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Autonomous driving systems depend on their ability to perceive and understand their environments for navigation. Neural networks are the building blocks of such perception systems, and training these networks requires vast amounts of diverse training data that includes different kinds of driving...
GPS-based navigation systems have played crucial roles to improve transportation system performances. A limitation of such route guidance systems is that their route recommendation algorithms are mostly based on the shortest travel time and/or toll avoidance. To enhance the performance of route...
Network-wide traffic prediction at the level of an intersection can benefit transportation systems management and operations. However, traditional traffic modeling approaches relying on mathematical or simulation-based models are either less useful or require higher computational time in...
Nonrecurring traffic events, including improvement actions and vehicular accidents, cause traffic congestion and travel delay. The impact of a traffic event, even when the event is quickly cleared, may last considerably longer than the event itself and may be incurred over long distances. To...
Routine and consistent data collection is required to address contemporary transportation issues. The cost of data collection increases significantly when sophisticated machines are used to collect data. Due to this constraint, State Departments of Transportation struggle to collect consistent...
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