Design and implementation of path planning and vehicle motion control algorithms by exploiting []

Design and Implementation of Path Planning and Vehicle Motion Control Algorithms The thesis activity will consist of the study, design, and development of path planning or vehicle control algorithms that take advantage of information from both onboard sensors and other vehicles or the infrastructure to which the vehicle belongs. The activity will include performing testing and validation in simulated environments and, where applicable, in real scenarios in an experimental infrastructure laboratory. Internship Main Topic: According to the Society of Automotive Engineers, Driver Assistance Systems (ADAS) are classified into 6 categories, whereas the level of vehicle autonomy increases. Ultimately, ADAS level 5 refers to vehicles capable of driving completely autonomously, without any intervention from the occupants of the passenger compartment. Commercialization of a vehicle with level 5 ADAS capabilities is expected by 2050. Currently, vehicles on the market offer ADAS systems that do not exceed level 3, for which a human driver is expected to be ready to take control of the vehicle at any time in the event of an emergency or failure of the autonomous driving system. ADAS development efforts to date have focused on the design and development of control and artificial intelligence algorithms capable of implementing driver assistance systems based solely on onboard sensors and actuators. The evolution of ADAS systems beyond the third level will require, in the near future, a change of viewpoint, broadening the study from the vehicle agent to an infrastructure forming a digital ecosystem to which autonomous vehicles will belong. Candidate Requirements/Course of Study: Computer Engineering, Electronics, or Automation. Location: Naples J-18808-Ljbffr

Location: provincia-di-napoli, IT

Posted Date: 4/4/2025