DEM Embedding in GNSS-Based Navigation Using a Statistical Modeling

Given the boom linked to smart mobility, transport systems require increasingly precise and relevant navigation applications to offer optimized journeys in terms of time and energy consumption, such as for HEV. Most of these navigation applications are based on the processing of 2D digital road maps, while taking into account the GNSS location of vehicles. These localization systems also integrate sensors such as accelerometers and gyroscopes to overcome the well-known problems of GPS positioning, even if the current limited introduction of IoT in the transport industry has made it possible to develop new aided-GPS methods such as geofencing. This paper focuses on one important parameter in the journey optimization of land vehicles: the road slope. We propose a method to estimate the roads’ inclination parameters by fusing GNSS, INS, OSM and ASTER GDEM data through a nonlinear filter. The incremental estimate of the slope will complement the 2D modeling of the roads already available in OpenStreetMap and could be used in route planning optimization. The scientific novelty lies more specifically in the statistical map-matching approaches that we develop both for OSM and DEM data. Estimation results of the roads slopes are shown in experimental conditions.

CONSISTENCY IN REMOTE SENSING-BASED URBAN MAPPING FOR GROWTH AND MOBILITY ANALYSIS

This extended abstract presents initial results from a study that focus on the accuracy of satellite-based maps of Accra’s urban expansion as well as their comparability and ability to provide a basis for assessing urban spatial growth dynamics. Within the study we have analysed five different satellite-derived maps of urban development in Accra and compared the results and underlying methods. It is discussed how these maps can be operationalized and, combined with census data and digital road maps, used for calculating how flood events that disable parts of the transport infrastructure impact the overall mobility of the Accra population.

The Localisation Problem in Cooperative Vehicle Applications

The next paradigm towards enhancing vehicle safety and road transportation represent cooperative systems. Advances in computer and communications technologies are facilitating the establishment of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications links. This enables the sharing and aggregation of information which results in an extension of the driver awareness horizon in an electronic manner. In this chapter, V2V and V2I applications are considered as a spatio-temporal problem. The tenet is that sharing information can be made only if this is time stamped and related to a spatial description of the information sources. The chapter formulates the spatio-temporal problem having as constraint the precision of the pose estimates of the vehicles involved. It regards the localisation problem and accuracy of digital road maps as a combined issue that needs to be addressed for the successful deployment of cooperative vehicle applications. Two case studies, intersection safely and an overtaking manoeuvre are included. Recommendations on the precision limits of the vehicle pose estimations and the potential uncertainties that need to be considered when designing V2V and V2I applications complete the chapter.