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Job Description
This position involves working on a project related to path planning and collision avoidance for autonomous vehicles (AVs), based on deep reinforcement learning, and in particular communication learning among agents (i.e., vehicles), as well as between AVs and infrastructure (e.g., traffic lights). The objective of this position includes contributing to the model development, solutioning, and implementation of robust decentralized controllers for safe traffic junction management by AVs using machine learning methods. The role involves the opportunity to work with the research team within the National University of Singapore in which the team leaders are from the Department of Mechanical Engineering, and Specialists from a high technology company. The successful candidate will be self-motivated with an outstanding track record in computer science, machine learning (in particular, reinforcement learning), or transportation and related disciplines.
The main research tasks for the project include but will not be limited to:
• Developing robust centralized and decentralized controllers for the path planning and collision avoidance of AVs at traffic junctions, based on local sensing at the junction and communication learning among AVs, as well as between vehicles and infrastructure.
• Developing models that can optimize traffic flow, safety, and overall quality of life of human-driven and AVs.
• Testing and optimizing the scalability of the devised controllers in larger scenarios in simulation.
• Designing and implementing controllers on hardware to obtain a laboratory-level prototype system.
Qualifications
• BEng/BSc/MEng/MSc in Operations Research, Computer Science, Engineering ,Transportation, or related disciplines.
• Experience in developing/applying data-driven models in transportation or big-data related projects.
• Proficiency with GNU/Linux, Python/C++ and at least one of the main machine learning libraries (e.g., pytorch, tensorflow, keras).
• Excellent interpersonal and communication skills.
• Good teamwork abilities, self-motivation and self-reflection.
• Proficiency in English language.
Prioritized Requirements:
• Experience/Knowledge in machine learning, and in particular (distributed) reinforcement learning and communication learning.
• Experience/Interest in traffic related problems, autonomous vehicles, and transportation theory.
• Experience with simulation, and transitions between simulation and actual robotic prototyping.
