In this research, an autonomous vehicle function management methodology is
studied. In accordance with the traffic situation, the decision making level chooses the
optimal function that guarantees safety and minimizes fuel consumption while the
control level is implemented via neuromorphic strategy based on the brain limbic
system. To realize the decision making strategy, the Analytic Hierarchy Process (AHP)
is used by considering driving safety, driving speed, and fuel efficiency as the objectives.
According to the traffic situation and predefined driving mode, Lane Change Maneuver
(LCM) and Adaptive Cruise Control (ACC) are chosen as the alternative functions in the
AHP framework.
The adaptive AHP is utilized to cope with dynamically changing traffic
environment. The proposed adaptive AHP algorithm provides an optimal relative
importance matrix that is essential to make decisions under a varying traffic situation
and driving modes. The simulation results show that proposed autonomous vehicle
function management structure produces optimal decisions that satisfy the driving preference. The stability of BLS based control is also investigated via Cell-to-Cell
Mapping.
In this research, autonomous vehicle functions such as Lane change maneuver
and Adaptive cruise control are developed by means of BLS based control. The
simulation results considered various traffic situations that an autonomous vehicle can
encounter. To demonstrate the suggested control method Cell-to-Cell Mapping is
utilized. Subsequently, the autonomous vehicle function management strategy is
developed by Applying AHP and an adaptive AHP strategy is developed to cope with
various traffic situations and driving modes. The suggested method is verified numerical
simulations.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-12-8878 |
| Date | 2010 December 1900 |
| Creators | Kim, Chang Won |
| Contributors | Langari, Reza |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
Page generated in 0.0021 seconds