Research on Integrated Decision Control Algorithm for Autonomous Vehicles Under Multi-Task Hybrid Constraints in Intelligent Transportation Scenarios

Abstract

In order to improve the decision-making and control effect of autonomous vehicles, in this paper, combined with literature research and process analysis, the control algorithm of autopilot vehicle is analyzed, and the driving process is analyzed combined with the flow method. In order to improve the effect of autonomous driving, with the support of improved algorithms, an integrated decision-making control system for autonomous vehicles under multi-task constraints in intelligent traffic scenarios is constructed, and system performance is improved by simulating autonomous driving decisions in a variety of complex situations. Moreover, this paper designs the road driving model according to actual needs, sets the functional modules of the entire system, and build the overall framework of the system. Finally, in order to study the integrated decision-making effect of this system, this paper conducts test research by designing a simulation test method. From the simulation test results, it can be seen that the intelligent decision-making system for autonomous vehicles constructed in this paper has certain effects.

Active Noise Control Scheme for Smart Beds Based on a Wide and Narrow Band Hybrid Control Algorithm

“…The road driving model was created in accordance with the actual needs, and the general architecture of the system and its functional modules were established. The test findings demonstrate that the intelligent decision-making system has some capabilities for decision control and that performance has been significantly enhanced [13]. By using a variable control method in the model predictive control MPC to control the maximum deviation parameter under all non-linear situations, Ali S U et al offer a distributed MPC-based control technique for multivariate optimisation.…”