Measuring and predicting the human mobility along the links of a transportation network has always been of a great importance to researchers in the field. Hitherto, producing such data relied heavily on expensive and time consuming surveying and on-field observational methods. In this work we propose an efficient estimation method for the assessment of the flow through links in transportation n...

This paper will look at the challenges involved in creating a scalable wireless network capable of collecting and distributing data from vehicles traveling at arbitrary speeds and locations through the current public transportation system. Observations will be made of available technologies that could be used to provide solutions for the problems that are outlined within this paper. We will als...

The airport transportation network structure and its performance are key factors to benefit the local area or national transportation capability and economic development. This paper presents a method based on the weighted algebraic connectivity to optimize and analyze the network. The indispensability of the weighted adjacent matrix and weighted Laplacian matrix in airport transportation networ...

Road transportation simulators are increasingly used by transportation stakeholders around the world for the analysis of intricate transportation systems. Model calibration is a crucial prerequisite for transportation simulators to reliably reproduce and predict traffic conditions. This paper considers the calibration of transportation simulators. The methodology is suitable for a broad family ...

A framework is presented which may be used to analyze and evaluate intermodal networks. An intermodal network can be defined as an integrated transportation system consisting of two or more modes. Modes on intermodal networks are connected through facilities which allow travelers and/or freight to transfer from one mode to another during a trip from an origin to a destination. The model may be ...

A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast literature on potential defaults including uniform priors, Jeffreys’ priors, reference priors, maximum entropy priors, and weakly informative priors. These methods, however, often manifest a key conceptual tension in prior modeling: a model encoding true prior information should be chosen without ...

Fixed charge solid transportation problem (FCSTP) is one of the main and most important problems in transportation and network research areas. To tackle such an NP-hard problem, An Electromagnetism-like algorithm (EM) is employed. To the best of our knowledge, EM has been considered for any kind of transportation problems. Due to the significant role of parameters on the algorithm’s performance...

Background & objectives: The urban rail transport network is always at risk due to its special conditions. Many cases indicate the existence of threatening and risk factors for human societies in urban rail transportation systems. Therefore, in this study, with the aim of identifying and prioritizing the risks of urban rail transportation networks in order to increase resilience is on the agend...

This paper proposes a convolution neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with high accuracy. Spatiotemporal traffic dynamics is converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. CNN is applied to the image following two consecutive steps: abstract traf...

Solving traffic equilibrium problem, or “traffic assignment”, as the last step in Transportation Planning, distributes OD trip demands of a transportation network over the network links with regard to Traffic Equilibrium Law, and estimates the link flows. In formulations of traffic equilibrium which are based on path saving, the memory consumption is considerably affected by the number of effct...