# Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning

arXiv: https://arxiv.org/abs/2111.13966 · HTML: https://mlsanity.com/paper/2111.13966/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving.
- Builds on 13 of its 50 references that are in the map.
- First posted on arXiv 27 Nov 2021.

## Placed in

- End-to-end autonomous driving / [Cooperative and V2X driving](https://mlsanity.com/driving/cooperative-and-v2x-driving/)

## Builds on (most cited first, 13 of 13)

- [Deep Reinforcement Learning for Autonomous Driving: A Survey](https://mlsanity.com/paper/2002.00444/) (2020)
- [A Survey of Deep Learning Techniques for Autonomous Driving](https://mlsanity.com/paper/1910.07738/) (2019)
- [A Survey of Deep Learning Applications to Autonomous Vehicle Control](https://mlsanity.com/paper/1912.10773/) (2019)
- [Game-Theoretic Modeling of Driver and Vehicle Interactions for Verification and Validation of Autonomous Vehicle Control Systems](https://mlsanity.com/paper/1608.08589/) (2016)
- [Control of Connected and Automated Vehicles: State of the Art and Future Challenges](https://mlsanity.com/paper/1804.03757/) (2018)
- [Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections](https://mlsanity.com/paper/1904.05423/) (2019)
- [Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation](https://mlsanity.com/paper/1910.07141/) (2019)
- [Decentralized Optimal Coordination of Connected and Automated Vehicles for Multiple Traffic Scenarios](https://mlsanity.com/paper/2003.05059/) (2020)
- [Combined Energy and Comfort Optimization of Air Conditioning System in Connected and Automated Vehicles](https://mlsanity.com/paper/1909.12448/) (2019)
- [Decentralized Cooperative Merging of Platoons of Connected and Automated Vehicles at Highway On-Ramps](https://mlsanity.com/paper/2002.04826/) (2020)
- [Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks](https://mlsanity.com/paper/2004.05161/) (2020)
- [Coordinated Receding-Horizon Control of Battery Electric Vehicle Speed and Gearshift Using Relaxed Mixed Integer Nonlinear Programming](https://mlsanity.com/paper/2102.09014/) (2021)
- [MultiCruise: Eco-Lane Selection Strategy with Eco-Cruise Control for Connected and Automated Vehicles](https://mlsanity.com/paper/2104.11959/) (2021)

## Abstract (arXiv)

Autonomous driving technologies are expected to not only improve mobility and road safety but also bring energy efficiency benefits. In the foreseeable future, autonomous vehicles (AVs) will operate on roads shared with human-driven vehicles. To maintain safety and liveness while simultaneously minimizing energy consumption, the AV planning and decision-making process should account for interactions between the autonomous ego vehicle and surrounding human-driven vehicles. In this chapter, we describe a framework for developing energy-efficient autonomous driving policies on shared roads by exploiting human-driver behavior modeling based on cognitive hierarchy theory and reinforcement learning.