IBM Research - Ireland Internship Project: Real-time filters for monitoring drivers behavior - overview
Abstract: Poor car-following behavior is responsible for a significant number of car accidents. In this work, we aim to design and implement a system that trains the driver to be a better driver utilising the measurements from the vehicle proximity sensors, e.g. relative distance and speed to leading vehicle(s). Recent work has shown that offline parameter identification of car-following models was a tedious task that requires precise knowledge of the model specificity's, i.e. parameters may only be identifiable in specific traffic regimes.
The work will consist in designing an algorithm that efficiently performs online parameter identification of car-following models given the available measurements. The first step is to study the mapping between the identifiability of car-following parameters with their corresponding traffic flow regime. The second step is the design an online filter that integrates this mapping. Then, a risk model based on safety indicators and simulation analysis will be derived. Finally, a prototype system will be implemented. The system will only intervene if a dangerous behaviour is detected according to the risk model.
Required skills: system identification, particle filter, Python.