Classification of Livebus arrivals user behavior

With the increasing use of Intelligent Transport Systems, large amounts of data are created. Innovative information services are introduced and new forms of data are available, which could be used to understand the behavior of travelers and the dynamics of people flows. This work analyzes the requests for real-time arrivals of bus routes at stops in London made by travelers using Transport for London's LiveBus Arrivals system. The available dataset consists of about one million requests for real-time arrivals for each of the 28 days under observation. These data are analyzed for different purposes. LiveBus Arrivals users are classified based on a set of features and using K-Means, Expectation Maximization, Logistic regression, One-level decision tree, Decision Tree, Random Forest, and Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO). The results of the study indicate that the LiveBus Arrivals requests can be classified into six main behaviors. It was found that the classification-based approaches produce better results than the clustering-based ones. The most accurate results were obtained with the SVM-SMO methodology (Precision of 97%). Furthermore, the behavior within the six classes of users is analyzed to better understand how users take advantage of the LiveBus Arrivals service. It was found that the 37% of users can be classified as interchange users. This classification could form the basis of a more personalized LiveBus Arrivals application in future, which could support management and planning by revealing how public transport and related services are actually used or update information on commuters.     

A list of accident scenarios for three legs skewed intersections

The term ‘scenario’ is used in the safety field to designate a prototype or a model of an accident process characterised by chains of facts, actions, causal relations and consequences in terms of damage to people and property. The prototypical scenarios, properly realized, provide a basis on which to consider the action to be taken, but also a concrete backup for accident information for use in information campaigns or training. The objective of this study is to define the prototypical accident scenarios for a particular configuration of road intersection: the skewed intersection. Limited sight distance at skewed intersections leads to safety issues. A non-skewed intersection provides the best operating conditions as drivers can easily sense the direction in which they are travelling, estimate the speeds of the opposing traffic and smoothly complete a maneuver in shorter time. In skewed intersections, instead, the ability of drivers to recognize any conflicting vehicles diminishes in comparison to right-angle intersections. The logical-deductive approach used in this paper for the determination of accident scenarios is based on an analysis of a large database of incidents, which occurred on several roads in eastern Sicily on 35 skewed intersections at three-legs. The skew angle of the minor leg of all the intersections studied is between 15° and 20°. This research allowed to develop accident scenarios related to particular configurations of intersections, compatible with the Italian rules. Prototypical scenarios are constructed using samples of accidents occurring on a particular type of study area, especially when they are based on files from in-depth investigations. The method used is an inductive approach, based on an examination of each case, grouping together similar cases and building a prototypical scenario using this case grouping. From the in-depth analysis of database accidents 9 prototypical accident scenarios have been identified for the skewed intersections.     

Factors with the greatest influence on drivers' judgment of roundabouts safety. An analysis based on web survey in Italy

The aim of this paper is to identify the roundabout geometric characteristics affecting the safety perception while the typical maneuvers (entry, circulation, exit) are being carried out. The tool used was an on-line questionnaire, filled out by about 1.650 respondents. Four different dimensionality reduction methods (Cluster Analysis, Correspondence Analysis, Exploratory Factor Analysis and Confirmatory Factor Analysis) were used to analyze the data collected from the survey, in order to examine the key factors affecting the safety perception during the typical roundabout maneuvers. The considerations arising from the final model are the following: 1) the respondents' opinions regarding the safety perception of maneuvers are not preconceived ideas, but they originate from specific safety perceptions due to roundabout geometric configurations; 2) the users prefer definitely single lane roundabouts; this is an important confirmation of most results in the literature; 3) it was quantified the extent of the relationship between the safety perception of the typical roundabout maneuvers and the following aspects: a) maneuver type, b) geometric characteristics of the roundabouts design elements. This is the innovative aspect of the present research whose results have implications regarding theory, infrastructure and the application of new safety technologies.     

Carbonate chemistry dynamics and carbon dioxide fluxes across the atmosphere–ice–water interfaces in the Arctic Ocean: Pacific sector of the Arctic

Climatic changes in the Northern Hemisphere have led to remarkable environmental changes in the Arctic Ocean, which is surrounded by permafrost. These changes include significant shrinking of sea-ice cover in summer, increased time between sea-ice break-up and freeze-up, and Arctic surface water freshening and warming associated with melting sea-ice, thawing permafrost, and increased runoff. These changes are commonly attributed to the greenhouse effect resulting from increased atmospheric carbon dioxide (CO₂) concentration and other non-CO₂ radiatively active gases (methane, nitrous oxide). The greenhouse effect should be most pronounced in the Arctic where the largest air CO₂ concentrations and winter–summer variations in the world for a clean background environment were detected. However, the air–land–shelf interaction in the Arctic has a substantial impact on the composition of the overlying atmosphere; as the permafrost thaws, a significant amount of old terrestrial carbon becomes available for biogeochemical cycling and oxidation to CO₂. The Arctic Ocean's role in determining regional CO₂ balance has been ignored, because of its small size (only  4% of the world ocean area) and because its continuous sea-ice cover is considered to impede gaseous exchange with the atmosphere so efficiently that no global climate models include CO₂ exchange over sea-ice. In this paper we show that: (1) the Arctic shelf seas (the Laptev and East-Siberian seas) may become a strong source of atmospheric CO₂ because of oxidation of bio-available eroded terrestrial carbon and river transport; (2) the Chukchi Sea shelf exhibits the strong uptake of atmospheric CO₂; (3) the sea-ice melt ponds and open brine channels form an important spring/summer air CO₂ sink that also must be included in any Arctic regional CO₂ budget. Both the direction and amount of CO₂ transfer between air and sea during open water season may be different from transfer during freezing and thawing, or during winter when CO₂ accumulates beneath Arctic sea-ice; (4) direct measurements beneath the sea ice gave two initial results. First, a drastic pCO₂ decrease from 410 μatm to 288 μatm, which was recorded in February–March beneath the fast ice near Barrow using the SAMI-CO₂ sensor, may reflect increased photosynthetic activity beneath sea-ice just after polar sunrise. Second, new measurements made in summer 2005 beneath the sea ice in the Central Basin show relatively high values of pCO₂ ranging between 425 μatm and 475 μatm, values, which are larger than the mean atmospheric value in the Arctic in summertime. The sources of those high values are supposed to be: high rates of bacterial respiration, import of the Upper Halocline Water (UHW) from the Chukchi Sea (CS) where values of pCO₂ range between 400 and 600 μatm, a contribution from the Lena river plume, or any combination of these sources.     

Mathematical characterization of spatiotemporal congested traffic patterns: mixed speed data analysis in the greater Toronto and Hamilton area,Canada

This paper formulates a comprehensive methodology for analyzing, quantifying and identifying congestion characteristics based on speed distribution. Utilizing vehicle speed data, a mathematical approach is applied, in order to characterize roadway segments, in terms of travel reliability, congestion severity and duration. We argue that the Gaussian mixture model (GMM) and its parameter combination is the appropriate tool if we are to obtain quantitative congestion measures and rank roadway performance. A significant contribution of our approach is that it is based on assumptions regarding mixed components as well as speed distribution and can be applied to large databases. We test our framework on the greater Toronto and Hamilton area in Ontario, Canada, and conclude that congestion quantification through the application of the GMM can be successfully accomplished. Results indicate that speed patterns differ significantly between counties as well as days of the week.