mpc_connected_cars - ARPA-E NEXTCAR Phase II

ARPA-E NEXTCAR Phase II

The Experimental Platform

▲ IONIQ5

▲ IONIQ PHEV

▲ IONIQ 5 - Component Layout

▲ IONIQ PHEV sensors and Vehicle-to-Infrastructure (V2I) Communication setup

Vehicle-in-the-loop (VIL) setup

Simulation: All surrounding vehicles and some traffic lights are simulated.

Real-world: Energy measurements, V2I communication with the traffic lights, Planning, and Control in the actual test vehicle.

Interaction: The actual vehicle interacts with the surrounding simulated vehicles and vice versa.

Untitled video - Made with Clipchamp.mp4

▲ Synchronization between the real-world test and the simulation

▲ Overall block diagram of VIL setup

Our Demos

Connected Arterial Eco Motion Planning and Control

In this demo, the ego vehicles drive autonomously through a corridor of signalized intersections. We aim to improve the energy performance of our ego vehicles by (i) optimizing longitudinal acceleration/deceleration using traffic light signals (V2I), (ii) predicting the future energy consumption in each lane and executing opportunistic lane changes (V2C), and (iii) forming a platoon for smooth driving (V2V).

Publications and Media:

Eco Parking and Charging

In this demo, the ego vehicles (or ego vehicle fleet) autonomously drive and park at the assigned parking/charging spots which are computed based on our algorithms. We plan to save energy in our ego vehicles (or ego vehicle fleet) by (i) coordinating their vehicle motions (V2V/V2I), (ii) powertrain optimization, and (iii) charging management (V2I, grid efficiency).

Publications:

X Shen, EY Choi, A Wong, F Borrelli, S Moura, and S Woo, "Parking of Connected Automated Vehicles: Vehicle Control, Parking Assignment, and Multi-agent Simulation," in arXiv preprint arXiv:2402.14183

Eco E-Fleet Dispatching

In this demo, the ego vehicle fleet follows the given route to complete the stops (destinations) given by our dispatching algorithms. Our goal is to improve the overall energy performance of our ego vehicle fleet by (i) route coordination, (ii) optimizing powertrain, (iii) predictive charging, and (iv) charging coordination.

Publications:

S. Woo, EY. Choi, SJ. Moura, and F. Borrell, "Saving Energy with Eco-friendly Routing of an Electric Vehicle Fleet," to be appeared in Transportation Research Part E.