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) 4-51 Test setup and planning for vehicle fleet testing
2) 4-52 System implementation on different vehicles
3) 4-53 Intensive testing of the fleet management system
4) 4-54 Results analysis and management system improvement
5) 4-56 Validation of the fleet management system
The main objective of this training is to assist the research team in the development and validation of a real-time management and tracking system for road vehicle fleets. Initially, the system will be installed on a rented fleet of vehicles in order to perform targetted tests in various realistic scenarios. During these tests, the student will guide the drivers through pre-defined scenarios, he will record raw data from all the vehicles for post-processing purpose and he will analyze the performances of the system and validate it based on a robust reference. Following this test phase, the student will share the encountered problems with the research team and study possible improvement of the system. Once the improvement is made to the system, the student will be responsible for intensive series of tests to be conducted in realistic environments on a larger fleet of vehicles from existing iMetrik customers. During this test phase, the trainee will achieve robust validation of the system and analyze its performances in a real environment with a real fleet of vehicles.
