BMW is expanding its position as a premium mobility provider, with intelligent services and applications like ChargeNow, ParkNow or intermodal navigation. Now, with the Dynamic Parking Prediction research project, the BMW Group is demonstrating a solution that will in future be able to shorten the search for vacant on-street parking, particularly in cities. Together with its partner INRIX, a provider of transportation intelligence and connected car services, BMW will present a research prototype of this application at TU-Automotive Detroit (formerly Telematics Detroit), one of the world’s leading connected car fairs, from 3 – 4 June 2015. The system will be displayed in a BMW i3.
Dynamic Parking Prediction for reduced parking-related traffic
One major sub-cluster of connected vehicle technology from BMW is Connected Navigation, where the RTTI Real-Time Traffic Information system is already helping drivers cope with today’s driving challenges by providing them with early warning of congestion and hold-ups and informing them of alternative routes. Now, the new research project Dynamic Parking Prediction is able to predict parking availability using movement data from vehicle fleets. In this way the application is able to shorten the search for vacant on-street parking, particularly in cities, and provides an effective way of reducing parking-related traffic.
The BMW Group has been researching solutions to take the stress out of parking and to reduce the time spent locating a vacant space ever since 2011. For the purposes of this project, up-to-date digital maps were produced showing all public parking spaces, while several thousand vehicles from a test fleet supplied anonymous movement data generated when using these spaces. Data was supplied by fleet vehicles both when leaving a parking space and also when searching for a space. Based on the digital map, the local prediction algorithm and the parking data from the fleet vehicles, the research application calculates current parking options in a given area, for example a particular part of town. This information is then presented on the dashboard display.
The number of currently vacant parking spaces and the number of drivers looking for parking are both factored into the calculation. Even when the system is restricted to using data just from the fleet vehicles it achieves reliable results – and prediction accuracy increases in step with the number of vehicles supplying data. In this way Dynamic Parking Prediction will be able to help BMW drivers obtain the information they need to home in on parking areas where fewer other road users are simultaneously searching for parking. This will ease pressure on both drivers and local residents.
With the DriveNow fleet vehicles the BMW Group is collecting further useful experience. This parking information service could potentially be rolled out to all other vehicles in the car-sharing fleet in the near future.
BMW and INRIX team up to develop a production-ready system
BMW will present a research prototype of this on-street predictive parking application at one of the world’s leading connected car fairs, TU-Automotive Detroit. The new system will be displayed in a BMW i3 at the INRIX booth on 3 and 4 June 2015. INRIX and BMW will be pooling their expertise to further refine the research prototype for use in production vehicles.
“There is a clear demand from customers living in large cities for a system capable of predicting on-street parking availability. Through its collaboration with INRIX, the BMW Group aims to continue setting the benchmark in urban mobility into the future. We are starting from an excellent baseline, since most of our vehicles are already equipped with connected technology ex-factory” says Martin Hauschild, Head of Traffic Technology and Traffic Management at the BMW Group.
Connected research platform: the BMW i3
The BMW i3 is not only the world’s first premium electric vehicle. With its standard-specification built-in SIM card it also offers a range of connectivity features. These include services such as intermodal navigation, which also takes into account other modes of transport, recommending local public transport whenever this offers the best way of reaching the destination. It therefore also makes the ideal vehicle for the first unveiling of a research version of the Dynamic Parking Prediction system.
Initial tests with this prototype have already been successfully completed in Munich. The system is self-teaching and can therefore easily be rolled out to other cities too.
This system will enjoyed by many drivers that may spend more than 30 minutes to find a parking place. Unfortunately the ability of the system to deliver is strongly depending on the number of users being connected. Do you think that it will be widely and quickly adopted by the drivers and OEMs or that it will take several years to see the benefits of such a technology?