Photo: Das sensorgesteuerte Parkmanagementsystem – Parkplatz ohne Suche / The sensor-controlled parking management system – parking space without searching

Berlin to test radar-based parking space detection

08 October 2015

Siemens has launched a pilot project in Berlin aimed at simplifying the search for a parking space. The company has installed radar sensors on street lamps, for test and demonstration purposes, that provide information on parking space occupancy. The network of sensors scans from above an area of up to 30 metres, the equivalent of five to eight parking spaces.

The test results will be available in 2016 and should prove that by reducing parking search traffic the system is suitable for cutting CO2 emissions.

“Our system guides drivers to a free parking space from the minute they start their journey,” Markus Zwick, Head of Innovative Mobility Solutions at Siemens, told Cities Today. “Drivers avoid the hassle and waste of time circling around looking for a free place to park, which in some cities account for up to 30 percent of downtown traffic. The system reduces overall traffic in the city by minimising the traffic related to finding a parking lot.”

As part of the City2.e 2.0 research project, Siemens is demonstrating a faster way to find parking in the Bundesallee in Berlin in cooperation with the Senate Department for Urban Development and the Environment in Berlin, the VMZ Berlin Betreibergesellschaft mbH, the Institute for Energy and Mobility, and the Robotics Innovation Center of the German Research Center for Artificial Intelligence.

Street lamps on a 200-metre-long section of road have been fitted with radar sensors that continuously monitor urban parking areas and report free parking spaces and the number of occupied e-parking spots to parking space management software.

“The information from the overhead radar sensors is processed by adaptive system software, recognising recurring patterns in the parking space situation,” added Zwick. “Our solution provides drivers with forecasts, for example concerning the expected parking space situation at their destination and even suggest alternative routes with lower volumes of traffic.”

A key aspect to the project is the software application developed by the Robotics Innovation Center uses intelligent learning methods. Data from parking space sensors helps the system to recognise typical parking space situations. This learning feature enables the system to predict in advance where and when the best chances exist for finding a free parking space. The system is also coupled with a multimodal route planner. So if no parking spaces are available, the route planner provides real-time information on possible options for switching to public transportation services.

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