Safety

Multi-Adversarial Safety Analysis for Autonomous Vehicles

Bahati, Gilbert
Gibson, Marsalis
Bayen, Alexandre
2021

This work in progress considers reachability-based safety analysis in the domain of autonomous driving in multi-agent systems. We formulate the safety problem for a car following scenario as a differential game and study how different modelling strategies yield very different behaviors regardless of the validity of the strategies in other scenarios. Given the nature of real-life driving scenarios, we propose a modeling strategy in our formulation that accounts for subtle interactions between agents, and compare its Hamiltonian results to other baselines. Our formulation encourages...

A Rigorous Multi-Population Multi-Lane Hybrid Traffic Model for Dissipation of Waves via Autonomous Vehicles

Kardous, Nicolas
Hayat, Amaury
McQuade, Sean T.
Gong, Xiaoqian
Truong, Sydney
Bayen, Alexandre M.
2022

In this paper, a multi-lane multi-population microscopic model, which presents stop-and-go waves, is proposed to simulate traffic on a ring-road. Vehicles are divided between human-driven and autonomous vehicles (AV). Control strategies are designed with the ultimate goal of using a small number of AVs (less than 5% penetration rate) to represent Lagrangian control actuators that can smooth the multilane traffic flow and dissipate the traffic instabilities, and in particular stop-and-go waves. This in turn may reduce fuel consumption and emissions. The lane-changing mechanism is based on...

Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control

Wu, Fangyu
Wang, Guanhua
Zhuang, Siyuan
Wang, Kehan
Keimer, Alexander
Stoica, Ion
Bayen, Alexandre
2022

Model predictive control (MPC) is a powerful control method that handles dynamical systems with constraints. However, solving MPC iteratively in real time, i.e., implicit MPC, remains a computational challenge. To address this, common solutions include explicit MPC and function approximation. Both methods, whenever applicable, may improve the computational efficiency of the implicit MPC by several orders of magnitude. Nevertheless, explicit MPC often requires expensive pre-computation and does not easily apply to higher-dimensional problems. Meanwhile, function approximation, although...

Approaches for Synthesis and Deployment of Controller Models on Automated Vehicles for Car-following in Mixed Autonomy

Bhadani, Rahul
Bunting, Matthew
Nice, Matthew
Bayen, Alexandre M.
2023

This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software- and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed...

Connected and Automated Vehicle Technology is Not Enough; it Must also be Collaborative

Patire, Anthony D.
Dion, Francois
Bayen, Alexandre M.
2023

Connected and automated vehicles (CAVs) will revolutionize the way we travel; however, what impact this revolution will have on advancing broader societal goals is uncertain. To date, the private sector technology rollout has emphasized the automation side of CAVs and neglected the potentially transformative possibilities brought by a more collaborative notion of connectivity. This may have significant downsides from a broader societal perspective. For example, CAVs (including those on the road today) collect a vast amount of data gathered through onboard systems (e.g., radar, lidar,...

Pareto Control Barrier Function for Inner Safe Set Maximization Under Input Constraints

Cao, Xiaoyang
Fu, Zhe
Bayen, Alexandre M.
2024

This article introduces the Pareto Control Barrier Function (PCBF) algorithm to maximize the inner safe set of dynamical systems under input constraints. Traditional Control Barrier Functions (CBFs) ensure safety by maintaining system trajectories within a safe set but often fail to account for realistic input constraints. To address this problem, we leverage the Pareto multi-task learning framework to balance competing objectives of safety and safe set volume. The PCBF algorithm is applicable to high-dimensional systems and is computationally efficient. We validate its effectiveness...

Modeling, Monitoring, and Controlling Road Traffic Using Vehicles to Sense and Act

Monache, Maria Laura Delle
McQuade, Sean T.
Matin, Hossein Nick Zinat
Gloudemans, Derek A.
Wang, Yanbing
Gunter, George L.
Bayen, Alexandre M.
Lee, Jonathan W.
Piccoli, Benedetto
Seibold, Benjamin
Sprinkle, Jonathan M.
Work, Daniel B.
2025

This review offers a comprehensive overview of current traffic modeling, estimation, and control methods, along with resulting field experiments. It highlights key developments and future directions in leveraging technological advancements to improve traffic management and safety. The focus is on macroscopic, microscopic, and micro-macro models, as well as state-of-the-art control techniques and estimation methods for deploying vehicles in traffic field experiments.

Middleware for Cooperative Vehicle-Infrastructure Systems

Manasseh, Christian
Sengupta, Raja
2008

Middleware has emerged as an important architectural component in supporting distributed applications. The role of middleware is to present a unified programming model to application writers and to mask out problems of heterogeneity and distribution. Mobile sensors fall into the space of distributed systems that suffer from isolated data sources, heterogeneous communication infrastructure and varying application requirements. In this report, we provide a middleware architecture that addresses the needs of a distributed system made of mobile sensors in general and discuss the implementation...

Long Term Impacts of California’s Graduated Licensing Law of 1998

Cooper, Douglas
Gillen, David
2005

In July 1998 California changed its graduated driver licensing laws (GDL) for new drivers under the age of 18 to include restrictions on hours of driving, carrying teen-age passengers, and requiring more adult supervised driving practice. With fatal and injury crash data from California's Statewide Integrated Traffic Records System, this study, sponsored by Caltrans, used standard regression analysis as well as the Bai-Perron stochastic multiple structural break model to determine the effect of the law on teen-age passengers and crash rates of 16 year-old drivers. We found that in the four...

Collisions in Freeway Traffic: Influence of Downstream Queues and Interim Means to Address Them

Li, Zhibin
Chung, Koohong
Cassidy, Michael J.
2013

Findings from previous studies indicate that a freeway traffic collision is more likely to occur in close physical proximity to the tail of a queue. The implication is that collision likelihood increases when drivers abruptly alter their trajectories (e.g., by decelerating or changing lanes) on encountering the queue. The implication is supported and bolstered with new and detailed data that were painstakingly extracted from two freeway stretches in California. These data show how the likelihood of collision increases as both the spatial and the temporal proximities to the tail of an...