Enhancing Parking Behavior Detection

Abstract: A review of navigation systems nowadays shows that new features are required in the automotive field. One such feature is suggesting a parking space within a positioning system. In the new global context of navigation, finding a parkingplace has become a central issue for all drivers. The research question for this study is what happens when you get to the destination or when you don’t need to use a GPS to arrive to your destination? This thesis has two major purposes:(1) to investigate an efficient solution for detecting the parking behavior of a moving car; (2) to implement and integrate an environment-friendly solution for HERE in a way that would give the company a competitive edge. By examining only the latitude and longitude from all the input GPS data received in a navigation system, the author defines the best configuration for a parking detection algorithm. Once the best configuration was found, an implementation was proposed. An extensive series of tests has been carried out on the final implementation. Data for tests was obtained using internal tools from HERE for producing different testing routes as navigation files (.nmea files). Creating the input files manually offers flexibility and gives the opportunity to touch all the unexpected behaviors, knowing the expected result in any case. The results obtained from the analysis of the algorithm are encouraging.It has been shown that the configuration chosen for implementation is cheap and effective in predicting parking behavior. In conclusion, the implementation of the algorithm was successfully integrated with the existing HERE SDK. The new feature will be available for the following three automotive companies: Audi, BMW, and Daimler. The algorithm is designed such that it can be easily extended and improved. Future work might include adding parameters that should be adjustable by the user or client like speed of the car.