NDLI: Performance analysis of a scalable navigation solution using vehicle safety sensors

Content Provider	IEEE Xplore Digital Library
Author	Martin, S. Rose, C. Britt, J. Bevly, D. Popovic, Z.
Copyright Year	2012
Description	Author affiliation: College of Engineering, Auburn University, Auburn, AL USA (Martin, S.; Rose, C.; Britt, J.; Bevly, D.) \|\| Automobile Technology Research, Honda R&D Americas, Inc., Southfield, MI USA (Popovic, Z.)
Abstract	GPS receiver performance can suffer in difficult environments such as urban canyons and heavy foliage. Inertial sensors provide information between GPS updates and can enhance the position solution in a GPS/INS architecture. Additional information from safety sensors already on the vehicle, such as lane departure warning (LDW) sensors, can enhance the navigation solution further by constraining inertial errors even in the presence of GPS errors. This paper outlines a scalable navigation solution that can use a combination of GPS, reduced inertial sensors, full inertial data, vehicle CAN data, and vision sensors, depending on what data is available in difficult environments. Data was collected in Detroit, Michigan in a diverse mix of environments that includes heavy foliage, highway, and downtown areas, in proportions representative of what is expected in typical driving. Validation of the approach consists of both a qualitative analysis of the resulting trajectories overlaid on a map of the area and quantitative comparison of the trajectories produced by the proposed system and the reference system.
Starting Page	926
Ending Page	931
File Size	1163140
Page Count	6
File Format	PDF
ISBN	9781467321198
ISSN	19310587
e-ISBN	9781467321181
DOI	10.1109/IVS.2012.6232286
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Global Positioning System Vehicles Sensors Laser radar Wheels Cameras lidar positioning localization sensor fusion urban canyon foliage GPS INS IMU inertial navigation vision camera
Content Type	Text
Resource Type	Article

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