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Detecting Subtle Cyberattacks on Adaptive Cruise Control Vehicles: A Machine Learning Approach
With the emergence of vehicles featuring advanced driver-assistance systems like adaptive cruise control (ACC) and additional automated driving functionalities, there has arisen a heightened potential for cyberattacks targeting these automated vehicles (AVs). While overt attacks that lead to collisions are more conspicuous, subtle attacks that slightly modify driving behaviors can cause widespread...Show More
A Customizable Neural Network Based Framework for Autonomous Vehicle Control with Human-Guided Learning
Tianyi Li;Shian Wang;Mingfeng Shang;Seongjin Choi;Raphael Stern
2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2024 | Conference Paper |
This study introduces a novel control framework for adaptive cruise control (ACC) in autonomous vehicles (AVs), utilizing Long Short-Term Memory (LSTM) networks and physics-informed constraints. The LSTM component captures complex vehicle dynamics and temporal dependencies, while physics constraints ensure realistic operational limits. This framework supports customization of control objectives, a...Show More
Analysis and Applications of Population Flows in a Networked SEIRS Epidemic Process
Transportation networks play a critical part in the spread of infectious diseases between populations. In this work, we define a networked susceptible-exposed-infected-recovered epidemic process with loss of immunity over time (SEIRS) that explicitly models the flow of individuals between sub-populations, which serves as the propagating mechanism for infection. We provide sufficient conditions for...Show More
Analytical Characterization of Cyberattacks on Adaptive Cruise Control Vehicles
While automated vehicles (AVs) are expected to revolutionize future transportation systems, emerging AV technologies also open the door for malicious actors to compromise intelligent vehicles. As the first generation of AVs, adaptive cruise control (ACC) vehicles are particularly vulnerable to cyberattacks. Although recent efforts have been made to understand the impact of attacks on transportatio...Show More
Automated vehicles (AVs) hold the potential to significantly improve traffic flow, reducing travel time, energy consumption, and emissions. However, until AVs achieve high market penetration rates, navigating the transition to mixed-autonomy traffic — comprising both AVs and human-driven vehicles (HVs) — presents substantial challenges. While numerous studies have concentrated on AV control within...Show More
Automated Vehicles (AVs), particularly those with Adaptive Cruise Control (ACC), are increasingly integral to intelligent transportation systems, but they bring new cybersecurity challenges. This study explores the subtleties of cyberattacks targeting ACC vehicles, specifically through false data injection, and assesses their impact on traffic dynamics. We innovatively adapt and implement strategi...Show More
The Electric Vehicle Model (EVM): A Novel Car-Following Model for Electric Adaptive Cruise Control Vehicles
2024 Forum for Innovative Sustainable Transportation Systems (FISTS)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Electric vehicle (EV) adoption is accelerating across the automotive industry. The first generation of electrified vehicles with driver assistance features like adaptive cruise control (ACC) are now commercially available. While studies have highlighted the sustainability benefits of EVs, recent research suggests these EVs may impact traffic flow differently than traditional internal combustion en...Show More
A Two-Condition Continuous Asymmetric Car-Following Model for Adaptive Cruise Control Vehicles
Adaptive cruise control (ACC) vehicles have the potential to impact traffic flow dynamics. To better understand the impacts of ACC vehicles on traffic flow, an accurate microscopic car-following model for ACC vehicles is essential. Most of the ACC car-following models utilize a continuous function to describe vehicle acceleration and braking, e.g., the optimal velocity relative velocity (OVRV) mod...Show More
Modeling Car-Following Behavior of Electric Adaptive Cruise Control Vehicles Using Experimental Testbed Data
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Automated vehicles (AVs) have the potential to revolutionize the transportation industry. While extensive research has been conducted to explore the benefits of AVs on traffic flow, commercially available adaptive cruise control (ACC) vehicles with advanced driver assistance features have been shown adverse effects on traffic flow. As vehicle automation advances, electric vehicles (EVs) equipped w...Show More
Capacity implications of personalized adaptive cruise control
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
With the emergence, advancement, and development of automated vehicle (AV) technologies, adaptive cruise control (ACC) is becoming increasingly relevant in commercially available vehicles. While fully automated vehicles promise numerous benefits, recent studies suggest that ACC vehicles may have adverse effects on traffic flow. Although considerable research has been devoted to investigating the e...Show More
Impacts of mixed autonomy traffic flow with adaptive cruise control vehicles on fuel consumption and emissions
2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The first generation of automated vehicles has already begun to appear on our roads in the form of adaptive cruise control (ACC). Although studies have found that ACC vehicles may theoretically improve traffic flow, recent findings show that commercially-available ACC vehicles may instead deteriorate traffic conditions. However, it is still unclear how ACC vehicles and more advanced AVs in the tra...Show More
Exploring Energy Impacts of Cyberattacks on Adaptive Cruise Control Vehicles
Tianyi Li;Benjamin Rosenblad;Shian Wang;Mingfeng Shang;Raphael Stern
The emergence of automated vehicles (AVs) with driver-assist features, such as adaptive cruise control (ACC) and other automated driving capabilities, promises a bright future for transportation systems. However, these emerging features also introduce the possibility of cyberattacks. A select number of ACC vehicles could be compromised to drive abnormally, causing a network-wide impact on congesti...Show More
A Network Traffic Model for the Control of Autonomous Vehicles Acting as Moving Bottlenecks
In this work we present a traffic model to simulate network-level traffic evolution under the impact of controlled autonomous vehicles acting as moving bottlenecks. We first extend the Newell-Daganzo method to track the trajectories of moving bottlenecks and calculate the cumulative number of vehicles passing each moving bottleneck. By integrating the solutions to the cumulative number of vehicles...Show More
New frontiers of freeway traffic control and estimation
2022 IEEE 61st Conference on Decision and Control (CDC)
Year: 2022 | Conference Paper |
Cited by: Papers (6)
This article provides an overview of the classical and new techniques in traffic flow control and estimations. The overview begins with a description of the most used traffic flow models for estimation and control. Then, it shifts towards using those models for traffic flow estimation using physics-informed machine learning techniques. Lastly, it focuses on traffic flow control describing the most...Show More
Modeling Adaptive Cruise Control Vehicles: A Continuous Asymmetric Car-Following Perspective
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Adaptive cruise control (ACC) vehicles are the first generation of automated vehicles. Studying the traffic impacts of commercially available ACC vehicles is an initial and crucial step before fully automated vehicles become widely available in the market. Many studies focus on modeling the behavior of ACC vehicles with a microscopic car-following model where a single continuous function has been ...Show More
Detecting Stealthy Cyberattacks on Automated Vehicles via Generative Adversarial Networks
Tianyi Li;Mingfeng Shang;Shian Wang;Matthew Filippelli;Raphael Stern
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2022 | Conference Paper |
Cited by: Papers (16)
The emergence of vehicles with driver-assist features, including adaptive cruise control (ACC) or other automated driving capabilities, introduces the possibility of cyberattacks where a select number of automated vehicles (AVs) are compromised to drive with adversarial controls. While obvious attacks that force vehicles to crash may be easily detectable, more subtle attacks are harder to detect a...Show More
Smoothing Nonlinear Mixed Traffic with Autonomous Vehicles: Control Design
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
Stop-and-go waves are easily caused by unstable traffic due to the collective behavior of human drivers, resulting in higher fuel consumption and emissions. In this article, we aim to smooth unstable mixed traffic flow in the presence of both autonomous vehicles (AVs) and human-driven vehicles (HVs), via feedback control of AVs. Unlike prior studies focused on analyzing head-to-tail string stabili...Show More
Robustness of vehicle identification via trajectory dynamics to noisy measurements and malicious attacks
2022 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop (DI-CPS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
The possibility of using infrastructure-based sensors to identify individual vehicles, and then actuate transportation control infrastructure in response to their individual dynamics will enable to next generation of traffic infrastructure control. However, any such system to identify individual vehicles in the flow will be prone to faulty data or worse, cyberattacks where a malicious actor intent...Show More
A Novel Asymmetric Car Following Model for Driver-Assist Enabled Vehicle Dynamics
Adaptive cruise control (ACC) vehicles are proving to be the first generation of driver-assist enabled vehicles. In order to study the impacts of ACC vehicles on string stability and traffic flow characteristics, accurately calibrating microscopic car following models is crucial to simulate inter-vehicle dynamics. While many car following models have been used to simulate car following behavior, a...Show More
Optimal Control of Autonomous Vehicles for Traffic Smoothing
Uniform traffic flow has been shown to be unstable in certain flow regimes due to collective behaviors of human drivers, resulting in the well-observed stop-and-go waves. These traffic waves can arise even in the absence of merges, bottlenecks, or lane changing, and may lead to higher vehicle fuel consumption and emissions. In this article, we aim to smooth unstable traffic flow via optimal contro...Show More
Capturing the Effects of Transportation on the Spread of COVID-19 With a Multi-Networked SEIR Model
Damir Vrabac;Mingfeng Shang;Brooks Butler;Joseph Pham;Raphael Stern;Philip E. Paré
In this letter we present a deterministic discrete-time networked SEIR model that includes a number of transportation networks, and present assumptions under which it is well defined. We analyze the limiting behavior of the model and present necessary and sufficient conditions for estimating the spreading parameters from data. We illustrate these results via simulation and with real COVID-19 data ...Show More
The Effect of Population Flow on Epidemic Spread: Analysis and Control
Brooks Butler;Ciyuan Zhang;Ian Walter;Nishant Nair;Raphael Stern;Philip E. Paré
2021 60th IEEE Conference on Decision and Control (CDC)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
In this paper, we present a discrete-time networked SEIR model using population flow, its derivation, and assumptions under which this model is well defined. We identify properties of the system’s equilibria, namely the healthy states. We show that the set of healthy states is asymptotically stable, and that the value of the equilibria becomes equal across all sub-populations as a result of the ne...Show More
Classification of adaptive cruise control vehicle type based on car following trajectories
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
The emergence of vehicles with driver-assist features or other automated driving capabilities has been shown to dramatically alter traffic dynamics at the aggregate level. These new traffic flow dynamics usher in the possibility for specialized traffic control based on the types of vehicles with differing car following dynamics and the resulting shift and macroscopic traffic flow behavior. To enab...Show More
A hybrid fundamental diagram for modeling mixed human and automated traffic flow
2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
Automated and partially automated vehicles will substantially change the way traffic flows, even at low market penetration rates. While the primary tool for analysis of mixed human-piloted and automated traffic has been microscopic simulation, the use of macroscopic traffic simulation allows for larger-scale simulations. With that in mind we propose a simple numerical method to estimate the compos...Show More
Modeling oscillatory car following using deep reinforcement learning based car following models
2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
In this work, we use reinforcement learning (RL) to train a car following model for vehicle jerk. The learned model is specifically trained for car following in low-speed oscillatory driving conditions such as stop-and-go traffic typical in congested urban centers. This driving is of particular interest since it is difficult to model and substantially contributes to urban air pollution. The propos...Show More
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