|
|
| content name: |
|
| |
In April 2007, Centrum dopravního výzkumu, v.v.i. was appointed to
coordinate a project CONGMAN – Effective traffic flow management of congestions on
motorways and dual carriageways with the use of ITS. The project is assigned by the
Ministry of Transport of the Czech Republic as a R&D project. In the first stage of the
project, the research team (CDV, Brno University of Technology, and HIT Hofman
s.r.o.) has developed an intelligent transport system for effective traffic flow
management in bottlenecks. The main attention will be paid to the issue of “zipping”
and to ways to manage traffic flow, so that the road capacity is used in its maximum;
and undesirable behaviour of some drivers who unconsciously contribute to queues
occurrence at narrow sites (either at the sites of road accidents or at roadwork sites) is
prevented. CDV has won the project in cooperation with FWHA (Federal highway of
administration – USA road administrator) in project “Bottleneck. This project is aim to
exchange know-how about the “smart work zone” projects. In start of April this
presented system supposed be transfer to USA. FHWA would like to see this system in
progress. Expecially they are interested in ENVIRO system in cooperation with portable
LED system in cooperation. The issue of this document is to offer of possible cooperation
between the CDV and FARDATA company in testing in USA. |
| |
|
| content link: |
http://www.cdv.cz |
| |
|
| content language: |
English |
| English summary: |
yes |
|
|
|
| This content is related to: |
|
| |
| project type |
| National projects |
|
| area of interest |
| SAFETY & SECURITY |
|
| user type |
| road authorities/owners |
|
|
| Other similar contents:
The similarity algorithm calculates how much two contents in the system are similar to one another. So far, similarity is calculated based on similarity of the project type, area of interest and user type. Generally, if two contents have more parameters in common they are more similar to each another. More information.
|
|
| content |
description |
similarity (%) |
|
|
|
