UR:BAN

The main aim of “UR:BAN” is to optimize the efficiency of traffic in urban areas while reducing the emissions. This aim will be achieved through the development of intelligent infrastructure and its networking with intelligent vehicles with special consideration of new propulsion concepts. In addition, applications for intelligent guidance of traffic taking into account both, current and predicted demand and ecological optimization potentials are developed during the project. Particular attention is put on a standardized production-oriented design of system architecture with online data supply to ensure appropriate direct options for transition into productive operation after the project.

The major tasks of the Institute of Traffic Engineering and Logistics are:

• Prediction of switching time points of traffic actuated signal systems
• Development of  a quality management for coordinated traffic lights
• Development of smartphoneapplications (green wave assistent)

The focus of this subproject is on innovative vehicle functions that can be used in urban road networks to make private motorized transport in cities more fuel-efficient. To this end, new vehicle functions are being developed which, on the basis of traffic light phase anticipation using driver information and adapted energy management in the vehicle, enable consumption-reduced driving through the light signal-controlled main urban road network. In order to achieve the most comprehensive effect possible, it is necessary to provide not only individual so-called cooperative traffic signal systems, but also the availability of the traffic signal switching times of the traffic signal systems located in the urban road network as comprehensively as possible. For this purpose, a central-based solution is to be developed and tested, in which the cities of Kassel and Düsseldorf provide traffic signal switching points and their forecast for the generation of service information based on the operating data of the traffic signal systems available on the central side. However, since there is currently no forecasting of the switching times of traffic signals that are controlled locally based on traffic, procedures and algorithms must be developed for this purpose and used in the cities' central traffic management system. In order to ensure the transferability of the procedures for switching time prediction, two test areas were selected, Düsseldorf and Kassel, in which very different control strategies are used. In Düsseldorf, fixed-time control, which is static and traffic-dependent, is used primarily, whereas in Kassel, locally traffic-dependent LSAs are mainly used. The development of the procedures in the two very different test areas is intended to ensure the transferability of the approach.

Energy-efficient and low-emission driving can only be ensured by reliably coordinated traffic signal systems. In order to achieve the desired traffic effects and the resulting environmental relief, not only must the forecast data be fed back into the vehicle, but conclusions must also be drawn for the control system from the resulting information on the driving patterns. To optimize the process, it is therefore also necessary to adapt the control system. The aim is to determine in concrete terms how the data models and defined use cases prove themselves in practice and whether it is possible to achieve the required operational quality. Traffic signals on a route in the city of Düsseldorf and in the city of Kassel will be considered with regard to motorized individual traffic. By reducing stops and unnecessary starts of motorized individual traffic, the flow of traffic is to be maintained and pollutant emissions reduced.

Crossing inner-city intersections involves situations for all road users that are difficult to predict. When does the traffic signal change? Where is the traffic flow disrupted? The service information generated from the data provided by the city is transmitted to the road users via mobile radio data channels and converted directly into the corresponding new vehicle functions in the vehicles. The target functions to be implemented in the vehicle are the deceleration assistant (approaching the traffic light, if necessary use of braking energy recovery) and the green wave assistant (sailing through several traffic lights). Using smartphone technology, which is very widespread these days, the driver is shown information on the optimum deceleration before the LSA. In a similar way to the adaptive automatic start-stop system, the driver receives information on when it makes sense to switch off the engine and when it should then be restarted. When the vehicle passes through a green wave, the application visualizes the current virtual position of the vehicle in this wave, thus providing the driver with a basis for decelerating or accelerating so that he can pass the coordinated traffic light without stopping.