Surface recogniton for cars: A comprehensive approach for neural networks
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- New Mexico Tech. Univ., Socorro, NM (United States)
- Univ. of Utah, Salt Lake City, UT (United States)
This paper explores the viability of neural-networkbased classification of ground surface for vehicles. By classifying road surface in near realtime, improvements in vehicle performance (e.g. braking and cornering) may be possible. Classification performance for many combinations of feature encoding and neural network types are compared. The vehicle used here was an An Audi “S3” with a magnetic suspension system on the sport mode. An NI CompactRIO (or cDAQ) module was used to record from a lowing the cDAQ to communicate with the PCB 352C03 one-axis accelerometer. The accelerometer was firmly attached to the windshield of the car. This work focuses on the classification of four road surfaces (asphalt, dirt, concrete, and sand), though larger target sets were also considered. The most accurate method involved a MATLAB feature extraction package with a back-propagation neural network, yielding an overall accuracy of 97%. Lessons learned from this wide exploration of options may extend to other related classification problems.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1429718
- Report Number(s):
- SAND--2017-13615J; 659570
- Country of Publication:
- United States
- Language:
- English
Similar Records
ACEEE's green book: The environmental guide to cars and trucks, Model year 2000
Racing strategy and car design for staged solar car races using simulation of environmental and vehicular parameters
State of the art of underground coal mine tracked vehicle brake systems. Revised report. [Pros and cons of adding braking systems to haulage cars]
Book
·
Sat Jul 01 00:00:00 EDT 2000
·
OSTI ID:20076013
Racing strategy and car design for staged solar car races using simulation of environmental and vehicular parameters
Conference
·
Thu Jul 01 00:00:00 EDT 1999
·
OSTI ID:20030566
State of the art of underground coal mine tracked vehicle brake systems. Revised report. [Pros and cons of adding braking systems to haulage cars]
Technical Report
·
Mon Oct 01 00:00:00 EDT 1973
·
OSTI ID:7339826