Traffic Message Channel (TMC) is a technology for delivering traffic and travel information to motor vehicle drivers. It is digitally coded using the ALERT C or TPEG protocol into Radio Data System (RDS) carried via conventional FM radio broadcasts. It can also be transmitted on Digital Audio Broadcasting or satellite radio. TMC allows silent delivery of dynamic information suitable for reproduction or display in the user's language without interrupting audio broadcast services. Both public and commercial services are operational in many countries. When data is integrated directly into a navigation system, traffic information can be used in the system's route calculation.
Detailed technical proposals for an RDS-TMC broadcasting protocol were first developed in the European Community's DRIVE programme research project RDS-ALERT, a partnership of the BBC, Philips, Blaupunkt, TRRL and CCETT led by Castle Rock Consultants (CRC). The main goal of the project was to develop and build consensus upon a draft standard for broadcasting RDS-TMC traffic messages in densely coded digital form.
An initial proposal for defining RDS-TMC data fields had been made to the European Conference of Ministers of Transport (ECMT) in Madrid, based on a scheme developed by CCETT and Philips in the Eureka-sponsored CARMINAT research project. This proposal required the use of at least two 104-bit RDS data groups for each message. Within these RDS Groups, 32 bits per group would be used for traffic data, giving a total traffic message length of 64 bits. A second proposal, by Bosch-Blaupunkt and the German Road Research Institute BASt, sought to use just a single RDS Group per traffic message. Then, in 1987, the CEC invited Castle Rock Consultants to lead a joint team that would take TMC development a stage further. CRC produced a proposal for a modified BASt/Blaupunkt single group message definition, which became known as the ALERT A coding scheme. Tests also continued at CCETT and BBC on the CARMINAT approach, which formed the basis of an alternative ALERT B coding proposal.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas an
An automotive navigation system is part of the automobile controls or a third party add-on used to find direction in an automobile. It typically uses a satellite navigation device to get its position data which is then correlated to a position on a road. When directions are needed routing can be calculated. On the fly traffic information (road closures, congestion) can be used to adjust the route.
Navteq (styled as 'NAVTEQ') was an American Chicago-based provider of geographic information system (GIS) data and a major provider of base electronic navigable maps. The company was acquired by Nokia in 2007–2008, and fully merged into Nokia in 2011 to form part of the Here business unit. The unit was subsequently sold to a consortium of German auto makers in 2016. Navteq's underlying map database is based on first-hand observation of geographic features rather than relying on official government maps.
Map database management systems are software programs designed to store and recall spatial information for navigation applications, and are thus a form of Geographic information system. They are widely used in localization and navigation, especially in automotive applications. Moreover, they are playing an increasingly important role in the emerging areas of location-based services, active safety functions and advanced driver-assistance systems.
We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...
This research is the result of four years of practical and scientific investigation of the phenomenon of traffic evaporation, which was considered and then demonstrated to be the opposite of traffic induction. It has anchored, in practice and in time, an o ...
EPFL2022
This dissertation introduces traffic forecasting methods for different network configurations and data availability.Chapter 2 focuses on single freeway cases.Although its topology is simple, the non-linearity of traffic features makes this prediction still ...