English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In order to track the active obstacle avoidance path of the autonomous vehicle, this thesis proposes two controllers with different inputs and constraints, on the basis of the Model Predictive Control (MPC). The controller A takes front-wheel steering angle as control input, while the controller B adds rear-wheel braking torque as another control input with extra constraints on the rear wheel braking torque. The simulation results indicate that both controllers can well track the desired path. More specifically, the performance of controller B is better than controller A in terms of lateral displacement and yaw rate, but the performance of controller A is better in yaw angle.

Research on Active Obstacle Avoidance for Autonomous Vehicle Based on Model Predictive Control