Project description :
Summary (MAX of 2100 characters with spaces)
This project aims to establish new design methods for robust and efficient automotive navigation and optimal management of a fleet of vehicles in harsh environments. In addition, the project also aims to develop innovative metrics for real-time analysis of dangerous driving behaviour as well as real-time analysis of car accidents in order to significantly improve global safety of Canadian drivers. In general, this research proposes to combine measurements from a high sensitivity GPS receiver with data coming from a self-contained inertial navigation system and other complementary autonomous sensors such as odometers and magnetometers. Moreover, in order to provide an affordable solution, the targeted system will be based exclusively on the use of very low cost sensors. It is expected that this project will help reduce the environmental footprint of motor vehicles in addition to having a significant positive impact on overall vehicle safety. For example, improving vehicle localisation accuracy and robustness in harsh environments can significantly reduce the time to find a stolen or misplaced vehicle, which can have an important impact on Canadian companies’ finances. Furthermore, having a robust and precise solution for monitoring vehicle behaviour can lead to the implementation of a new taxation system based on car usage or on driving behaviour, which according to recent studies, can help reduce vehicle greenhouse gas emissions by up to 10%. In addition, accurate reconstruction of car accidents in real-time allow prediction of specific parameters of an accident scene thus improving reaction time and vehicle safety. The proof-of-concept demonstrator will be evaluated in-laboratory and on-road using simulation equipment and a car test platform under real operating conditions in order to characterize protocols and system performance. The project will contribute to international initiatives for the definition of new standards and contribute to Canadian efforts to reduce greenhouse gas emissions, and create new employment opportunities for the team of highly qualified personnel.
Responsibilities of the candidate:
According to the schedule, this trainee student will be in charge of the following tasks:
1) 4-22 Metric validation in controlled environment
2) 4-24 Final real car accident tests realisation
3) 4-25 Analysis metrics validation and performance analysis
The main objective of this training is to assist the research team in the development and validation of accident analysis and diagnosis metrics that have been developed after the preliminary analysis that took place during the second year of project. These new metrics will be first tested and validated on simulated data as well as on real measurements recorded during the first test phase in order to assess their performance in a controlled environment. Subsequently, the student will be involved in conducting a second series of tests with real accident scenario with a specialized company. These tests involving different accident scenarios will assess the actual performance of the new analysis metrics developed by the research team. During these tests, the student will mainly evaluate the real-time analysis aspect of the system as well as the accuracy of the obtained results. Following this test phase, the student will analyze the results in order to characterize the current performance of the developed metrics, to study their main weaknesses and to explore possible improvements.
