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sts.components.contact.mr.placeholder Sebastian Webel
Mr. Sebastian Webel

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Pictures of the Future
The Magazine for Research and Innovation
 

Livable and Sustainable Cities

A System that Could Help Cities Rethink Parking

In the future, radar sensors may help drivers find empty parking spaces quickly and easily. This will benefit not only drivers but also cities.

Parking is a problem in major cities. There simply aren't enough parking spaces. Now, however, Siemens has developed a system that will help future drivers find parking spots quickly and without stress. In September 2015, Siemens and partners have launched the world's first pilot project on intelligent search for parking space in Berlin

On average, finding a parking place in a German city requires about 4.5 kilometers of extra driving. According to the German Federal Motor Transport Authority, that means that a typical car emitting around 140 grams of CO2 per kilometer will generate at least 630 grams of unnecessary CO2 in the process of looking for a parking space. And significantly more in stop-and-go traffic.

Thirty Percent of Traffic

A scarcity of parking spaces has many negative consequences: exhaust fumes and particulates in the air, noise, and the frazzled nerves of frustrated drivers. “Depending on a city’s size, vehicles looking for parking spots account for about 30 percent of its total traffic volume,” says Marcus Zwick, who heads a project that is developing smart parking space monitoring in Siemens' Mobility Division. “If we want to manage the parking problem in major cities worldwide in the future, it won’t be enough to create new parking areas and switch to bicycles more often,” he adds. The problem is serious. In 2014 passenger traffic volume in Germany grew by 1.4 percent compared with 2013; according to the Federal Ministry of Transport and Digital Infrastructure, a further one-percent increase is expected in 2015.

That’s why Zwick and several of his colleagues have been working since October 2013 to develop new approaches to the problem. His solution, which was presented at the annual meeting of the Eurocities network in Munich in November 2014, is called Advanced Parking Management. In this concept, radar sensors integrated into streetlights or mounted on buildings could continuously monitor parking areas throughout a city and send information about parking space occupancy to a software system. Urban authorities would collect this information and pass it along to app operators in real time. Thus every road would know the locations of empty parking spaces — via a terminal such as a smartphone, tablet or a navigation device.

In the future, drivers will be able to enter their destination into a smartphone or a navigation device and find out whether empty parking spaces are available in the vicinity and, if so, where they are.

Monitoring Parking Areas from Below

Sensors that monitor sections of a street and document parking space use are actually not a new phenomenon. For example, a trial project in the Westminster district of London is testing the use of 3,000 ground sensors. The sensors, which are embedded in the road asphalt, simply register whether there is something above them — though not the size or position of the vehicle. But as soon as there is a snowfall or the ground sensors are covered by dirt, most of them stop transmitting measurement data. “That’s how we got the idea of monitoring the streets not from below but from above,” explains Dr. Florian Poprawa, the head of Hardware Development in the Advanced Parking Management research project.

To equip stretches of a street with radar sensors for monitoring parking spaces, cities can use their streetlights as masts. No expensive new infrastructure will be required.

Radar Sensors to the Rescue

Siemens specialists opted to use radar-based sensors in the project, which is being supported by Germany's Federal Ministry for the Environment. “It’s true that radar sensors have a lower resolution than conventional surveillance cameras, but they offer other advantages,” Zwick says. For example, because of their low resolution, they can record only schematic images. “The individual road users’ right to privacy is safeguarded,” he explains. What’s more, radar sensors are much less sensitive to fog, rain, changing light conditions, and winter weather, and they are more economical than ground sensors.

Identifying Empty Spaces

“The first time we monitored the cars parking in front of our office building, we mounted a box with a radar sensor fitted inside it next to the office window. The box was about the size of a car tire,” Poprawa recalls. Poprawa and his colleagues, who had developed the sensor, could now observe parking cars on a monitor in various colors and in real time. Cars that were driving or standing still were shown in red, and empty parking spots were shown in blue.

“The sensor consists of an antenna, an analog electronic system, an analog-to-digital-converter, and a signal processing component,” explains Florian Poprawa. He wants to simply have the sensors installed in streetlights.

The principle underlying the process is simple. The sensor’s circuit board, which is about the size of an adult’s fist, transmits microwaves at a predefined space, and the microwaves bounce back to the sensor when they hit an obstacle. The sensor then uses an algorithm to calculate whether an object is in the parking space and, if so, how big it is and how it is positioned. “The asphalt constantly reflects microwaves to the sensor. As soon as a car moves into the space, the microwaves are reflected to the sensor differently,” Poprawa explains. The radiation exposure to individuals is far below statutory limits.

Developing this kind of high-frequency sensor was a tremendous challenge. After all, the sensor must be able to communicate with its “colleagues” as well as being small enough to fit in a streetlight and easy to built and install. “The sensor consists of an antenna, an analog electronic system, an analog-to digital converter, and a component for processing signals. It should be possible to integrate it into the urban infrastructure without too much effort,” Poprawa says.

Simple Mounting on Streetlights

The reason for this is simple. Because the sensors are so small, they can be installed in streetlights, where they can be supplied with electricity. They can also be mounted on lampposts or building walls. From above they can monitor an area measuring approximately 30 meters by nine meters, which corresponds to about five to seven cars parked in a row. “However, we can flexibly vary the size of the monitored area as needed,” Poprawa says. Unlike cameras and ultrasound sensors, a radar sensor can be protected by covering it with a plastic casing without disturbing the radar beams. The sensor thus remains invisible within its urban surroundings.

In September 2015, Siemens and partners have launched the world's first pilot project on intelligent search for parking space in Berlin. For the City2.e 2.0 research project, street lamps on a 250-meter-long section of road have been fitted with radar sensors that report the availability of parking spaces. The system is also coupled with a multimodal route planner. So if no parking spaces are available at the targeted destination, the route planner provides real-time information on possible options for switching to public transportation services. The data collected by the system can either be used by the traffic information center for its own information services or forwarded through a data interface, such as to app operators, so that drivers always have access to guidance.

Networked communication: Radar sensors (in this picture: points) monitor parking spaces to see if they are occupied or empty and report their findings to a control center. This information is relayed in real time to road users, who are guided to empty spaces via a smartphone or a navigation device.

A System that Learns from Experience

How will the information generated by such sensors reach a tomorrow's driver? The sensors will transmit their data via mobile radio to software in a control center. There, the data will beprocessed and made user-friendly by calculating the real-time occupancy of parking spaces. In combination with location and destination data supplied by smartphones or navigation devices, vehicles will be directed to the nearest available parking spaces.

The software’s special feature is that it works with learning systems. It notes situations in which parking spaces are occupied in recurring identical cycles — for example, if they are very frequently occupied or rarely used at certain times of the day or on certain days of the week. It then uses this information to calculate forecasts for road users about the parking situation they will probably find on reaching a given destination.

Stress-Free Parking

“Advanced Parking Management could also help to make city parking less stressful and optimally distribute parking spaces,” Zwick says. This would involve automatic pricing models that are adjusted to the time of day, the day of the week, and the length of time a car was parked. For example, a city could charge lower fees on side streets with less traffic than on major streets with lots of traffic. Parking could thus be spread more evenly among various neighborhoods, to the benefit of the city, drivers, and residents.

The system has obvious advantages. Road users would spend less time and energy looking for a parking spot, and driving in major cities would become a more relaxed experience. Noise and emissions would decrease.

Before high-frequency sensors can enter daily use, they are put through a function check in testing chambers.

But that’s not all. Many different functions could be added to the system in the future. For example, Siemens experts can imagine equipping cars with RFID chips in order to increase transparency in reserved residential parking areas. Before starting out, drivers could use an app linked with the system to find out where they could park within their destination area and which spaces would be reserved for residents. One aspect of this idea has already been tested: Street-mounted RFID sensors read vehicle chips and sidewalk-mounted LED display indicates whether or not the driver is authorized to parking in a space.

The system could also benefit traffic wardens by directing them to illegally parked cars by means of enforcement software that uses measuring data from the radar sensors. A further feature could permit drivers to pay parking fees by means of an RFID code. In the future, this function could calculate parking fees automatically to the minute, without involving cash. There would be less bureaucracy and fewer parking ticket machines — and cities would save money.

The radar sensors could help cities to efficiently locate illegally parked cars, such as those on bike paths or parking spaces for handicapped drivers.

Much more than Parking Management

“The system can do a lot more than simply optimizing the parking situation,” says Poprawa. Sensors could conceivably have additional functions, such as measuring traffic flow, opimzing autonomous vehicle navigation, or informing drivers of electric cars regarding charging station services. “Of course we want to make sure that the drivers who have no chance of finding an empty spot at their destination switch to public transportation,” Zwick adds. It would also be possible to transmit information about traffic density to control centers for a city’s street lighting system. The centers could then adjust lighting to fluctuating traffic needs. “Our parking space monitoring system could thus play an important role in the smart city of the future,” he concludes.

This Siemens concept has not yet been extensively tested, but an initial pilot project will be launched in Berlin in the spring of 2015. In the project, an over 100-meter-long parking area along a street will be equipped with sensors. “The parking problem affects every major city and every one of its residents,” says Zwick. “We’re optimistic that in the future we can use our system to mitigate the parking problems of other cities as well.”

Ulrich Kreutzer