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In this work, we develop an eco-driving algorithm for Connected and Automated Vehicles (CAVs) to reduce their energy consumption for urban corridor scenarios. The proposed algorithm considers the uncertainty from both the adaptive traffic signals and the surrounding traffic, thereby increasing its suitability for real-world deployment. In this hierarchical approach, the higher level makes global passing decisions and computes speed targets for further intersections, while the lower level generates smooth and safe speed trajectories. The performance of the algorithm is then demonstrated for an electric vehicle model through extensive (traffic) simulations. Across these experiments, 8-12% energy savings is observed compared to the baseline algorithm.