A MODEL OF THE DRIVER BASED ON NEURAL NETWORKS

Two driver models based on neural networks, for speed and acceleration control as well as for lateral control will be introduced. In contrast to conventional models, driving is not represented as control with respect to given input functions, but as a reaction to external situations. The first model for speed and acceleration control is divided into two parts: a neural network classifies the street geometry as a variable which can be interpreted as the representation of action. These are used by the second part, the fuzzy controller, which adjusts speed and acceleration. In order to simulate a double lane change, a controller based on back propagation networks will be introduced in the second model. (A) For the covering abstract see IRRD 874974.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/7800033090
• Corporate Authors:

  INTERNATIONAL ACADEMIC PUBLISHERS

  137 CHAOKEI DAJIE
  BEIJING,   China 
• Authors:
  • JURGENSOHN, T
  • RAUPACH, C
  • WILLUMEIT, H-P
• Conference:
  • VEHICLE DYNAMICS. 25TH FISITA CONGRESS, OCTOBER 1994, BEIJING. VOL 2. TECHNICAL PAPER NO. 945082
• Publication Date: 1994

Language

• English

Media Info

• Features: References;
• Pagination: p. 161-6

Subject/Index Terms

• TRT Terms: Acceleration (Mechanics); Conferences; Control; Drivers; Driving; Dynamics; Mathematical analysis; Mathematical models; Simulation; Speed
• Uncontrolled Terms: Side
• ITRD Terms: 5405: Acceleration; 6471: Analysis (math); 8525: Conference; 3874: Control; 1772: Driver; 1855: Driving (veh); 5473: Dynamics; 6473: Mathematical model; 9074: Side; 9103: Simulation; 5408: Speed
• Subject Areas: Data and Information Technology;

Filing Info

• Accession Number: 00717921
• Record Type: Publication
• Source Agency: Transport Research Laboratory
• ISBN: 7-80003-309-0
• Files: ITRD
• Created Date: Mar 20 1996 12:00AM