Real-World Travel Time Data from RITIS.org for the Washington, DC Metropolitan Area

This dataset provides real-world travel time data from RITIS.org, specifically covering the Washington, DC Metropolitan Area. The data records travel time variations across multiple road segments at 15-minute intervals, reflecting time-dependent traffic patterns. It is primarily used for Electric Vehicle (EV) routing optimization, integrating Deep Reinforcement Learning (DRL), Temporal Multimodal Multivariate Learning (TMML), and the Time-Dependent Shortest Path (TDSP) algorithm. The dataset includes travel times, probability distributions for travel time uncertainties.Bayesian updates can be used based on real-time observations. This dataset supports intelligent transportation systems, enabling real-time decision-making for EV routing, energy management, and dynamic charging infrastructure planning in urban environments.