In German cities, an average of 4.5 kilometers is required to find a place to park. According to the German Federal Automobile Transport Agency, this means that a car that emits about 140 grams of carbon dioxide per kilometer will unnecessarily emit at least 630 grams of carbon dioxide in the search for a parking space. Frequent stop and go will also increase emissions significantly. Insufficient parking spaces have caused many undesirable consequences, such as exhaust and particulate matter, noise generation, and frustration and physical exhaustion. This article refers to the address: http:// According to calculations, depending on the size of the city, vehicles looking for parking spaces account for about 30% of the total traffic. Obviously, it is not enough to build a new parking lot and promote cycling. In 2014, passenger traffic in Germany increased by 1.4% compared to 2013; according to the German Federal Ministry of Transport and Digital Infrastructure, this figure will increase by 1% in 2015. At the European City Network Annual Meeting in Munich in November 2014, a solution called “Advanced Parking Management System†appeared. This solution integrates radar sensors into streetlights or onto buildings to continuously monitor parking lots distributed throughout the city and send parking space occupancy to the software system. The traffic authority will collect this information and forward it to the application operator in real time. In this way, drivers on each road can know where there is an empty parking space through terminals such as smart phones, tablets or navigation devices. Ground sensor The use of sensors to monitor the streets and record the use of parking spaces is not new. For example, a pilot project in Westminster, London, is experimenting with 3,000 ground sensors. These sensors embedded in the asphalt pavement simply record whether there is something above it and do not measure the size or position of the vehicle. But once it snows or the ground sensor is covered with dust, most sensors stop sending measurement data. Therefore, this project chose a radar-based sensor. Radar sensors have a lower resolution than conventional surveillance cameras. Due to their low resolution, they can only record simple images, which protects the privacy of people on the road. In addition, radar sensors are less susceptible to fog, rain, Lighting conditions, and winter weather than ground sensors, and are more cost effective. The basic principle of the monitoring process is simple. An adult fist-sized sensor circuit board emits microwaves in a predetermined space, and the microwaves are reflected back to the sensor after hitting an obstacle. The sensor then uses an algorithm to calculate whether there is an object in the parking space, as well as its size and position. The sensor is very compact and easy to install, it needs to be powered by a street light, or it can be mounted to a pole or building exterior. They can monitor an area of ​​about 30 meters long and 9 meters wide, which is equivalent to about 5 to 7 cars parked in rows. Self-learning system How do you transmit the information generated by this sensor to future drivers? The sensor will send its data to the control center's software via mobile radio communication. Here, the data will be processed and converted into clear and understandable information by calculating the real-time occupancy status of the parking space. Combined with the location and destination data provided by the smartphone or navigation device, the vehicle will be directed to the nearest empty parking space. The particularity of this software is that it uses a self-learning system. It recognizes situations where parking spaces are occupied in the same cycle that occurs repeatedly. For example, parking spaces are often occupied or rarely used during certain hours of the day or certain days of the week. Based on this information, it will then calculate a prediction about the situation of the parking space that the road user may encounter when arriving at a particular destination. This will involve an automatic pricing model based on time of day, days of the week, and length of parking. For example, for a street with low traffic, the on-street parking space may be charged at a lower rate than the main street with a large traffic volume. As a result, parking between different communities may be more evenly distributed, and cities, drivers and residents will benefit. This system has significant advantages. Road users can find parking spaces faster and easier, driving in larger cities will be easier, and noise and emissions will be reduced. Not only that. In the future, this system may add many different features. For example, Siemens experts who designed the system envisioned the use of RFID chips for cars to increase the transparency of private parking spaces in residential areas. Before departure, the driver can use the app connected to the system to find out which parking areas are in their destination area and which are private parking spaces. One aspect of this idea has been tested: an RFID sensor mounted on the street reads the vehicle chip, and an LED display mounted on the sidewalk shows whether the driver has the right to park in a parking space. The system also guides traffic inspectors to find vehicles parked in violation of the rules using the execution software of the measurement data sent by the radar sensors to help them work more efficiently. Another feature may allow the driver to use the RFID code to pay for the parking fee. In the future, this feature will automatically calculate the parking fee accurately, without the need to pay in cash. This will streamline procedures, reduce the printing of parking tickets, and save money for the city. Far more than parking space management In fact, this system can do more than just parking optimization. It is conceivable that the sensor will perform more functions, such as measuring traffic flow, optimizing autonomous vehicle navigation, or providing information to the electric vehicle driver about the charging station. Marcus Zwick, head of the development of the intelligent parking space monitoring system at Siemens AG, added, "Of course, we want to ensure that drivers who cannot find empty parking spaces around their destinations instead use public transport. It is possible that The traffic density information is sent to the city street lighting system control center. Then, the street lighting system control center will adjust the lighting according to the changing traffic demand.†He concluded, “So our parking space monitoring system can play an important role in the future smart city. effect." This solution from Siemens has not been extensively tested, but a pilot project will be launched in Berlin in the summer of 2015. In this project, a roadside parking area with a length of more than 100 meters will be equipped with sensors. Zwick said: "The difficulty of parking affects every big city and every resident. We are optimistic that we can use this system in the future to alleviate the parking problems in other cities." Rechargeable Battery & Charger Battery Zhejiang Baishili Battery Technology Service Co,.Ltd. , https://www.bslbatteryservice.com