|Countries: Germany||? test users|
|30 partners||? vehicles|
|Active from 2012 to ?|
|Federal Ministry of Economicas and Technology of Germany|
|Data catalogue||Tools catalogue|
|Data sets used in this FOT:
||The following tools|
were used in this FOT:
Thirty partners including automobile and electronics manufacturers, sup - pliers, communication technology and software companies, as well as research institutes and cities, have joined in the cooperative project UR:BAN to develop advanced driver assistance and traffic management systems for cities. The focus is on the human element in all aspects of mobility and traffic. The research objectives will be pursued in three main thematic target areas
Project “Cognitive Assistance” (KA)
The focus of the project is improvement of safety in urban traffic in complex situations such as intersections with pedestrian movements and bicycle traffic, narrow or obstructed streets, conflicts with op pos - ing traffic and lane changing. Novel technologies now support panoramic sensing capabilities, which allow an evaluation of space available for possible lateral avoidance (swerving) maneuvers. Thus, collisions can be avoided not only by automatic braking, but also by swerv ing as required. All these challenges will be supported by studies of legal issues and effectiveness evaluation.
Previous research projects have concen - trated on improvement of safety on freeways and other limited-access highways. These have led to a variety of advanced driver as - sistance systems such as following distance warnings, night vision, lane keeping, blind spot monitoring and traffic sign detection, which are already available and are successively helping to reduce accidents on high - ways.
However, these systems have not been implemented for urban use, so that there is still a need for activities to reduce the number and severity of accidents in urban traffic. Complex scenarios, such as heavy traffic, confusing intersections, merges and lane changes into small gaps, or partially blocked lanes pose difficult and hitherto unsolved challenges for cognitive assistance systems. Thus, methods for longitudinal and lateral (steering) control that have been successful implemented in freeway traffic need to be considerably extended and refined for urban traffic.
In particular, measurement of the surround - ing environment poses exceptional demands regarding reliability and precision. The main new challenge is the high density and variety of objects in urban environments.
The following areas will be investigated in depth by the cooperation partners in the five KA subprojects:
Measurement and modeling of vehicle surroundings: Robust perception, modeling, and interpretation of complex traffic movements as a pre-requisite for use of safety relevant advanced driver assistance functions in urban areas.
Protection of vulnerable road users: Development of cognitive and user-friendly driver as - sistance systems for effective, anticipatory protection of vulnerable road users in urban areas.
Collision avoidance by braking and swerving: Cognitive assistance systems in urban areas to support accident avoidance maneuvers such as braking and swerving.
Safe lateral and longitudinal vehicle control in urban areas: Decrease burden on driver in narrow urban streets by timely information on available lateral clearance and by continuous lateral and longitudinal control support.
Areas of effective application, legal issues: Comprehensive assessment of cognitive assistance sys - tems for urban areas concerning potential, effectiveness, and legal requirements.
Project “Networked Traffic System” (VV)
Development of applications for energy and traffic efficient driving in urban areas is the focus of the project VV. The aim is to find new approaches to solution of the following scientific and technical issues: > Measurement of complex urban situations for information and assistance systems supporting energy and traffic efficient, comfortable and safe mobility
> Determination of requirements posed by vehicles with alternative power sources and optimization with respect to these special requirements
> Infrastructure control and networking with innovative vehicle concepts and systems
> Complex network control with aim of satisfying new demands on mobility in the post-fossil fuel era.
The project aims to optimize traffic efficiency in urban areas while lowering emissions. This aim is to be achieved by deploying intelligent infrastructure and networking this with intelligent vehicles taking into account novel power and drive train concepts (electromobility and hybrid vehicles). Applications for intelligent control based on current and forecasted traffic demand as well as ecolo - gical aspects go hand in hand with advanced driver assistance systems for optimization of driving efficiency and use of energy resources.
Applications for energy and traffic efficient driving are central to the research. Future vehicle assistance systems will be calibrated according to the characteristics of each drive train. The required information on the traffic environment will be acquired by communi - cation with infrastructure.
VV will develop methods for strategic traffic network management individualized to the energy and drive train characteristics of each type of vehicle. The expected increasing diversification of future vehicle fleets with a higher percentage of hybrid and/or electric motors will benefit from these improvements.
Four VV subprojects have been defined for prototype implementations of these aims:
The various aspects of urban traffic will be closely coordinated in three application projects: first, large-scale traffic management in “Regional Networks”; next, forward-look - ing energy and traffic efficient driving in “Urban Streets”; and finally, adaptive control of “Smart Intersection”, with support of the driver in the vehicle.
Each of these traffic applications and their interplay will be demonstrated in a real traffic test field in cooperation with leading official representatives of the city of Duesseldorf.
The sub-project “Cooperative Infrastructure” brings to - gether the traffic-based sub-projects. It aims to implement the traffic-based solutions in additional communities and regions by setting up a roadmap for introduction of co - operative systems. Assessment of the combined effect of the applications on traffic and extrapolation of the results will provide estimates of the potential of these new applications.
Project “The Human Element in Traffic” (MV)
The MV project will focus specifically on the user of future assistance and information systems. In the case of advanced driver assistance systems for urban areas, the primary emphasis is safety rather than just comfort. By means of an individualized design of the driver-vehicle interaction for different drivers, the aim is to achieve low-stress, efficient, and safe driving in urban traffic. Research institutes and manufacturers will cooperate to investigate how humans and machines interact and how to predict hu - man behavior. Novel techniques will be developed on the basis of experimental studies.
In urban areas, demands on the human-machine interaction are quite challenging. In order for the vehicle to act as an active helper in hazardous urban situations, rather than a hindrance, distraction of the driver by excessive information must be strictly avoided.
The solutions must provide technical solu - tions and interaction concepts to achieve and synthesize the goals of comfort, efficiency, and safety. An example of a similar synthesis is provided by navigation devices. They contribute to fuel economy and to improvement of traffic safety and comfort without dis - tracting the driver. Similar effects could be achieved by coordination of future information and assistance systems that focus on the user. Optimal design of the driver-vehicle interaction will play a key role.
The MV sub-projects explore the decisive issues of urban traffic:
Human-machine-Interaction (HMI) – How, and with which technologies, should the HMI concept be designed for urban traffic driving conditions?
Intention detection and behavior prediction – How can the vehicle detect the driver’s intentions and react appropriately according to the driver’s needs?
Simulation – How can pedestrians and cyclists with their high density in urban traffic be appropriately modeled in driving and traffic simulation?
Controllability – What measures must be taken to ensure that complex assistance systems remain controllable for the driver in urban traffic? Investigation of advanced driver assistance and information systems in urban scenarios poses new issues for user oriented human-machine interactions and on concept assessment during the course of development.
The project MV is uniquely linked to the related UR:BAN projects KA and VV both in the thematic direction and the partner constellation; interaction concepts as well as basic methodological problems will be investigated.
The project MV is designed to take a user-oriented position contributing to unified, integrated, interaction solutions based on validated behavioral models for optimization of traffic simulations and assistance systems.
Details of Field Operational Test
Start date and duration of FOT execution
The research objectives will be pusued in three main thematik target areas:
Novel panoramic sensor technologies now allow comprehensive observation and evaluation of the complex city traffic environment. To improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is to evaluate and predict their behavior and movements. In complex urban traffic, the driver is supported in maneuvers such as driving in narrow or obstructed streets, resolving conflicts with opposing traffic, and performing lane changes; using novel panoramic sensing and prediction capabilities, collisions can be avoided by automatic braking or swerving as needed.
Economic and energy efficient driving
New information and communication technologies such as GPS/ Galileo, UMTS/ LTE and C2X enable novel methods for cooperative urban traffic management. By deployment of intelligent infrastructure and networking with intelligent vehicles, future advanced driver assistance systems will be able to implement instructions or advisories of strategic traffic management. In this way, traffic diversion and network optimization can take the energetic characteristics and other features of electric, hybrid, or conventionally powered vehicles into account. These key considerations will contribute to the goal of optimizing traffic and energy efficiency, achieving a high level of service (avoiding clogged roads), and reducing emissions in urban areas.
Anticipatory and stress-free driving
Novel assistance functions provide the driver with supporting information in complex traffic situations, but benefits arise only if the information flow is intelligently filtered to avoid over - loading the driver. To this end, support is adapted to the driver’s current state and activation by detection of overburdened or inattentive drivers. By incorporating adaptive support into the design of vehicle controls and displays, the driver receives information much earlier and is motiv ated to anticipate traffic situations rather than simply react to them. This anticipatory approach is the key to a safer, more efficient, and less taxing urban driving experience.
Summary, type of funding and budget
City Safety: Budget 40 million Euros
Networking Traffic System: Budget 23 million Euros
The Human Element in Traffic: Budget 17 million Euros
Cooperation partners and contact persons
Project Cognitive Assistance:
Adam Opel AG, AUDI AG, BMW Forschung und Technik GmbH, Bundesanstalt für Straßenwesen, Continental Safety Engineering International GmbH, Continental Teves AG&Co. oHG, Daimler AG, MAN Truck & Bus AG, Robert Bosch GmbH, Volkswagen AG
Project Networked Traffic System:
Adam Opel AG, BMW AG, Continental Automotive GmbH, Daimler AG, DLR, GEVAS, HTW Saarland, ifak Magdeburg, Landeshauptstadt Düsseldorf, MAN Truck & Bus AG, PTV AG, Stadt Kassel, TU Braunschweig, TU München, TomTom, Transver GmbH, Uni Duisburg-Essen, Uni Kassel, Volkswagen AG
Project The Human Element in Traffic:
Adam Opel AG, AUDI AG, BMW AG, BMW Forschung und Technik GmbH, Bundesanstalt für Straßenwesen, Daimler AG, DLR, Fraunhofer IAO, MAN Truck & Bus AG, PTV AG, Robert Bosch GmbH, RWTH Aachen, TU Braunschweig, TU Chemnitz, TU München, Universität der Bundeswehr München, Uni Würzburg, Volkswagen AG
- Public Authorities:
- Vehicle Manufacturer:
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Main Contact person
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