Traffic flow development at North European company level with respect of China and Russia

The aim of the thesis is to analyze traffic flows and its development from North European companies` point of view to China and Russia using data from logistics questionnaire. Selected North European companies are large Finnish and Swedish companies. The questionnaire was sent via email to the target group. The study is based on the answers got from respondent companies from years 2006, 2009 and 2010. In the thesis Finnish Talouselämä newspaper and Swedish Affärsdata are used as a database to find the target companies for the survey. Respondents were most often logistics managers in companies. In the beginning of the thesis concepts of transportation logistics is presented, including container types, trade terms, axel loads in roads and in railways. Also there is information about warehousing types and terminals. After that, general information of Chinese and Russian transportation logistics is presented. Chinese and Russian issues are discussed in two sections. In both of them it is analyzed economic development, freight transport and trade balance. Some practical examples of factory inaugurations in China and Russia are presented that Finnish and Swedish companies have completed. In freight transport section different transportation modes, logistics outsourcing and problems of transportation logistics is discussed. The results of the thesis show that transportation flows between Europe and China is changing. Freight traffic from China to European countries will strengthen even more from the current base. When it comes to Russia and Europe, traffic flows seem to be changing from eastbound traffic to westbound traffic. It means that in the future it is expected more freight traffic from Russia to Europe. Some probable reasons for that are recent factory establishments in Russia and company interviews support also this observation. Effects of the economic recession are mainly seen in the lower transportation amounts in 2009.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function

This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.

A novel map-matching procedure for low-sampling GPS data with applications to traffic flow analysis

An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.

TanDEM-X High Resolution DEMs and Their Applications to Flow Modeling

Lava flow modeling can be a powerful tool in hazard assessments; however, the ability to produce accurate models is usually limited by a lack of high resolution, up-to-date Digital Elevation Models (DEMs). This is especially obvious in places such as Kilauea Volcano (Hawaii), where active lava flows frequently alter the terrain. In this study, we use a new technique to create high resolution DEMs on Kilauea using synthetic aperture radar (SAR) data from the TanDEM-X (TDX) satellite. We convert raw TDX SAR data into a geocoded DEM using GAMMA software [Werner et al., 2000]. This process can be completed in several hours and permits creation of updated DEMs as soon as new TDX data are available. To test the DEMs, we use the Harris and Rowland [2001] FLOWGO lava flow model combined with the Favalli et al. [2005] DOWNFLOW model to simulate the 3-15 August 2011 eruption on Kilauea's East Rift Zone. Results were compared with simulations using the older, lower resolution 2000 SRTM DEM of Hawaii. Effusion rates used in the model are derived from MODIS thermal infrared satellite imagery. FLOWGO simulations using the TDX DEM produced a single flow line that matched the August 2011 flow almost perfectly, but could not recreate the entire flow field due to the relatively high DEM noise level. The issues with short model flow lengths can be resolved by filtering noise from the DEM. Model simulations using the outdated SRTM DEM produced a flow field that followed a different trajectory to that observed. Numerous lava flows have been emplaced at Kilauea since the creation of the SRTM DEM, leading the model to project flow lines in areas that have since been covered by fresh lava flows. These results show that DEMs can quickly become outdated on active volcanoes, but our new technique offers the potential to produce accurate, updated DEMs for modeling lava flow hazards.

Event-based time series data preprocessing: application to traffic flow time series

Traffic flow time series data are usually high dimensional and very complex. Also they are sometimes imprecise and distorted due to data collection sensor malfunction. Additionally, events like congestion caused by traffic accidents add more uncertainty to real-time traffic conditions, making traffic flow forecasting a complicated task. This article presents a new data preprocessing method targeting multidimensional time series with a very high number of dimensions and shows its application to real traffic flow time series from the California Department of Transportation (PEMS web site). The proposed method consists of three main steps. First, based on a language for defining events in multidimensional time series, mTESL, we identify a number of types of events in time series that corresponding to either incorrect data or data with interference. Second, each event type is restored utilizing an original method that combines real observations, local forecasted values and historical data. Third, an exponential smoothing procedure is applied globally to eliminate noise interference and other random errors so as to provide good quality source data for future work.

The development of UTCS/NETSIM/ICG: an integrated urban traffic control system - network simulation - interactive computer graphics program. Final report.

Transportation Department, Office of University Research, Washington, D.C.

Integrated traffic simulation model - phase I. Volume 4: revisions to the UTCS-1 traffic simulation model to enhance operational efficiency. Final report.

Federal Highway Administration, Washington, D.C.

Further investigation of traffic operations on two-lane, two-way rural highways. Research summary. Final report.

Federal Highway Administration, Washington, D.C.

Handbook of computer models for traffic operations analysis. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Handbook of computer models for traffic operations analysis - technical appendix: summary of models and references.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

Integrated traffic simulation model, phase, I. Volume 1: executive summary. Final report.

Federal Highway Administration, Washington, D.C.

Integrated traffic simulation model - phase I. Volume 2: design of the TRAF system (TOS). Final report.

Federal Highway Administration, Washington, D.C.