 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
TNO And INRIX Establish Technology And Research Alliance On European Predictive Traffic
Delft, Netherlands (SPX) Apr 24, 2008 Dutch research organization TNO, and INRIX, the leading provider of traffic information, are joining forces in the development and application of predictive traffic models throughout Europe. The companies are collaborating to enhance and deploy INRIX's state-of-the-art, real-time analysis engine to make highly accurate predictions about future traffic conditions for the ultimate benefit and use by government agencies, commercial organizations, and consumers throughout Europe. Reliable predictive traffic flow information can significantly decrease average travel times for individual drivers by as much as 15 percent. Additionally, national and regional governments can use predictive traffic information to increase the reliability of their road networks and provide additional tools to assist individual travelers in avoiding planned and unplanned traffic delays. "In seeking new markets for traffic predictions and traffic information, we found TNO's extensive knowledge of European traffic systems and markets, their role as leaders of innovation and research, and their experience with integrating GPS, sensor and cellular data into traffic models central to INRIX's European strategy," commented Craig Chapman, chief technology officer for INRIX. TNO's primary interest is developing new technology and to be closely involved in the application of this technology to both the commercial and public sectors. "INRIX's market-leading position in traffic data acquisition and operational algorithms, as well as their successful implementation across portals and automobile navigation services, will make it possible to enhance mobility on crowded Dutch and European roads," said Arie Bleijenberg, business unit manager mobility and logistics at TNO. INRIX and TNO's approach to predictive traffic is based upon developing an in-depth understanding of what traffic is like in each metropolitan area and within individual countries, and then determining the combination of factors that will influence future traffic patterns. Whether predictive travel times are for 30 minutes, a few hours or up to one year ahead, the technology intelligently combines input of commonly known traffic-impacting factors such as the current traffic conditions, day of the week, season, holidays, current and forecast weather, accidents and road construction, as well as other regional events such as sports games, concerts and other organized occasions with expected attendance of five thousand people or more. This allows the companies to make continually updated predictions conditioned on dynamic knowledge of current and future conditions. The unified strength of INRIX and TNO will result in new combinations of information that lead to better, more accurate and customized travel time predictions and travel alternatives ultimately leading to less congestion on European roads. Related Links TNO GPS Applications, Technology and Suppliers
Current Technology's Celevoke Expands GPS Tracking System's Marketing Reach
Vancouver, Canada (SPX) Apr 24, 2008Current Technology and MSGI Security Solutions have announced Texas-based Celevoke is participating in a series of Regional Heavy Equipment Theft Summits sponsored by, amongst others, FBI/LEEDA (Federal Bureau of Investigation/Law Enforcement Executive Development Association) and the NER (National Equipment Register). |
|
|
| The content herein, unless otherwise known to be public domain, are Copyright Space.TV Corporation. AFP and UPI Wire Stories are copyright Agence France-Presse and United Press International. ESA Portal Reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space.TV Corp on any Web page published or hosted by Space.TV Corp. Privacy Statement |
