5/14/2014 | 1 MINUTE READ

Alliance Touts Role in German Mobility Projects

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BMW AG and 31 other companies, research institutes and cities have presented midterm results of a five-year research effort to develop sustainable mobility options.

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BMW AG and 31 other companies, research institutes and cities have presented midterm results of a five-year research effort to develop sustainable mobility options.

The program is called UR:BAN, a German acronym for urban space: user-oriented assistance systems and network management. The effort, which runs through 2016, is funded by Germany's Federal Ministry of Economics and Energy.

The alliance has focused on three broad issues: cognitive assistance, networked traffic systems and human factors in traffic:

Cognitive Assistance. BMW and Technik GmbH are developing algorithms that would enable a vehicle to detect and analyze the behavior of pedestrians in complex urban situations, then direct the car to automatically use steering and/or braking to avoid a collision. Their goal is to create a single set of algorithms that can be used by multiple driver assist systems to assess a vehicle's environment 360 .

The partners note that a successful system must be able to construct and continuously update a complete picture of its surroundings and correctly interpret "complex situations involving many different protagonists and boundary conditions."

Networked Traffic System. BMW and other UR:BAN participants are developing a "green coordination and deceleration assistant" that reads traffic flow and controls the timing of traffic lights accordingly. BMW notes that using such a system to smooth traffic flow would maximize the efficiency of all vehicles regardless of their propulsion system.

In preliminary tests, researchers showed how traffic control centers could channel data between vehicles and the traffic infrastructure. Later this year the concept will be tested at facilities and Dusseldorf and Kassel.

Human Factors in Traffic. One project in this area is attempting to create a standardized way to assess the efficiency of driver-operated controls in the vehicle, especially in time-critical conditions. A second project aims to develop technology to detect a driver's intentions as quickly as possible so the vehicle's assistance systems can better offer relevant suggestions.