# Heterogeneous Mixed Traffic Control and Coordination

arXiv: https://arxiv.org/abs/2409.12330 · HTML: https://mlsanity.com/paper/2409.12330/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2024.

## Built on by (most cited first, 7 of 7)

- [Mixture-of-Personas Language Models for Population Simulation](https://mlsanity.com/paper/2504.05019/) (2025)
- [Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learning](https://mlsanity.com/paper/2504.04691/) (2025)
- [Exploring Transformer-Augmented LSTM for Temporal and Spatial Feature Learning in Trajectory Prediction](https://mlsanity.com/paper/2412.13419/) (2024)
- [Neighbor-Aware Reinforcement Learning for Mixed Traffic Optimization in Large-scale Networks](https://mlsanity.com/paper/2412.12622/) (2024)
- [LDGNet: A Lightweight Difference Guiding Network for Remote Sensing Change Detection](https://mlsanity.com/paper/2504.05062/) (2025)
- [Multi-Objective Reinforcement Learning for Large-Scale Mixed Traffic Control](https://mlsanity.com/paper/2512.11247/) (2025)
- [Learning to Design City-scale Transit Routes](https://mlsanity.com/paper/2512.19767/) (2025)

## Abstract (arXiv)

Urban intersections with diverse vehicle types, from small cars to large semi-trailers, pose significant challenges for traffic control. This study explores how robot vehicles (RVs) can enhance heterogeneous traffic flow, particularly at unsignalized intersections where traditional methods fail during power outages. Using reinforcement learning (RL) and real-world data, we simulate mixed traffic at complex intersections with RV penetration rates ranging from 10% to 90%. Results show that average waiting times drop by up to 86% and 91% compared to signalized and unsignalized intersections, respectively. We observe a "rarity advantage," where less frequent vehicles benefit the most (up to 87%). Although CO2 emissions and fuel consumption increase with RV penetration, they remain well below those of traditional signalized traffic. Decreased space headways also indicate more efficient road usage. These findings highlight RVs' potential to improve traffic efficiency and reduce environmental impact in complex, heterogeneous settings.