4.7 Article

Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

Journal

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
Volume 91, Issue -, Pages 366-382

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trb.2016.05.017

Keywords

Traffic optimization; Ramp metering; Cybersecurity; Multi-objective optimization

Funding

  1. FORCES (Foundations Of Resilient CybEr-Physical Systems) from the National Science Foundation (NSF) [CNS-1238959, CNS-1238962, CNS-1239054, CNS-1239166]
  2. California Department of Transportation under the Connected Corridors program

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This article presents a study on freeway networks instrumented with coordinated ramp metering and the ability of such control systems to produce arbitrarily complex congestion patterns within the dynamical limits of the traffic system. The developed method is used to evaluate the potential for an adversary with access to control infrastructure to enact high-level attacks on the underlying freeway system. The attacks are executed using a predictive, coordinated ramp metering controller based on finite-horizon optimal control and multi-objective optimization techniques. The efficacy of the control schemes in carrying out the prescribed attacks is determined via simulations of traffic network models based on the cell transmission model with onramps modeled as queue buffers. Freeway attacks with high-level objectives are presented on two illustrative examples: congestion on-demand, which aims to create precise, user-specified pockets of congestion, and catch me-if-you-can, which attempts to aid a fleeing vehicle from pursuant vehicles. (C) 2016 Elsevier Ltd. All rights reserved.

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