivers to reach their destinations.

Satisfying the healthcare needs of patients at home have many advantages in today’s world. Providing an orderly health services both decreases the costs and speeds up healing of patients. For instance by replacing hemodialysis with peritoneal dialysis which can be done at home, patients feel more comfortable and the medical expenses would be lower. In this paper a periodic robust vehicle routing mathematical model with simultaneous deliveries and pickups and soft time windows to serve peritoneal dialysis patients at home is developed. The model is built according to the issues and problems which are seen in dialysis center of Hasheminejad kidney center. It has been tried to consider realistic assumptions in the model design, such as the uncertainty in the travel time of the vehicle. Having the sensitiveness of providing timely healthcare service in mind, a method should be applied to face the uncertainty in time which guarantees minimum risk. Moreover, considering a cost term called “lost opportunity”, the presented robust model should not be too conservative and impose on huge unnecessary costs. Results show that the presented robust model at the worst condition or in other words at the maximum uncertainty level has no constraint violations. It means that by using this model the chance of providing timely health service would be enhanced.

Pedestrian environments (PEs) are one of urban spaces that can improve walkability of people and foster social attitude to walking, as well as to enhance safety and environment. In order to improve the quality of PEs, it is important and necessary to design and build them in accordance with the walking behavior pattern of pedestrians. The aim of this research is to identify the characteristics of pedestrian flow and their route choice pattern by determining the pedestrian bahavior parameters and constructing pedestrian behavior models in the pedestrian environment. In order to study the pattern of pedestrian behavior in PEs, the PE of Khayyam in Qazvin is chosen as a case study. The research is carried out by collecting data from videos of the PE at the peak and non-peak hours using a cellular automata model, and simulating pedestrian flow in PE. A discrete choice model, i.e. the logit one for each of the cells in the neighborhood definition as the choice set are constructed. Results show that Pedestrians at the cells in proximity to land use prefer to occupy lateral cells in their next step, and at the middle strip of the PE, they tend to move either straightly to move forward, or perpendicularly to cross the PE. The relative symmetry in arrangement of obstacles with respect to each pedestrian causes to the selection of straight path.

Recently, utilizing the traffic simulation models have been known as an efficient traffic control and management tool. However, all traffic micro-simulation models require a car-following model so that the simulations would be performed based on it. Many car-following methods have been proposed yet, but all these methods have several number of parameters to calibrate, in a way a little variation over them creates considerable disturbance. In this paper a new car following model was proposed using the Multi-variate Adaptive Regression Spline (MARS) method that do not need any calibration stage. The proposed model inputs are leading vehicle velocity, relative velocity of leading and following vehicles and spacing between them and the output is the acceleration of the following car. As a result of this paper, a car following model with the Mean Squared Error (MSE) equal to 0.004 and the correlation coefficient (R) equal to 0.98 was achieved using the function estimation method through the MARS method. Finally, the MARS output was compared with the results achieved by the Helly linear model, the GHR model and the Gipps model. Based on micro simulation experiment it was shown that the proposed method was more accurate than those models.

Pervious concrete is increasingly used in the pavements and overlays subjected to heavy traffic and in cold weather regions. Typically, pervious concrete has little or no fine aggregate and has just enough cementitious paste to coat the coarse aggregate particles while preserving the interconnectivity of voids. In the present study, effect of nano silica additives on pervious concrete abrasion resistance is investigated. Five samples indicate the PPC, PCNS1, PCNS3, PCNS5 and PCNS7, which respectively represent plane pervious concrete, pervious concrete containing nano silica in the amount of 1%, 3%, 5% and 7% by weight of binder, have been evaluated. A total of 30 samples were prepared which 15 samples for testing compressive and 15 cubic cubes was for wear resistance. The results indicate that by increasing the use of nano silica in pervious concrete, compressive strength and abrasion resistance were also increased. The concrete containing nano silica in the amount of 5 % by weight of binder has the best abrasion resistance performance. Use of nano silica in the amount of 5% has a very good influence in enhancing abrasion resistance and compressive strength about 48% and 28% respectively. Other studies on microstructures between the cement mortar mixed with the nano-particles and the plain cement mortar showed that the nano-silica filled up the pores and reduced CaOH2 compound among the hydrates. Finally, the relationship between the indices of abrasion resistance and compressive strength of concrete is obtained, which indicates that the abrasion resistance of concrete increases with increasing compressive strength.

In recent years, increasing use of public urban transportation and road networks causes that route planning is now becomes a necessary element in the transportation networks more than ever. Multimodal network is a special case of the transportation network in which we are able to use different transportation modes. In this network, the sequence of the transportation modes is as important as the sequence of nodes in determining the optimal route take into account the constraints. In this paper, a multi-objective mathematical modeling multimodal network has been presented. In addition to minimize the number of changing modes, cost and the time are also considered in the objective function. An approximation algorithm based on dynamic programming has been developed. Furthermore, the experimental analysis shows that the efficiency of the proposed algorithm in compared to NSGAII algorithm. Moreover, a real case study based on the public transportation system in Tehran is solved by our model.

Increasing of tire inflation pressure in recent years is one of the main changes in truck loads characteristics which is highly effective on the interaction of tire and pavement. It results in the reduction of tire imprint surface area leading to the increase of pavement damage. Reinforcement of pavement using geosynthetic is one of the methods to overcome this problem. In this study, the effects of tire inflation pressure on the responses of a typical asphalt pavement reinforced by geosynthetic have been investigated.3D Finite Elements method using ABAQUS has been utilized for pavement analysis and determination of pavement responses. Viscoelastic behavior was assumed for the asphalt layer and a method was developed for determination of the Proney’s series parameters for a typical asphalt concrete mixture used in Iranian pavements. Three types of geogrid with different elastic modulus has been utilized at three different positions in the pavement structure, and the effects of different tire pressures of 600, 750 and 900 kPa on the two critical pavement responses of the horizontal tensile strain at the bottom of asphalt layer and the vertical compressive strain on the top of subgrade have been investigated. It is found that, the tire pressure is mainly affect the horizontal tensile strain of the asphalt layer and the compressive vertical strain on the subgrade is not significantly affected by the tire pressure. The results also show the optimum position of the geogrid for reducing the horizontal tensile strain of the asphalt layer is at the bottom of asphalt layer and that for reduction of the compressive strain on the subgrade is beneath the sub-base layer. it is also found that the performance of geogrid in reduction of the tensile and compressive strain is not affected by the tire pressure.