ITS Info-communications Forum

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Activities

+Symposium

+Fiscal 2005 ITS Info-communications System Symposium Report


+5. "Introduction to P-DRGS Research & Development Activities"
Akinori Sato, Assistant Supervisor, Technology Development Group, P-DRGS Consortium

Taro ISHI, Secretary General, Japan Organizing Committee for the  2004 Aichi-Nagoya ITS World Congress<Lecture Summary>
Professor Morikawa introduced the "P-DRGS (Probe-Dynamic Route Guidance System) Consortium", including an overview and planning. For my lecture, I will discuss the technical elements involved in developing P-DRGS.

A diverse range of technical elements is currently under development. From among them, I would like to introduce "DB (database) information accumulation technologies," "technologies for updating the DB based on real-time data," "road and rail route search technologies" for predicting trip time, "trip time correction using real-time rainfall information," for integrating weather information into data, and finally "developing vehicle-mounted devices" for evaluating vehicle-mounted systems.

The DB information accumulation technology used to predict trip times employed probe data from approximately 1,500 taxis operating in the city of Nagoya over a 10-month period in 2002 and 2003. The information was made into a database for expressing the average trip time in time units per link. A DB utilizing probe data was also assembled for showing the average trip time per effective link. This was formed using technologies for "screening out abnormal data," "setting optimal time widths" and "supplementing information with VICS (Vehicle Information Communications Systems) data".

There are two types of DB update technology that use real-time data. One type is technology that can "update with real-time probe data". This technology utilizes an autoregressive model to make predictions and update the data accumulated in the DB. The other technology utilizes JARTIC (Japan Road Traffic Information Center) data, and updates information accumulated in the DB using traffic congestion/jam information and other regulatory data.
A link cost update technology for searching out the optimal route was developed from among the road and rail path search technologies available. The route search is calculated while taking into account the lateral split cost on the link. Results revealed cases in which the shortest route was not the same when the lateral split cost was considered. A route search technique was also developed for use with train commutation. This approach uses the same algorithm as when making a road network search.

Integrating weather information and analyzing the difference between trip times during fair weather and trip times when it is raining revealed that trips when it is raining are approximately 5-7% longer than those taken at the time of fair weather. Other factors such as the rainfall intensity and time segments were also used in the analysis. A system for correcting the trip time using real-time rainfall information is also being configured.

The final stage concept of the P-DRGS consortium is aimed at delegating functions so that base information, such as a link cost table, is drawn up at the center and sent to the vehicle-mounted system in real time, where the route to be taken by the vehicle is created. However, the experimental system is configured so that vehicle-mounted processing is also performed at the center.

The P-DRGS center located in the Morikawa Research Lab of Nagoya University and My personal computer (PRONAVI user terminal which simulates a vehicle-mounted system) gives a real-time demonstration of the system via connections over the Internet. The information area is a two-dimensional mesh made up of a 25-grid area centered on the city of Nagoya, and the road network consists of 149,042 links and 57,827 nodes. This demonstration can compare access routes from a parking lot in Nagoya to the Aichi Expo when the expressway or ordinary roads. It can also compare routes when using public transportation systems such as the subway.

Future prospective ITS features include incorporating the above-mentioned technical elements under development into the system, developing new technologies for accumulating probe data, improving trip time prediction accuracy, combining our systems with eco-points and park-and-ride services, etc.

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