Much of the development surrounding autonomous driving has been focused on automating the mundane tasks of highway driving – maintaining speed and lanes, for example, and interacting smoothly with traffic around you – but a key goal is safety and that’s nowhere better illustrated than in congested conditions such as city traffic.
That’s where the German initiative UR:BAN (Urbaner Raum: Benutzergerechte Assistenzsysteme und Netzmanagement or, literally, Urban Space: User Assistance Systems and Network Management) hopes to make its biggest impact on future driving safety.
UR:BAN is a series of projects undertaken by 31 partners (including automobile manufacturers and suppliers such as Audi, BMW, Bosch, Continental, Daimler, Opel, TomTom and Volkswagen) to develop advanced driver assistance and traffic management systems for cities, with the focus on the human element in all aspects of mobility and traffic.
The research objectives are broken down into three main areas – cognitive assistance, networked traffic system and human factors in traffic – with each broken down further into specific items.
Cognitive Assistance, or City Safety, aims to improve protection of vulnerable road users such as pedestrians and cyclists by predicting their behaviours and movements. By developing novel panoramic sensor technologies (such as proximity sensors, radar, lasers and cameras), future cars and trucks would be able to automatically brake or swerve more quickly, as needed in congested, reduced-reaction-time conditions. Among the areas researched and developed are measurement and modeling of the road environment, protection of vulnerable road users, automatic collision avoidance, safe lateral and longitudinal vehicle control, and effectiveness, assessment, and legal issues.
Networked Traffic System, or Economic and Energy Efficient Driving, involves connectivity technologies such as GPS, LTE and C2X to connect road users to road and traffic infrastructures. The networking of intelligent vehicles with future advanced driver assistance systems will enable the implementation of instructions and advisories to the benefit of traffic management, allowing vehicles to navigate more effectually, use energy more efficiently and reduce emissions more effectively in urban areas. This area of research targets regional road networks, urban roads, smart intersections and cooperative infrastructure for development of coordinated traffic lights, real time information of traffic congestion with route options, and interaction and coordination between vehicle and traffic management systems.
Human Factors in Traffic, or Anticipatory and Stress-Free Driving, aims to provide important information to drivers without overloading them. There are two facets to this research – determining the driver’s state of attentiveness and providing appropriate information in a timely manner – with the ultimate goal of having drivers anticipate traffic situations rather than simply reacting to them as they arise, thus reducing the level of stress while driving in stress-filled situations. Among the areas of research are human/machine interaction in the urban environment, behaviour prediction and intention detection, simulation, and controllability.
The Germany-wide UR:BAN cooperative project has been running since 2012 and is scheduled to run through winter of 2016, and has received some 40 million Euros (roughly $59 million Canadian) from the country’s Federal Ministry of Economics and Energy