Audi has wrapped up a three-year partnership launched in 2011 involving the Volkswagen Group’s Electronics Research Laboratory (ERL) in Silicon Valley and four leading US research universities to develop innovations in predictive driving technology that would allow a car to anticipate future traffic trends and to “learn” a person’s driving habits for a customized driving experience on each commute. (Earlier post.)
Audi this week demonstrated some of the early concept results of the Audi Urban Intelligent Assist (AUIA) project to media in San Francisco. The demonstration focused on two primary applications: Driver Centric Urban Navigation and Urban Assistance.
Audi, with an eye toward increasingly dangerous traffic patterns in the world’s biggest cities, launched the AUIA project to help make urban driving safer and more convenient through a number of advanced functions such as telling a motorist the optimal time to leave for an appointment; directing him or her on the most efficient route to an open street or garage parking; providing naturalistic navigation based on visual cues; monitoring driver awareness; and signaling when it is safe to accomplish maneuvers to merge or change lanes on a congested highway.
This project brings to life a connected car that essentially predicts the behavior of its driver, analyzes current and future driving conditions and creates a safer and hopefully less stressful experience for the person behind the wheel.—Mario Tippelhofer, Senior Software Engineer, ERL
The functions demonstrated in San Francisco utilize traffic information from multiple on and off-board sources to predict how traffic in a city flows throughout the day and combines this information with driver diagnostic data to generate a route that is comfortable, efficient and tailor-made to each driver. Highlights of the featured technology include:
Audi Driver Centric Urban Navigation
Time-2-Start notifies drivers via their mobile devices how long it will take them to reach their destination before they leave.
Smart Parking combines the parking habits of a driver with the availability of nearby parking spots—parking structures as well as metered street parking—to help identify parking spots in a destination area and provide navigation to that location.
Predictive Traffic anticipates and analyzes current traffic patterns based on present and past traffic data, along with weather and event information.
Naturalistic Guidance uses surrounding landmarks to provide detailed instructions for easy navigation (e.g. “Please turn left at the park”).
Seamless Navigation provides walking guidance to the driver from his or her “Smart Parking” spot directly to their destination.
Audi Urban Assistance
Merge Assist helps a driver merge on the highway by utilizing components of speed calculation and speed displayed in the instrument cluster and green LEDs on the side mirrors notify the driver it is safe to merge.
Lane Change Assist monitors a driver’s blind spot areas as well as fast-approaching vehicles and hazardous objects in an effort to assist the driver in changing lanes on the highway. The system also analyses driver behavior to predict when the driver intends to performing a lane change. This coupled with the environmental data allows the vehicle to signal the driver when it is safe to change lanes via green LED lights on the side mirrors.
Attention Guard provides early detection of driver distraction through countermeasures that get the attention of a driver and bring their focus back on the road.
Although Audi may decide to extend parts of the research for further development, that is yet to be determined, according to an Audi spokesperson.
At the 2012 LA Auto Show, an AUIA exhibit in Audi’s stand showcased the advancements in predictive technology made by AUIA, the harnessing the power of Big Data through algorithms, real time data, Human Machine Interface (HMI), advanced sensors, lidar/radar detections and other innovative approaches.
The AUIA project was the latest in a series of research projects that Audi has formed with leading US universities. The four academic partners in AUIA were the University of Southern California; University of California, San Diego; University of California, Berkeley PATH (Partners for Advanced Transportation TecHnology); and University of Michigan Transportation Research Institute (UMTRI).