• Meet BMW: the company

The special fascination of the BMW Group not only lies in its products and technology, but also in the company’s history, written by inventors, pioneers and brilliant designers. With its four brands BMW, MINI, Rolls-Royce and BMW Motorrad, the BMW Group is the world’s leading premium manufacturer of automobiles and motorcycles, and provider of premium financial and mobility services. The BMW Group production network comprises 31 production and assembly facilities in 15 countries; the company has a global sales network in more than 140 countries.

Long-term thinking and responsible action are the basis of economic success. Ecological and social sustainability, comprehensive product responsibility and a clear commitment to conserving resources are therefore an integral part of our strategy.

• BMW in ICT4CART: what is your role?

In the ICT4CART project, BMW focuses on realizing a use case for smart parking in the city of Ulm (Germany). Smart parking enables fleet managers to intelligently and securely relocate fleet vehicles by processing parking data from the city or from third party providers. This process requires common data format, an interface for seamless bilateral communication between different stakeholders (for example between the Automotive OEM Cloud (Fleet Manager) and the Service Provider Clouds), communication authentication, and encryption.

To this end, BMW has developed algorithms for fleet management and ride hailing, and combined the results with parking data provided by the city of Ulm.

Afterwards, with the help of a simulator, BMW developed all the backend in-car components necessary for the demonstration in the vehicle. This has led to the development of prototype components aiming at facilitating the parking spot search, which can be used for further research purposes.

Next to the work on the use case for smart parking, BMW leads ICT4CART’s tasks on data analytics, working on requirements analysis, use cases specification, interfaces and components in ICT4CART’s IT-environment. BMW also works on the definition and refinement of the overall architecture.

Lastly, BMW participates in dissemination and standardization activities.

• How did ICT4CART implement and/or use simulation in the smart parking use case?
  
  

A big part of the development of the smart parking’s use case is the implementation of a ride-hailing simulator.

The BMW simulator has two types of basic entities: vehicles and requests. Vehicles entities include information typically associated with cars, like position, while requests represent a client’s request to be picked up for a ride. As the simulation starts, requests are matched to vehicles, which then start moving. Throughout the simulation, both vehicles and requests go through different statuses. Transition from one status to another is triggered when a vehicle reaches a specific position, like pickup location, drop off location or vehicle service location.

One of the simulation components is the parking component. It enables the simulation to relocate idle vehicles to the nearest parking garage with available parking spaces. The parking information stems from the ICT4CART Service Provider Gateway and the parking functionality can be switched on and off.

While running, the simulator gathers various statistical data, with the most important being revenue and cost information for each vehicle. These data are used to evaluate the impact ICT4CART’s infrastructure has on the smart parking use case in relation to profit. All information about vehicles and requests are stored and can be exported from the simulation anytime as a snapshot.

• How does the application in the vehicle look like? And how would it look like in a fully automated scenario?
  
  

According to studies, German drivers spend on average 41 hours a year searching for a parking spot, and this costs €896 per driver in wasted time, fuel and emissions[i]. Moreover, drivers looking for a parking spot cause about one third of traffic in city centers.

The BMW in-car prototype application intends to assist the driver, and as a consequence the fleet manager, to find a parking spot in a quick, effortless and efficient manner. As soon as the vehicle is within a defined radius from the destination, the application alerts the driver with parking garages with available parking spots. The user may select one of them and switch on the navigation. Once the vehicle has been parked and the on/off button has been pressed, the application gives information about the garage, such as parking time and costs.

This application is just one tile of the “fully automated scenario” puzzle. This could include automated driving combined with automated smart parking, reservation of parking spots, automated payment, and even automated navigation in the parking garage. Of course, such automated smart parking scenario is still in the research phase and under investigation for usability and profitability.

• What are the first results we have from our evaluation, related to the impact that the ICT4CART infrastructure has on our use case?

After running several preliminary tests with the simulator using different input parameters, , we have concluded that the ICT4CART infrastructure greatly reduces the costs for the fleet manager. These results are extremely premature. A full set of results, as well as an evaluation report, will be published at a later time in an appropriate technical report within the project.

[i] https://www.parking-net.com/parking-news/inrix/germans-41-hours-searching-parking