Intelligent Transportation Systems - Groups

T-6

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

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T-5

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

Dataset
JSON

T-4

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

Dataset
JSON

T-3

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

Dataset
JSON

T-2

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

Dataset
JSON

T-1

Real datasets extracted from GPS trajectories of 536 cabs in the San Francisco Bay Area over 30 days

Dataset
JSON

ST-GIN: An Uncertainty Quantification Approach in Traffic Data

Traffic data serves as a fundamental component in both research and applications within intelligent transportation systems. However, real-world transportation data, collected...

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Deep Q-Networks for Intelligent Transportation Systems

The dataset is used for Deep Q-Networks (DQN) to optimize real-time trafﬁc light control policies in emerging large-scale Intelligent Transportation Systems.

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Urban Traffic Flow Forecast Based on FastGCRNN

Traffic forecasting using timely information provided by Internet of Things technology(IoT) is an important prerequisite for the application of intelligent transportation...

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9 datasets found