Résumé (MAX 2200 caractères avec les espaces)
Ce projet vise à établir de nouvelles méthodes pour la navigation automobile ainsi que pour la gestion optimale d’une flotte de véhicules en environnement hostile. En outre, le projet vise également à développer des mesures innovantes pour l’analyse temps réel des comportements de conduite dangereuse ainsi que l’analyse temps réel des accidents de voiture afin d’améliorer la sécurité globale des conducteurs Canadiens. De façon générale, cette recherche propose de combiner les mesures d’un récepteur GPS haute sensibilité avec celles provenant d’un système autonome de navigation inertielle ainsi que d’autres capteurs autonomes complémentaires tels que l’odomètre et les magnétomètres. Par ailleurs, afin de fournir une solution abordable, le système cible sera basé exclusivement sur l’utilisation de capteurs à très faible coût. Il est attendu que ce projet permettra une réduction significative de l’empreinte environnementale des véhicules automobiles en plus d’avoir un impact positif sur la sécurité globale des véhicules ciblés. Par exemple, l’amélioration de la précision sur la localisation des véhicules routiers permettrait de réduire considérablement le temps requis afin de trouver un véhicule volé ou égaré, ce qui peut avoir des répercussions importantes sur les finances des entreprises Canadiennes. De plus, l’établissement d’un système de suivi des comportements de conduite des automobilistes pourrait permettre la mise en place d’un nouveau système de taxation basé sur l’utilisation de la voiture ou sur le comportement de conduite, ce qui, selon des études récentes, permettrait de réduire jusqu’à 10% les émissions de gaz à effet de serre des véhicules ciblés. Finalement, la reconstruction précise d’un accident de voiture en temps réel permettrait de prédire les besoins spécifiques sur une scène d’accident, améliorant ainsi le temps de réaction ainsi que la sécurité globale des automobilistes. La preuve de concept sera d’abord réalisée en laboratoire ainsi que sur route à l’aide de matériel de simulation et d’une voiture de test en vue de caractériser les performances du système. Le projet contribuera aux initiatives internationales afin de réduire les émissions de gaz à effet de serre, et de créer de nouveaux emplois pour l’équipe de personnel hautement qualifié.
Responsibilities of the candidate:
According to the schedule, the post-doctoral fellow will be in charge of the following tasks:
1) 1-11 In-depth literature review on project topics
2) 1-12 Study of scientific objectives
3) 1-34 Initial system architecture selection
4) 1-42 Preliminary modeling of the calibration procedure
5) 1-44 Study of temperature effect on inertial measurements
6) 1-52 Preliminary modeling of the AHRS algorithm
7) 1-54 Study of soft and hard iron effects
8) 1-62 Mathematical modeling of the linearized navigation model
9) 1-65 Study of advanced non-linear models
10) 1-8 Final year report
11) 2-11 Review of the actual GNSS assistance methods
12) 2-21 Review of the actual analysis metrics
13) 2-22 Modeling of the preliminary analysis metrics
14) 2-41 Modeling of the temperature dependant model
15) 2-51 Modeling of the magnetic disturbance detection / compensation algorithm
16) 2-61 Study of automotive vehicle constraints
17) 2-62 Modeling and integration of vehicle constraints
18) 2-71 Study of advanced sensor error estimation models
19) 2-73 Mathematical modeling of online calibration algorithms
20) 2-91 Mathematical modeling of advanced non-linear filters
21) 2-11 Final year report
22) 3-22 Study of A-GNSS integration schemes
23) 3-31 Study of vehicle monitoring data integration schemes
24) 3-45 Modeling and testing of improved analysis metrics
25) 3-61 Mathematical modeling of the advanced adaptive navigation model
26) 3-71 Review of the actual analysis metrics
27) 3-72 Modeling of the preliminary analysis metrics
28) 3-85 Modeling and testing of improved analysis metrics
29) 3-10 Final year report
30) 4-15 Study of possible architectural improvements
31) 4-21 Modeling of improved analysis metrics
32) 4-6 Final year report
The objective of the post-doctoral fellow’s project is to ensure that theoretical developments made by the research team will lead to the ultimate goal of the project: the development of a robust embedded integrated navigation system for real-time vehicle fleet monitoring and real-time analysis and diagnosis of car accidents. He should work on the most important theoretical subjects of the project, from the initial integrated navigation algorithm design, its integration with the Orchid platform as well as the development of more advanced navigation algorithms and analysis metrics. One of the tasks of the post-doctoral fellow is to ensure, together with the professors conducting the research project, and the industrial groups, that the research subjects proposed during the three years advance at reasonable pace. He should also support the research team members during their research activities, guide and supervise their research work. He should always have a general view of the global project and mainly on the progress in related theory. He will know about the work of the trainee, Master’s, and Ph.D. students in theoretical areas.
The post-doctoral fellow will start his research work with a thorough overview of the individual project requirements and integration goals and with a detailed literature review and theoretical background about the integrated navigation algorithms and the accident analysis metrics. He will be actively involved in the detailed module design to the point of ensuring that reliability, interoperability, and robustness issues will be addressed. The post-doctoral fellow will be involved in the development of an improved navigation algorithm based on the use of non-linear models, as well as, in the development of innovative metrics for real-time analysis and diagnosis of car accidents. His work will mostly involve mathematical modeling these two modules. During this period, he will work very closely with the Ph.D. students on these research subjects. Finally, the post-doctoral fellow will review overall integration details as well as results from laboratory and on-road tests. A critical aspect of his work will be to ensure that lessons learned from on-road tests make their way back into the design process as it is taking place. The post-doctoral fellow will also focus on the interoperability and robustness aspects and on the improvement that could be done in order to obtain a simple and compact platform, using a simplified and non-intrusive architecture.
