A driver support system for freeway lane-change operations.

Author(s)
Wei, C.-H. & Chen, I.-C.
Year
Abstract

Lane-change is one of the most difficult tasks of driving. A notable number of situations have to be considered simultaneously. A lane-change decision support model is developed in this study using the artificial neural networks (ANN). The advantages of the ANN approach lie in the learning capability. Due to its nature, the ANN model can consolidate various information surrounding the drivers and generate reliable results to help control the vehicles. Several preliminary validations and comparisons are conducted with the field survey data. It is confirmed that the ANN model mimics traffic characteristics more accurately. In particular, the ANN model can be adopted to individual driver characteristics. This reveals practical feasibility and significant market potential for customized in-vehicle equipment. (A*)

Request publication

13 + 3 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Publication

Library number
C 19600 (In: C 19519 CD-ROM) /91 / ITRD E110408
Source

In: ITS: smarter, smoother, safer, sooner : proceedings of 6th World Congress on Intelligent Transport Systems (ITS), held Toronto, Canada, November 8-12, 1999, Pp-

Our collection

This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.