Digital map data compression techniques

1984 ◽  
Author(s):  
P. POEHLER
2012 ◽  
Vol 256-259 ◽  
pp. 2279-2284
Author(s):  
Lian Ying Li ◽  
Zhang Huang ◽  
Xiao Lan Xu

A necessary updating degree is vital for the digital map data in a vehicle navigation system. Only when the digital map data are well updated, can the quality of the navigation be assured. Today the companies devoting to the production of digital map data for vehicle navigation have to cost much labor, material and capital to collect and update data in order to maintain a necessary updating degree. Throughout the history of electronic navigation data updating, they have made considerable progress both on the methods and processes of data production, and the way of map management. Updating from the CD to the network, from the wired to the wireless, from the replacing to the incremental way, each of the technical changes is a power source to enhance the data updating rate. As we all know, the change detection is a prerequisite and base for the electronic navigation data updating. By rapidly developing the area with changes and using the appropriate updating method, we can scientifically maintain the original database of navigation data and terminal physical data. In view of this, starting from application needs for dynamic data updating, this paper analyses change detection methods of navigation data in different versions used for generating incremental data, and focuses on that of rasterizing features and attributes, exploring a new approach to quickly get the incremental data between versions.


2005 ◽  
Vol 58 (2) ◽  
pp. 257-271 ◽  
Author(s):  
Mohammed A. Quddus ◽  
Robert B. Noland ◽  
Washington Y. Ochieng

Map Matching (MM) algorithms are usually employed for a range of transport telematics applications to correctly identify the physical location of a vehicle travelling on a road network. Two essential components for MM algorithms are (1) navigation sensors such as the Global Positioning System (GPS) and dead reckoning (DR), among others, to estimate the position of the vehicle, and (2) a digital base map for spatial referencing of the vehicle location. Previous research by the authors (Quddus et al., 2003; Ochieng et al., 2003) has developed improved MM algorithms that take account of the vehicle speed and the error sources associated with the navigation sensors and the digital map data previously ignored in conventional MM approaches. However, no validation study assessing the performance of MM algorithms has been presented in the literature. This paper describes a generic validation strategy and results for the MM algorithm previously developed in Ochieng et al. (2003). The validation technique is based on a higher accuracy reference (truth) of the vehicle trajectory as determined by high precision positioning achieved by the carrier-phase observable from GPS. The results show that the vehicle positions determined from the MM results are within 6 m of the true positions. The results also demonstrate the importance of the quality of the digital map data to the map matching process.


1993 ◽  
Vol 46 (2) ◽  
pp. 208-222 ◽  
Author(s):  
Peter J. Bennett

A GEC Marconi Avionics/MoD joint–funded integrated, digital terrain system called ' PENETRATE ' (passive enhanced navigation with terrain referenced avionics) is in its fourth year of flight trials on a Hunter fast–jet aircraft at the Defence Research Agency, Farnborough. Although originally designed to enable military aircraft to penetrate enemy defences at low level in poor weather conditions and at night, the system also has a direct read across to civil air transport operations. The heart of the PENETRATE system is a digital data–store housing a three–dimensional model of the terrain including cultural details, obstructions and tactical intelligence information.PENETRATE incorporates terrain-referenced navigation to provide accurate position information relative to the ground contours. A sophisticated digital map displays navigation information and includes intelligence and intervisibility overlays. Head-up visual enhancement options are provided which can be tailored to the outside visibility. These comprise monochrome skeletal perspective displays which are superimposed on the outside world view and also on the forward-looking infra-red (FUR) scene. The display enhancements range from obstruction cues through ridge line overlays to skeletal perspective terrain presentations.This paper covers the philosophy and architecture of PENETRATE together with details of the demonstration system. It also discusses the capability of this digital terrain system to enhance the safety of civil aircraft approaches into difficult airports such as Kathmandu and Hong Kong.


2021 ◽  
Vol 13 (17) ◽  
pp. 9724
Author(s):  
Philipp Luz ◽  
Li Zhang ◽  
Jinyue Wang ◽  
Volker Schwieger

To prevent terror attacks in which trucks are used as weapons as happened in Nice or Berlin in 2016, the European Project Autonomous Emergency Maneuvering and Movement Monitoring for Road Transport Security (TransSec) was launched in 2018. One crucial point of this project is the development of a map-aiding approach for the localization of vehicles on digital maps, so that the information in digital map data can be used to detect prohibited driving maneuvers, such as off-road or wrong-way drivers. For example, a lane-level map-aiding approach is required for wrong-way driver detection. Navigation Data Standard (NDS) is one of the worldwide map standards developed by several automobile manufacturers. So far, there is no lane-level NDS map covers a large area, therefore, it was decided to use the latest available NDS map without lane level accuracy. In this paper, a lane-level map-aiding approach based on a non-lane-level NDS map is presented. Due to the inaccuracy of vehicle position and digital map the map-aiding does not always provide the correct results, so probabilities of off-road and wrong-way diver detection are estimated to support risk estimation. The performance of the developed map-aiding approach is comprehensively evaluated with both real and simulated trajectories.


2021 ◽  
Author(s):  
J.E. Andrew

<div>Digital map data files in ArcGIS shapefile format for data collection points, geologic contacts, and geologic unit polygons.<br></div>


Author(s):  
Suk-Hwan LEE ◽  
Won-Joo HWANG ◽  
Jai-Jin JUNG ◽  
Ki-Ryong KWON
Keyword(s):  

2007 ◽  
Vol 21 (11) ◽  
pp. 1436-1447 ◽  
Author(s):  
David C. Mason ◽  
Matthew S. Horritt ◽  
Neil M. Hunter ◽  
Paul D. Bates

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