# Optimal Control and Coordination of Connected and Automated Vehicles at Urban Traffic Intersections

arXiv: https://arxiv.org/abs/1509.08689 · HTML: https://mlsanity.com/paper/1509.08689/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2015.

## Built on by (most cited first, 2 of 2)

- [Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections](https://mlsanity.com/paper/2201.07833/) (2022)
- [Neural Solvers for Fast and Accurate Numerical Optimal Control](https://mlsanity.com/paper/2203.08072/) (2022)

## Abstract (arXiv)

We address the problem of coordinating online a continuous flow of connected and automated vehicles (CAVs) crossing two adjacent intersections in an urban area. We present a decentralized optimal control framework whose solution yields for each vehicle the optimal acceleration/deceleration at any time in the sense of minimizing fuel consumption. The solu- tion, when it exists, allows the vehicles to cross the intersections without the use of traffic lights, without creating congestion on the connecting road, and under the hard safety constraint of collision avoidance. The effectiveness of the proposed solution is validated through simulation considering two intersections located in downtown Boston, and it is shown that coordination of CAVs can reduce significantly both fuel consumption and travel time.