摘要: |
The objective of this research is to advance the understanding and use of machine learning
(ML) tools and techniques at state DOTs and other transportation agencies. The proposed research will aid state DOTs in transitioning to a more advanced state of practice by:
(1) Demonstrating the feasibility and practical value of ML in the context of transportation systems, to better understand its application opportunities, implementation processes, and data requirements.
(2) Identifying skills, capabilities, resource, and organizational capacities necessary to leverage ML.
(3) Identifying and learning from existing applications at transportation agencies.
(4) Providing insight into costs, benefits, and performance and limitations considerations.
(5) Identifying and sharing ML frameworks, tools, guidance, and ML code for common use cases. |