Real-time AI-enabled Optimized Motion Planning of Connected Autonomous Vehicles in Urban Transportation Networks

Project: Research

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Description

Key features in future transportation systems are expected to include autonomy, connectivity and electrification. Planned industry investments of 100s of billions of dollars point to future autonomous and smart transportation systems, where safety, mobility, and comfort are greatly improved, and fuel consumption and pollution are significantly reduced. This project will develop motion planning optimization techniques for a system of connected and autonomous vehicles (CAVs). This will be done in order to ensure both safety (first and foremost) and smooth driving without excessive delay with an eye towards saving energy and reducing costs associated with congestion. Safety is achieved by imposing strict constraints based on safety requirements. In very rare events, life and death decisions are made by a CAV that dictate trajectory decisions in such events that are part of motion planning. A public survey will be performed to understand society acceptance of such decisions.  

Detail(s)

Project number7020007
Grant typeSIRG
StatusActive
Effective start/end date30/06/21 → …