A SPATIAL DATABASE MODEL FOR MOBILITY MANAGEMENT

Abstract. In urban and metropolitan context, Traffic Operations Centres (TOCs) use technologies as Geographic Information Systems (GIS) and Intelligent Transport Systems (ITS) to tackling urban mobility issue. Usually in TOCs, various isolated systems are maintained in parallel (stored in different databases), and data comes from different sources: a challenge in transport management is to transfer disparate data into a unified data management system that preserves access to legacy data, allowing multi-thematic analysis. This need of integration between systems is important for a wise policy decision.This study aims to design a comprehensive and general spatial data model that could allow the integration and visualization of traffic components and measures. The activity is focused on the case study of 5T Agency in Turin, a TOC that manages traffic regulation, public transit fleets and information to users, in the metropolitan area of Turin and Piedmont Region.The idea is not to replace the existing implemented and efficient system, but to built-up on these systems a GIS that overpass the different software and DBMS platforms and that can demonstrate how a spatial and horizontal vision in tackling urban mobility issues may be useful for policy and strategies decisions. The modelling activity take reference from a review of transport standards and results in database general schema, which can be reused by other TOCs in their activities, helping the integration and coordination between different TOCs. The final output of the research is an ArcGIS geodatabase, which enable the customised representation of private traffic elements and measures.</p

Road network comparison and matching techniques. a workflow proposal for the integration of traffic message channel and open source network datasets

The rapid growth of methods and techniques to acquire geospatial data has led to a wide availability of overlapping geographic datasets with different characteristics. Road network data sources are today a significant number, with high differences in level of detail and modelling schemas, depending on the main purpose. In addition, continuous information about people and freight movement is today available also in real-time. This type of data is today exchanged between traffic operators using referencing standards as Traffic Message Channel. Integrating these heterogeneous databases, in order to build an added value product, is a serious task in geographical data management. The paper is focus on techniques to conflate the Traffic message Channel logical network on Open Source road network dataset, in order to allow the precise visualisation of traffic data also in real-time. A first step of the research was the quality assessment of available Open Source (OS) road network dataset, then, a specific procedure to conflate data was set up, using an iterative process in order to reduce at every step the number of possible matching features. A first application of the enhanced OTM dataset is shown for the city of Turin: real-time open data of traffic flows recorded by road network fixed sensors, made available by the metropolitan Traffic Operation Centre (5T) and based on the TMC location referencing, are matched on the OTM road network, allowing a detailed real-time visualisation of traffic state

DEFINITION OF A METHODOLOGY TO DERIVE ROAD NETWORK FUNCTIONAL HIERARCHY CLASSES USING CAR TRACKING DATA

Road network functional hierarchy classifies individual roads into several levels, for efficient traffic management and road network generalization purposes. Automatic and semi-automatic road network extraction methods exist, but the generated products normally lack information on its functional hierarchy. This paper presents a methodology for automatically retrieve functional hierarchy for an OpenStreetMap derived road network from Floating Car Data, obtaining evenly distributed (e.g. for generalization purposes) or dynamic (e.g. to take into account differences in traffic volumes in different moments of the day) classifications. Road network elements are classified in function of vehicle speed values: the class distribution generated with the proposed methodology follows a linear distribution that can be better exploited for generalization purposes. Furthermore, the methodology allows to clearly distinguish different distributions in different moments of the day and days of the week, supporting traffic management activities

Floating car data (fcd) for mobility applications

Floating car data (FCD) is becoming more and more relevant for mobility domain applications, overcoming issues derived by the use of physical sensors (e.g. inductive loops, video observation, infrared and laser vehicle detection etc.), such as limited geographical distribution, measure inhomogeneities, limited or null coverage of minor roads. An increasing number of vehicles are equipped with devices capable of acquiring GPS positions and other data, transmitted in almost real-time to traffic control centres. Based on FCD data, several traffic analysis in support to mobility services can be performed: vehicle density, speed, origin-destination matrices, different patterns in function of vehicle type. If currently the representativeness of FCD can be considered an issue, current growing trend in FCD penetration should naturally overcome this issue. FCD are also higher sensitive to traffic events (e.g. traffic jams) than model-based approaches

SPATIO TEMPORAL DATA CUBE APPLIED TO AIS CONTAINERSHIPS TREND ANALYSIS IN THE EARLY YEARS OF THE BELT AND ROAD INITIATIVE – FROM GLOBAL TO LOCAL SCALE

Maritime trade represents a significant part of all global import-export trade. The traffic of containerships can be monitored through Automatic Identification System (AIS), due to the fact that the International Maritime Organization (IMO) regulation requires AIS to be fitted aboard all ships of 300 gross tonnage and upwards engaged on international voyages. The approach proposed by the authors aimed to extract value added information from an AIS dataset, with a focus on maritime economy. Using an AIS dataset of global position of containerships from 01/01/2012 to 31/12/2016, the paper focuses on space-time data cube creation and analysis for a better understanding of maritime trades trends. Data cube creation has been tested at different spatio-temporal bins dimension and on different specific topics (TEU classes, alliances, chokepoints and port areas), analysing the sensitivity on trend results, and highlighting how appropriate spatio-temporal bins dimensions are important to effectively highlight relevant trends. Results of the trend analysis are discussed and validated with the main data and information found over the period 2012–2016. The aim of this paper is to demonstrate the suitability of this approach applied to AIS data and to highlight its limitations. The authors can conclude that the approach used has proved to be adequate in describing the evolution of the global import-export trade

Geospatial reference data access for emergency response: data inventory and quality assessment

Proceedings on C

Cooking pots, tableware, and the changing sounds of sociability in Italy, 1300–1700

This article considers how the sounds produced by the preparation and consumption of meals in Italy changed between around 1300 and 1700. It argues that by focusing on sound, and by using ecological approaches, we can rediscover obscured connections between different categories of material objects. By examining material and textual evidence for three categories of objects associated with cooking and dining – metalwork, ceramics, and glass – the article traces changes in the material cultures of kitchen and table, and the clear impact these changes had on domestic soundscapes. It considers these sound-producing objects as agents of social interaction, exploring the social relationships they constructed, and the role sound played in those relationships. The article then focuses on the practices of cooking and dining, and the way they shaped the sound of objects. Finally, the article situates objects and social practices within the spatial context of the home, tracing an increasing impetus to manage and control specific types of sound in relation to gender. In the discourse on hospitality, noise came to signify a badly-managed, and therefore morally dubious, household, while silence testified to decorous and authoritative domestic management