Statistical Safeguards: Redefining Col lision Avoidance with Probability Theory: Employing Statistical Decision-Making to Enhance Safety in Mixed Traffic Environments
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Systems, control and mechatronics (MPSYS), MSc
Publicerad
2024
Författare
Hjertén Brink, Sebastian
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This thesis introduces a probabilistic collision avoidance system that employs statistical decision-making in order to enhance the safety of mixed traffic environments.
Central to this approach is the representation of vehicle positions as normal probability distributions, which are convolved with real-time sensor data to assess risks
more accurately and reduce the unnecessary emergency stops.
The research develops and implements a dynamic collision probability threshold,
that is derived from safety integrity levels (SIL), which is imperative for complying with the rigorous safety standards and regulations. Simulations and analytical methods were used to validate the effectiveness of the proposed algorithm and
demonstrating its potential in decision-making in emergency situations.
Thus a a scalable solution for collision avoidance is presented in the form of an
algorithm that can be integrated into existing safety systems, in order to enhance
the operational efficiency for mixed traffic environments.
Beskrivning
Ämne/nyckelord
Collision avoidance systems , Probabilistic risk assessment , Safety integrity levels , Statistical decision making