# Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks

arXiv: https://arxiv.org/abs/2004.05161 · HTML: https://mlsanity.com/paper/2004.05161/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Apr 2020.

## Built on by (most cited first, 1 of 1)

- [Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning](https://mlsanity.com/paper/2111.13966/) (2021)

## Abstract (arXiv)

We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and an optimal power-train control strategy over this route. In order to show the effectiveness of our method in practice, we use a HERE Maps API to apply our algorithms based on traffic data in the city of Boston with more than 110,000 links. Moreover, we validate the performance of our eco-routing algorithm using speed profiles collected from a traffic simulator (SUMO) as input to a high-fidelity energy model to calculate energy consumption costs. Our results show significant energy savings (around 12%) for PHEVs with a near real-time execution time for the algorithm.