Graph Orientation and Flows Over Time

Flows over time are used to model many real-world logistic and routing problems. The networks underlying such problems -- streets, tracks, etc. -- are inherently undirected and directions are only imposed on them to reduce the danger of colliding vehicles and similar problems. Thus the question arises, what influence the orientation of the network has on the network flow over time problem that is being solved on the oriented network. In the literature, this is also referred to as the contraflow or lane reversal problem. We introduce and analyze the price of orientation: How much flow is lost in any orientation of the network if the time horizon remains fixed? We prove that there is always an orientation where we can still send $\frac{1}{3}$ of the flow and this bound is tight. For the special case of networks with a single source or sink, this fraction is $\frac12$ which is again tight. We present more results of similar flavor and also show non-approximability results for finding the best orientation for single and multicommodity maximum flows over time

Speed-related traffic accident analysis using GIS-based DBSCAN and NNH clustering

To ensure road safety and reduce traffic accidents, it is essential to determine geographical locations where traffic accidents occur the most. Spatial clustering methods of hot spots are used very effectively to detect such risky areas and take precautions to minimize or even avoid fatal or injury accidents. This study aims to determine speed-related hot spots in the pilot Mersin Region, which includes seven cities in the central-southern part of Turkey. Two different hot spot clustering methods, the Nearest Neighbourhood Hierarchical Clustering Method (NNH) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Method, were employed to analyse traffic accident data between 2014-2021, obtained from the General Directorate of Highways. CrimeStat III program, which is free software, was used to detect NNH clusters, while the DBSCAN clusters were obtained using the open-source GIS program QGIS, which was also used to visualize and evaluate the results comparatively. As a result of the analysis, it was determined which method gave more effective results in determining the traffic accident risk clusters. These clusters were analysed based on road geometries (intersection or corridors). In addition, by considering the areas where repeated accidents have occurred over the years, future predictions of traffic accidents have been estimated

Tabu-based heuristic approach for optimization of network evacuation contraflow

In urban evacuations, especially in response to an expected disaster, capacity reversibility (also known as contraflow) has been considered a workable strategy to reduce traffic congestion and to meet evacuation time deadlines. Currently, contraflow strategies are mostly planned by relying on engineering judgment because of the lack of appropriate large-scale decision support tools. A tabu search-based heuristic approach is introduced here that can be applied on realistic-size networks. The approach relies on insights from an analytical formulation of optimal reversibility design that reduces total system travel time. Computational results on a hypothetical and an urban network example network are presented and discussed

A method to estimate traffic penetration rates of commercial floating car data using speed information

Floating Car Data (FCD) are being increasingly used as an alternative traffic data source due to its lower cost and high coverage area. FCD can be obtained by tracking vehicle trajectories individually or by processing multiple tracks anonymously to produce average speed information commercially. For commercial FCD, the spatio-temporal distribution of these vehicles in actual traffic, traffic Penetration Rate (PR) is the most important factor affecting the accuracy of speed estimations, despite the high number of registered vehicles feeding to an FCD provider, denoting the market PR. This study proposes a method for assessing the traffic PR of commercial FCD by evaluating its speed estimation quality compared to Ground Truth (GT) data. GT speed data were employed to generate different levels of traffic PR using Monte Carlo (MC) simulations, which resulted in the development of Quality-PR (Q-PR) relations for Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) as selected Measures of Effectiveness (MoE). Simulation-based FCD results at an urban road segment in Ankara (Turkey) showed that a quality of FCD with traffic PR of 15% or more would improve significantly. Use of the developed Q-PR relations suggested an approximately 5% traffic PR for the commercial FCD speeds at the location

Quality of Floating Car Data (FCD) as a Surrogate Measure for Urban Arterial Speed

Commercial floating car data (FCD) is being increasingly used as a traffic data source due to its lower cost despite concerns about its reliability. This paper focuses on the evaluation of FCD speed quality as a surrogate measure for arterial speed from different aspects. First, FCD speed is compared to video-based traffic data, collected from a specific urban road segment and assumed as ground truth in (a) descriptive evaluations, (b) speed estimation, and (c) level of service estimation. Regression analysis carried out to derive transformation function between two datasets showed a nonlinear relation with a high correlation coefficient of 0.82. Working with data along an urban corridor of 3.6 km also showed that despite some outliers, FCD was capable of detecting peak-hour queue formations as well as incident related ones. Use of transformation function on FCD speeds helped to increase its potential in urban traffic monitoring.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Accessibility Of Touristic Destinations From High Speed Rail Stations

International audienc

ASSESSING THE LINK BETWEEN RAIL TRANSIT USAGE AND MULTIMODAL INTEGRATION

Current planning literature considers rail transit usage a function of neighborhood design (ND) parameters (such as density, diversity and connectivity) around station areas at a micro-level. However, during the early development stages of a rail transit system in a city, integration with the other modes may be equally influential on the rail transit usage, which must be determined. For this purpose, ridership data of 14 rail transit stations were evaluated based on both i) ND design parameters and ii) multimodal integration (MMI) parameters, along two existing urban rail corridors in Ankara, Turkey. A principal component analysis, as a part of quantitative analysis, suggested MMI as one of the three main components. Statistical regression model results also showed a clear relation between the ridership and MMI, which was clearer along the metro corridor, which serves suburban regions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

An assessment of the CO2 emissions reduction in high speed rail lines: Two case studies from Turkey

Transportation sector is one of the major emitters of greenhouse gases due to high consumption of fossil fuels in passenger and freight transportation. In recent years, high speed rail systems (HSR) have become an important policy option for intercity transportation in many countries, including Turkey, as they have relatively low emissions impact. Currently, the total HSR network in Turkey extends to 1213 km and connects 7 cities mostly located along a main HSR corridor. Annual ridership of the first two lines, Ankara-Eski ehir (ANK-ESK) and Ankara-Konya (ANK-KON), have reached almost 2 million passengers each, while total ridership in all four lines was about 3.5 million passengers in 2014. With the upcoming two new HSR lines, total length of HSR network will exceed 3000 km by 2020