Results of Traffic Assignment models are the main output of transportation planning studies and decision making for future developments is based on these results. Therefore, accuracy of these models is very important. Despite the mentioned importance, comparing the models and their solving Methods to estimate actual Traffic volume and network performance measures is rarely considered in previous studies. The Traffic Assignment process has started from the simplest Methods like All-or-Nothing, then it has developed using the rules and supplement assumptions such as Wardrop principles and finally it has evolved by concepts such as Fuzzy theory. Traffic Assignment models can be categorized by various factors into several groups: Deterministic vs. stochastic, congestion considering vs. unconstrained capacity and being equilibrium or not. The main goal of this paper is a comparative and quantitative analysis of various Traffic Assignment Methods to estimate the observed Traffic volumes. In this regard, the main questions that this study seeks to answer is as follows: 1-Do the results of various Traffic Assignment Methods have a significant difference in terms of overall network indices? 2-Is there a significant difference in the accuracy of Traffic volume estimation in various Traffic Assignment Methods? In this study various Traffic Assignment Methods such as All-or-Nothing, Incremental, Stochastic, User Equilibrium, Stochastic User Equilibrium and System Optimum have been examined. To compare the results of Traffic Assignment Methods, in addition to estimated link volumes, various performance measures such as vehicle-kilometers traveled, vehicle-hours traveled, fuel consumption and air pollutants emission are also used. In this regard the city of Qazvin is selected as a case study. This city has more than 400 thousands inhabitant, near 46 square kilometers area, 113 Traffic analysis zone (TAZ) and its network has 2300 directional links and 1200 nodes. The results of applying these Methods in Qazvin city network show that various Traffic Assignment Methods based on User Equilibrium, despite different assumptions, have no significant difference in estimating the overall network performance measures as well as estimating Traffic volume in links (correlation between estimated and actual link volumes using all of these models is approximately 0. 88). But the other Methods, which do not consider equilibrium assumption and volume-delay functions, produce different results (correlation between estimated and actual link volumes using all of these models is approximately 0. 70). Although estimated link volumes in some of Traffic Assignment models are significantly different, overall network performance measures are approximately the same. In all of Assignment models the differences between estimated and actual link volumes in average are high which are not negligible (approximately 20 percent). In addition to high average error in estimating link volumes, the distribution of these errors has significantly high standard deviation (approximately 20 percent). In spite of different and complicated assumptions, models and solving algorithms in various Traffic Assignment Methods, on basis of Kolmogorov-Smirnov (K-S) test results, the distribution of links volume estimation error is not significantly different. According to this fact, it seems that should be careful in using the results of Traffic Assignment models to compare and assess minor network improvement alternatives, such as changing conventional streets function to pedestrian streets, upgrading intersections to interchanges, cross section widening, Traffic signals optimization and changing Traffic direction in streets.

This paper presents and compares two different Methods using in the forecasting of wind power turbine (WPT) outputs. These two forecasting Methods, which utilize different types of input to forecast the output of WPT, are the Meteorology Forecasting Method (MFM) and the Observational Forecasting Method (OFM). The MFM determines the unit output from the forecasted wind speed at the WPT installation site, using the input from a composite data set created from the original annual-hourly weather data. Three different techniques can be used in MFM to forecast the wind speed, and the best result is selected for conversion calculation of the output of WPT. OFM, however, forecasts the unit output based on five observed annual-hourly data obtained from the operation of target WPT. Two different techniques can be used in the OFM simulation. The results from these techniques for each method are compared and the best one will be used for the final forecast of the WPT outputs. This paper presents and compares the forecasting results of WPT output obtained from MFM and OFM. Furthermore, in order to increase the result precision and decrease the forecast error, a new composite data system is also developed and proposed.The methodologies proposed in this paper will be very useful for designers, planners and operators of the wind power turbines

One of the conventional Methods for improving the performance of transportation networks is building new highways, which is not considered nowadays as an effective alternative especially for congested urban areas. Using the intelligent transportation systems (ITS) for Traffic control and congestion reduction, as a powerful alternative, has attracted a lot of attention in the past two decades. Advanced traveler information systems (ATIS) are typical ITS applications which provide the travelers and the Traffic control system operators with information in order to enhance the safety and performance of roadway facilities. The basic requirement of implementing and applying such systems is the modeling of time-varying Traffic flows over the network. Therefore, there has been an extensive focus on developing the dynamic Traffic Assignment (DTA) models. The DTA models can capture the dynamic characteristics of the Traffic flow by predicting the pattern of time-varying flows, provided that the time-varying travel demands are given. In this paper, an analytical multi-class DTA model is proposed which defines temporal path-link incidence and path-link fraction variables to explain the relationship between the link and path flows and travel times. This model applies the BPR performance function, while confining link flows to the link capacities and considering link queuing delays by employing link capacity constraints. Also, an algorithm is developed which rapidly converges to the optimal solution for large scale problems. In addition, the algorithm uses dynamic penalty functions to deal with the capacity constraints, whereby the queuing delays for each link and each time interval can be easily calculated. The suggested algorithm is applied to the DTA test problem of Tehran network, showing that it is able to efficiently solve the problem. The application of the algorithm for evaluating some multi-class ITS policies in Tehran is also investigated. Finally, a comparison between the dynamic and static results reveals significant differences.

After applying the logit model as a route choice model in early stochastic Traffic Assignment algorithms, other models have been developed to overcome its theoretical weakness in considering path overlap. These models maintain the closed-form and computational convenience of logit, while not requiring simulation and computational efforts of probit. The purpose of this paper is to evaluate the most important of these models in comparison with each other. The models under consideration are Multinomial-logit (MNL) model, two modified MNL models called C-logit and PS-logit, and two models from the generalized extreme value family called cross-nested logit (CNL) and Paired-Combinatorial logit (PCL). These comparisons were performed at different levels of network congestion (origin-destination demand) and different values of perception variance of network users (scaling parameter) and were also compared with results of Deterministic Traffic Assignment. Results of a nine-node and the Nguyen network show that as the congestion level increases, general patterns of link flows of stochastic Assignments approach the Deterministic Assignment link flows, While the difference of these link flows in four models that consider the effect of path overlap increases compared to MNL model. Also, as the variance of user perceptions increases, the difference of link flows of stochastic Assignments relative to the MNL model and relative to the Deterministic Assignment increases. Besides, results of the studied models for the Sioux-falls network show that path flows in stochastic Assignments have much more entropy than the Deterministic Assignment, and therefore stochastic models produce more probable answers in this regard.

The Traffic Assignment problem in the transport networks is formulated as a convex optimization problem using simplifier assumptions. Link-based, path-based and bush-based algorithms have been presented to solve this problem, among which the link-based algorithm has found more applications thanks to its low memory requirements. The link-based algorithm of Frank-Wolf (FW) is yet amongst the most popular Assignment algorithms, because of its simplicity as well as high convergence speed during the initial iterations. However, the low convergence rate of this algorithm near the optimal solution has driven many studies that focus on modifying the FW search direction, resulted in newer link-based algorithms. Among them are conjugate direction algorithms which are more effective and simply implementable. These algorithms include PARTAN, conjugate FW (CFW) and bi-conjugate FW (BFW). This paper uses the Chicago Regional and Sioux-Falls test networks to make direct comparisons among these algorithms with respect to the CPU time and iteration number needed to reach various accurate solutions. The results for Chicago show that, compared with the FW algorithm, the three algorithms CFW, PARTAN increase the convergence speed to the relative error of 10-5 (i.e. a stable solution) by about 89, 72 and 63%, respectively, while only the BFW can reach to a 10-6 relative error. Comparing the results from Sioux-Fall with those of Chicago demonstrates that the performance of the conjugate directions Algorithms improves as network size decreases.

Traffic Assignment algorithms are used to determine possible use of paths between origin-destination pairs and predict Traffic flow in network links. One of the main deficiencies of ordinary Traffic Assignment Methods is that in most of them one measure (mostly travel time) is usually included in objective function, and other effective performance measures in Traffic Assignment are not considered. The current study is an endeavor to introduce a solution for this problem by applying a multi-objective optimization idea to Traffic Assignment models. To do this, a problem with three objective functions including travel time, total traveled distance and the rates of cabin monoxide emissions are studied first, and then problem with two objectives combining two well-known Assignment approaches i.e. user equilibrium and system optimal is introduced. Using the weighting method to solve the multi-objective problem, and comparing the results, show that the analytical relationships resulted from weighting method is applicable to different networks.Furthermore, comparison of both multi-objective and single-objective problems (travel time only) showed that the results of proposed model are more appropriate in terms of having a plenary view to this issue, and thus more useful.

In transportation literature, in order to relate supply (street network) and demand (Traffic zone) sides, definition of centroids and connectors is essential. Centroids and their connector(s), despite their importance, are usually selected based on the engineering judgment and experience of experts. The main purpose of this paper is to investigate the effect of centroid connection pattern on static Traffic Assignment. Applying user equilibrium approach, different scenarios of connector patterns (from centroids to all possible connector nodes) are implemented and evaluated for the real-size city of Qazvin with a population of about 0.4 million and 113 Traffic zones. Results of 6 different scenarios show that different patterns and number of connectors can result in about 10 percent change in average link volumes and about 20 percent change in total vehicle-kilometer. Results also indicate that due to the high number of connection patterns, it is difficult to specify the optimum pattern; this difficulty indicates the effects of connector pattern on Traffic Assignment results.

Inter-city transportation has major differences with urban transportation. These differences were reasons of using a different method in the present paper. Studying the manner of Traffic Assignment in roads of the country (especially those with highway and rural road together) and also analyzing driver's behavior, the obtained results showed that characteristics and attributes of ways have crucial impact on route choice. So, the models with utility functions were considered and Logit models were selected due to their popularity and usefulness in such cases. Another object, important in the development of Traffic Assignment model between highways and rural roads, was the role of the type of vehicle used on route choice. Therefore, in addition to the route choice method, impact of vehicle type was also considered, which lead to development of process and simultaneous models of vehicle - route. For development of the models some information were needed information, about route choice. These information should have been provided by the main users of roads, the drivers and their main reasons for their specific choices. For this reason a questionnaire was designed and distributed among drivers. On the basis of the collected data, several models were developed. The comparison between models showed that those models in which the vehicle type is chosen as the first parameter and the route is taken as the second parameter are more compatible in Iranian circumstances.

One of the traditional ways to improve the condition of the networks is the construction of new roads, which is not a desirable option today, especially in crowded urban areas due to the high cost of construction. One of the effective options in this regard is Traffic management Methods. The issue of Traffic Assignment, especially dynamic Traffic Assignment by providing a platform for examining the status of the network under study by providing a Traffic flow model is one of the important tools and components in the discussion of Traffic management. In this study, using a complete and general dynamic network loading method based on LWR network expansion model, the dynamic network loading problem is formulated as a system of differential algebraic equations that the resulting dynamic network loading model is able to form, propagate and lose physical queue. In this research, an algorithm based on the fixed point formula has been used to solve dynamic user equilibrium problems. Then the software package algorithm in C ++ language is defined to implement both systems of differential algebraic equations and the fixed point algorithm by considering the queue spillback. The program is developed in such a way that it can be used to solve dynamic user balance problems and load dynamic network in any large-scale network defined by the user. The C ++ program was implemented for the Chicago metropolitan area network with 86, 179 origin-destination pairs and 250, 000 routes, and after 69 repetitions, the convergence threshold was reached and the results were evaluated. Finally, the results of this study are evaluated and the accuracy of the results is shown.