Improving performance of pedestrian positioning by using vehicular communication signals

Pedestrian-to-vehicle communications, where pedestrian devices transmit their position information to nearby vehicles to indicate their presence, help to reduce pedestrian accidents. Satellite-based systems are widely used for pedestrian positioning, but have much degraded performance in urban canyon, where satellite signals are often obstructed by roadside buildings. In this paper, we propose a pedestrian positioning method, which leverages vehicular communication signals and uses vehicles as anchors. The performance of pedestrian positioning is improved from three aspects: (i) Channel state information instead of RSSI is used to estimate pedestrian-vehicle distance with higher precision. (ii) Only signals with line-of-sight path are used, and the property of distance error is considered. (iii) Fast mobility of vehicles is used to get diverse measurements, and Kalman filter is applied to smooth positioning results. Extensive evaluations, via trace-based simulation, confirm that (i) Fixing rate of positions can be much improved. (ii) Horizontal positioning error can be greatly reduced, nearly by one order compared with off-the-shelf receivers, by almost half compared with RSSI-based method, and can be reduced further to about 80cm when vehicle transmission period is 100ms and Kalman filter is applied. Generally, positioning performance increases with the number of available vehicles and their transmission frequency

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Urban management revolution: intelligent management systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated transparent and open decision making mechanism. The paper emphasises the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This paper introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The paper discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This paper also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities

Architectural and Urban Spatial Digital Simulations

This study concerns digital tools and simulation methods necessary for the description, conception, perception, and analysis of spatial architectural and urban design. The purpose of the study is to categorize, analyse, and describe the influence of digital simulation tools and methods in architectural and urban design. The study analyses techniques, applications, and research in the field of digital simulations of architectural/urban ensembles while also referring to the benefits of their use both at the level of scientific and spatial perception of architectural/urban design

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Multi-dimensional modelling for the national mapping agency: a discussion of initial ideas, considerations, and challenges

The Ordnance Survey, the National Mapping Agency (NMA) for Great Britain, has recently begun to research the possible extension of its 2-dimensional geographic information into a multi-dimensional environment. Such a move creates a number of data creation and storage issues which the NMA must consider. Many of these issues are highly relevant to all NMA’s and their customers alike, and are presented and explored here. This paper offers a discussion of initial considerations which NMA’s face in the creation of multi-dimensional datasets. Such issues include assessing which objects should be mapped in 3 dimensions by a National Mapping Agency, what should be sensibly represented dynamically, and whether resolution of multi-dimensional models should change over space. This paper also offers some preliminary suggestions for the optimal creation method for any future enhanced national height model for the Ordnance Survey. This discussion includes examples of problem areas and issues in both the extraction of 3-D data and in the topological reconstruction of such. 3-D feature extraction is not a new problem. However, the degree of automation which may be achieved and the suitability of current techniques for NMA’s remains a largely unchartered research area, which this research aims to tackle. The issues presented in this paper require immediate research, and if solved adequately would mark a cartographic paradigm shift in the communication of geographic information – and could signify the beginning of the way in which NMA’s both present and interact with their customers in the future

Geoinformation, Geotechnology, and Geoplanning in the 1990s

Over the last decade, there have been some significant changes in the geographic information available to support those involved in spatial planning and policy-making in different contexts. Moreover, developments have occurred apace in the technology with which to handle geoinformation. This paper provides an overview of trends during the 1990s in data provision, in the technology required to manipulate and analyse spatial information, and in the domain of planning where applications of computer technology in the processing of geodata are prominent. It draws largely on experience in western Europe, and in the UK and the Netherlands in particular, and suggests that there are a number of pressures for a strengthened role for geotechnology in geoplanning in the years ahead

Intelligent GNSS Positioning using 3D Mapping and Context Detection for Better Accuracy in Dense Urban Environments

Conventional GNSS positioning in dense urban areas can exhibit errors of tens of meters due to blockage and reflection of signals by the surrounding buildings. Here, we present a full implementation of the intelligent urban positioning (IUP) 3D-mapping-aided (3DMA) GNSS concept. This combines conventional ranging-based GNSS positioning enhanced by 3D mapping with the GNSS shadow-matching technique. Shadow matching determines position by comparing the measured signal availability with that predicted over a grid of candidate positions using 3D mapping. Thus, IUP uses both pseudo-range and signal-to-noise measurements to determine position. All algorithms incorporate terrain-height aiding and use measurements from a single epoch in time. Two different 3DMA ranging algorithms are presented, one based on least-squares estimation and the other based on computing the likelihoods of a grid of candidate position hypotheses. The likelihood-based ranging algorithm uses the same candidate position hypotheses as shadow matching and makes different assumptions about which signals are direct line-of-sight (LOS) and non-line-of-sight (NLOS) at each candidate position. Two different methods for integrating likelihood-based 3DMA ranging with shadow matching are also compared. In the position-domain approach, separate ranging and shadow-matching position solutions are computed, then averaged using direction-dependent weighting. In the hypothesis-domain approach, the candidate position scores from the ranging and shadow matching algorithms are combined prior to extracting a joint position solution. Test data was recorded using a u-blox EVK M8T consumer-grade GNSS receiver and a HTC Nexus 9 tablet at 28 locations across two districts of London. The City of London is a traditional dense urban environment, while Canary Wharf is a modern environment. The Nexus 9 tablet data was recorded using the Android Nougat GNSS receiver interface and is representative of future smartphones. Best results were obtained using the likelihood-based 3DMA ranging algorithm and hypothesis-based integration with shadow matching. With the u-blox receiver, the single-epoch RMS horizontal (i.e., 2D) error across all sites was 4.0 m, compared to 28.2 m for conventional positioning, a factor of 7.1 improvement. Using the Nexus tablet, the intelligent urban positioning RMS error was 7.0 m, compared to 32.7 m for conventional GNSS positioning, a factor of 4.7 improvement. An analysis of processing and data requirements shows that intelligent urban positioning is practical to implement in real-time on a mobile device or a server. Navigation and positioning is inherently dependent on the context, which comprises both the operating environment and the behaviour of the host vehicle or user. No single technique is capable of providing reliable and accurate positioning in all contexts. In order to operate reliably across different contexts, a multi-sensor navigation system is required to detect its operating context and reconfigure the techniques accordingly. Specifically, 3DMA GNSS should be selected when the user is in a dense urban environment, not indoors or in an open environment. Algorithms for detecting indoor and outdoor context using GNSS measurements and a hidden Markov model are described and demonstrated