Connected and Automated Vehicles

We apply virtual machine abstractions to networked vehicles, enabling what we call cloud computing in space to create performance isolation between customers. In analogy to conventional system virtualization and cloud computing, there are customer-operated virtual vehicles that essentially perform like real vehicles, although they are in reality hosted by fewer, shared, provider-operated real vehicles. The motion of the virtual vehicles and real vehicles creates migration gain. As a result, cloud computing in space can do better than conventional cloud computing in the sense of realizing...

Digital maps of the transportation network are the foundation of future mobility solutions. Autonomous and connected vehicles rely on real-time, at-scale updating of the environment in which they operate. Successful operation in a hybrid environment, where human and machine intelligence coexist, requires explicit knowledge of the traffic regulator infrastructure. Future generation traffic management strategies and path planning systems must be tightly integrated with the regulator infrastructure in order to improve traffic dynamics and reduce congestion in urban environments. In this...

Autonomous vehicles (AVs) are being widely tested and piloted to carry passengers and freight. However, the potential uses and impacts of AVs in communities are uncertain. There are claims that AVs may be able to improve road safety, make travel more convenient, lower shipping costs, and reduce the need for automobile parking. But there are also concerns that AVs may increase road congestion, reduce transit ridership, compete for curb space, and even increase urban sprawl. To better understanding how cities and regions are currently engaging with and planning for AVs, twenty interviews...

Motion planning of autonomous vehicles in understructured road environments is challenging owing to a lack of an efficient and analyzable representation of the contextual information. On one hand, idealistic representations like splines, while efficient and interpretable, are not versatile enough to encode the full complexity of the environment. On the other hand, high-fidelity representations like images, although rich in contents, are computationally expensive to decode and are not readily analyzable. To address this problem, we propose a new data structure named stacked reservation grid (...