Welcome to SIAS: Social Interactive Autonomous Systems Lab
At SIAS, we envision a future where mobility is seamlessly integrated with intelligent, automated agents such as autonomous vehicles (AVs). Our mission is to pioneer advancements in the design and control of future mobility systems involving intelligent autonomous agents, ensuring they enhance and harmonize with the societal fabric.
Our research operates at the dynamic intersection of game theory, multi-agent systems, control and optimization, and machine learning. By weaving these disciplines together, we aim to develop robust, efficient, and sustainable technologies that transform the intelligent transportation systems of tomorrow. In doing so, we seek not only to innovate but also to elevate the societal benefits of such integrations, making safer, more accessible, and more equitable mobility solutions a reality for all.
The following summary outlines current ongoing directions from a specific perspective, focusing primarily on goals and applications, rather than delving into methodological details.
Unlocking the Potential of AVs in Intelligent Transportation Systems
The enhanced controllability of autonomous vehicles opens up a myriad of possibilities. For example, autonomous vehicles can be platooned with shorter headways, which increase road capacities, or they can act on information as altruistic decision-makers, thereby improving societal benefits. Such versatility demands the development of innovative models and presents a series of challenging tasks.
Representative publications:
Exploring the Potential of Autonomous Vehicles in Mixed Autonomy Transportation Systems
Ruolin Li. University of California, Berkeley, 2023. [Dissertation]
Employing Altruistic Vehicles at On-Ramps to Improve Social Traffic Conditions
Ruolin Li, Philip N. Brown, and Roberto Horowitz. American Control Conference (ACC), 2021.
A Unified Toll Lane Framework for Autonomous and High-Occupancy Vehicles in Interactive Mixed Autonomy
Ruolin Li, Philip N. Brown, and Roberto Horowitz. arXiv:2403.14011, 2024.
The Impact of Autonomous Vehicles’ Headway on the Social Delay of Traffic Networks
Ruolin Li, Negar Mehr, and Roberto Horowitz. IEEE Conference on Decision and Control (CDC), 2020.
Dynamic Routing and Queueing for Human-driven and Autonomous Vehicles with Responsive Signal Controls
Ruolin Li and Roberto Horowitz. American Control Conference (ACC), 2022.
React and Interact: Harmonizing AVs with Humans
Modeling human behavior in transportation systems is crucial yet challenging. Imagine drivers mischievously cutting in front of slowly moving autonomous vehicles just for fun! The impact of autonomous vehicles is significantly influenced by human reactions and interactions. Therefore, it is essential to investigate human behaviors and design control and optimization strategies for AVs that are resilient to such uncertainties.
Representative publications:
A Game-Theoretic Model for Aggregate Lane Choice Behavior of Highway Mainline Vehicles at the Vicinity of On-ramps
Ruolin Li, Jiaxi Liu, and Roberto Horowitz. American Control Conference (ACC), 2020.
An Extended Game–Theoretic Model for Aggregate Lane Choice Behavior of Vehicles at Traffic Diverges with a Bifurcating Lane
Ruolin Li, Negar Mehr, and Roberto Horowitz. IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
A Game-Theoretic Model for Aggregate Bypassing Behavior of Vehicles at Traffic Diverges Negar Mehr, Ruolin Li, and Roberto Horowitz. Transportation Research Part B: Methodological 144: 45-59, 2020.
Employing Altruistic Vehicles at On-Ramps to Improve Social Traffic Conditions
Ruolin Li, Philip N. Brown, and Roberto Horowitz. American Control Conference (ACC), 2021.
Optimization on Networks with Societal Awareness: Control and Impact
Transportation systems represent a complex and intricate network involving multiple parties and stakeholders. To achieve a sweet balance of societal benefits and individual interests, it is crucial to design optimization strategies that consider the diverse needs and objectives of different entities. The goal is to ensure that the system is equitable, efficient, and responsive to the varying demands of its users.
Representative publications:
The Impact of Autonomous Vehicles’ Headway on the Social Delay of Traffic Networks
Ruolin Li, Negar Mehr, and Roberto Horowitz. IEEE Conference on Decision and Control (CDC), 2020.
Dynamic Routing and Queueing for Human-driven and Autonomous Vehicles with Responsive Signal Controls
Ruolin Li and Roberto Horowitz. American Control Conference (ACC), 2022.
Submodularity of Optimal Sensor Placement Problems for Traffic Networks
Ruolin Li, Negar Mehr, and Roberto Horowitz. Transportation Research Part B: Methodological 171: 29-43, 2023.
Re-engineering Transportation Systems for AV Integration
Autonomous vehicles and existing transportation infrastructure are intricately linked. The challenge lies in managing or reshaping our current infrastructure to accommodate AVs efficiently and economically. How can we adapt our roads, signaling systems, and urban planning to meet the demands of AV technology? Insights into the dynamic interaction between robotic AVs and infrastructure optimization can guide us in creating cost-effective, efficient solutions that pave the way for the future of transportation.
Representative publications:
A Unified Toll Lane Framework for Autonomous and High-Occupancy Vehicles in Interactive Mixed Autonomy
Ruolin Li, Philip N. Brown, and Roberto Horowitz. arXiv:2403.14011, 2024.
A Highway Toll Lane Framework that Unites Autonomous Vehicles and High-Occupancy Vehicles
Ruolin Li, Philip N. Brown, and Roberto Horowitz. IEEE Intelligent Transportation Systems Conference (ITSC), 2021.
Visit Ruolin's CV or Google Scholar to view a comprehensive list of publications.