Demonstration of a Time-Efficient Mobility System Using a Scaled Smart City
arXiv:1903.01632 · doi:10.1080/00423114.2020.1730412
Abstract
The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework to deliver real-time control actions that optimize travel time, energy, and safety. Hardware is an integral part of any practical implementation of CAVs, and as such, it should be incorporated in any validation method. However, high costs associated with full scale, field testing of CAVs have proven to be a significant barrier. In this paper, we present the implementation of a decentralized control framework, which was developed previously, in a scaled-city using robotic CAVs, and discuss the implications of CAVs on travel time. Supplemental information and videos can be found at https://sites.google.com/view/ud-ids-lab/tfms.
References in corpus (2)
Cited by in corpus (10)
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- Beyond Reynolds: A Constraint-Driven Approach to Cluster Flocking
- A Digital Smart City for Emerging Mobility Systems
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