on-board automotive computers could interact with traffic lights in the future
By Mike Hanlon
June 17, 2005
June 18, 2005 Though rush hour grows more intensive every year, the number of cars on the roads is still increasing and with emerging nations such as China and India on the brink of an automotive boom, research is developing intelligent systems to prevent traffic from grid locking completely in the future. A recent invention in the area of driver assistance systems is based on communication between vehicle and infrastructure (traffic lights). For example, in the future, speed recommendations could be transmitted to a vehicle as it approaches an intersection, enabling it to reach an optimum speed and make the best possible use of phased traffic light systems. Functions for monitoring the immediate vicinity of an intersection could also be particularly useful. Drivers can be warned of an increased accident risk in cases where it looks like another road user is likely to jump a red light because of excessive speed.
Despite the growing intensity of daily rush-hour traffic jams, the number of cars in Germany will continue to increase. At the same time, emerging nations such as China are on the brink of an automotive boom. Researchers are already developing intelligent traffic systems to prevent traffic from grid locking completely in the future. These systems are aimed at keeping the traffic moving smoothly and safely, particularly in heavily built-up areas.
Since 1997, Dr. Paul Mathias, a mathematician with Siemens Industrial Solutions and Services (I&S) Group, has filed patent applications for 13 inventions that have advanced the development of traffic systems and paved the way for further innovations.
A recent invention in the area of driver assistance systems is based on communication between vehicle and infrastructure. Control and warning functions exchange data between vehicles and traffic lights, thus making driving in inner-city areas easier and safer. For example, in the future, speed recommendations could be transmitted to a vehicle as it approaches an intersection, enabling it to move through green lights or make the best possible use of phased traffic light systems. Functions for monitoring the immediate vicinity of an intersection are also particularly useful. Drivers can be warned of an increased accident risk in cases where it looks like another road user is likely to jump a red light because of excessive speed.
“Infrastructure operators could also benefit considerably from this kind of system,” said Mathias. “Standardized vehicle log-on processes with assigned priorities can be used in addition to or as an alternative to conventional traffic detection to provide a more transparent picture of the traffic flow and enable more effective traffic control.” Siemens plans to install and test prototypes of such systems in German cities over the next few years as part of European and national research projects.
One of Dr. Mathias’ designs is currently being implemented in the German research project INVENT, a cooperative venture involving Siemens and a host of prestigious research institutes and companies such as BMW, DaimlerChrysler, Ford and Bosch. Siemens’ part of the project focuses on using complex traffic models to obtain up-to-date traffic information and make predictions for entire road networks in cities or conurbations. The road system itself is being treated as a “recurrent neural network” in which the individual roads are seen as neurons and the vehicles on the roads as nerve pulses. The process developed on the basis of this theory, NEUROMONET, will be used over the next few months to compute traffic information online and forward it to dynamic routing services for the entire city of Magdeburg.
Dr. Mathias’ innovations could make driving safer in the future and could also lay the foundation for even more efficient traffic control. The novel interaction between on-board computer and traffic lights provides significantly more detailed information about the traffic flow than is now available, and can serve as the basis for a tailored traffic management system that relieves congestion in urban areas, preserves the environment and enhances safety.
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