ACM Home Page
Please provide us with feedback. Feedback
Dynamic travel time provision for road networks
Full text PdfPdf (201 KB)
Source
Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
POSTER SESSION: Poster session table of contents
Article No. 68  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Dieter Pfoser  RA Computer Technology Institute, Rion, Greece
Sotiris Brakatsoulas  RA Computer Technology Institute, Rion, Greece
Petra Brosch  Vienna University of Technology, Vienna, Austria
Martina Umlauft  Vienna University of Technology, Vienna, Austria
Nektaria Tryfona  Talent SA, Athens, Greece
Giorgos Tsironis  Talent SA, Athens, Greece
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 14,   Downloads (12 Months): 148,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1463434.1463513
What is a DOI?

ABSTRACT

The application domain of intelligent transportation is plagued by a shortage of data sources that adequately assess traffic situations. Typically, to provide routing and navigation solutions map attributes in the form of static weights as derived from road categories and speed limits used for road networks. With the advent of Floating Car Data (FCD) and specifically the GPS-based tracking data component, a means was found to derive accurate and up-to-date travel times, i.e., qualitative traffic information. FCD is a by-product in fleet management applications and given a minimum number and uniform distribution of vehicles, this data can be used for accurate traffic assessment and also prediction. This work showcases a system that facilitates the collection of FCD, produces dynamic travel time information, and provides value-added services based on the dynamic travel times. The essential components that will be discussed are a Web-services-based data collection approach, sophisticated map-matching algorithms, a data management architecture and an online visualization platform.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
H. Alt and M. Godau. Computing the Fréchet distance between two polygonal curves. Int. J. Comput. Geom. Appl., 5:75--91, 1995.
 
2
Austrosoft Weiss Datenverarbeitung Ges.m.b.H. Company homepage. http://www.austrosoft.net, current as of June 2008.
 
3
 
4
E. Brockfeld, P. Wagner, B. Passfeld, Bert. Validating travel times calculated on the basis of Taxi Floating Car Data with test drives. In Proc. 14th World Congress on Intelligent Transport Systems, 2007.
 
5
 
6
Dash Inc. Dash Express - Traffic powered by the Dash Driver Network. http://blog.dash.net/2008/03/18/dash-express-traffic-powered-by-the-dash-driver-network, current as of June 2008.
 
7
DLR. Cityrouter. http://www.cityrouter.net, current as of June 2008.
 
8
Google Inc. Google Maps. Web page http://maps.google.com, current as of June 2008.
 
9
INRIX Inc. Company homepage. http://www.inrix.com, current as of June 2008.
 
10
Microsoft Inc. Live Search Maps. http://maps.live.com, current as of June 2008.
 
11
 
12
 
13
R.-P. Schaefer, K.-U. Thiessenhusen, and P. Wagner. A Traffic Information System by Means of Real-time Floatingcar Data. In Proc. ITS World Congress, Chicago, USA, 2002.

Collaborative Colleagues:
Dieter Pfoser: colleagues
Sotiris Brakatsoulas: colleagues
Petra Brosch: colleagues
Martina Umlauft: colleagues
Nektaria Tryfona: colleagues
Giorgos Tsironis: colleagues