Driver Assistive Systems for Rural Applications: A Path to Deployment

Project summary:

The first component of this project was to develop and implement an automated means to collect geospatial data and process it, in order to create a geospatial database suitable for use in driver assistive systems. The approach used for this research was to equip a vehicle with DGPS, sensing systems, image capture hardware, image processing software, and data acquisition equipment in order to facilitate the real-time determination of the global position of a paint stripe as a vehicle travels on a lane. With this sensory and data acquisition system, the location of all paint markings on the roadway can be accurately determined, and used as the basis of a multipurpose high accuracy geospatial database. A complement to the image processing task was that of using paint striping machines to collect geospatial data. The image-based system was modified so that the global location of the paint nozzle could be determined from a sensor suite and a DGPS receiver located on the paint striping machine. Sensors were used to determine when the paint is applied. Raw data from these systems was converted into geospatial information; software for smoothing, feature extraction, and formatting were developed to allow for the automated creation of digital maps.

Deployment of any system is driven by market demand and system cost. Initial deployment of the Intelligent Vehicle Lab Snowplow Driver Assistive System (DAS) was limited to a 45 mile section of Minnesota Trunk Highway 7 west of I-494 and east of Hutchinson MN. To better gauge demand and functionality, St. Louis and Polk Counties in Minnesota operationally tested the system during the winter of 2003-2004; Polk County also tested during the winter of 2004-2005. Operational benefits were found to be drastically different in the two counties. Low visibility was not an issue with the St. Louis County snowplow routes, so the system offered few benefits. In contrast, the topology of Polk County is flat, with almost no trees. High winds combined with few visual cues create significant low visibility conditions. Polk County was pleased with their original system, and obtained a second system and tested it operationally during the winter of 2004-2005. The experience of these two counties is documented in Volume One. A key component of the DAS is a high accuracy digital map. With the exception of the mapping process, the present cost of the DAS is well documented. With cost data complete, counties can determine whether to acquire these systems.