Cyber Security of Traffic Signal Control Systems with Connected Vehicles

Our world is becoming increasingly connected through smart technologies. The same trend is emerging in transportation systems, wherein connected vehicles (CVs) and transportation infrastructure are being connected through advanced wireless communication technologies. CVs have great potential to improve a variety of mobility applications, including traffic signal control (TSC), a critical component in urban traffic operations. CV-based TSC (CV-TSC) systems use trajectory data to make more informed control decisions, therefore can accommodate real-time traffic fluctuations more efficiently. However, vehicle-infrastructure connectivity opens new doors to potential cyber attacks. Malicious attackers can potentially send falsified trajectory data to CV-TSC systems and influence signal control decisions. The benefit of CV-TSC systems can be realized only if the systems are secure in cyberspace. Although many CV-TSC systems have been developed within the past decade, few consider cyber security in their system design. It remains unclear exactly how vulnerable CV-TSC systems are, how cyber attacks may be perpetrated, and how engineers can mitigate cyber attacks and protect CV-TSC systems. Therefore, this dissertation aims to systematically understand the cyber security problems facing CV-TSC systems under falsified data attacks and provide a countermeasure to safeguard CV-TSC systems. These objectives are accomplished through four studies. The first study evaluates the effects of falsified data attacks on TSC systems. Two TSC systems are considered: a conventional actuated TSC system and an adaptive CV-TSC system. Falsified data attacks are assumed to change the input data to these systems and therefore influence control decisions. Numerical examples show that both systems are vulnerable to falsified data attacks. The second study investigates how falsified data attacks may be perpetrated in a realistic setting. Different from prior research, this study considers a more realistic but challenging black-box attack scenario, in which the signal control model is unavailable to the attacker. Under this constraint, the attacker has to learn the signal control model using a surrogate model. The surrogate model predicts signal timing plans based on critical traffic features extracted from CV data. The attacker can generate falsified CV data (i.e., falsified vehicle trajectories) to alter the values of critical traffic features and thus influence signal control decisions. In the third study, a data-driven method is proposed to protect CV-TSC systems from falsified data attacks. Falsified trajectories are behaviorally distinct from normal trajectories because they must accomplish a certain attack goal; thus, the problem of identifying falsified trajectories is considered an abnormal trajectory identification problem. A trajectory-embedding model is developed to generate vector representations of trajectory data. The similarity (distance) between each pair of trajectories can be computed based on these vector representations. Hierarchical clustering is then applied to identify abnormal (i.e., falsified) trajectories. In the final study, a testing platform is built upon a virtual traffic simulator and real-world transportation infrastructure in Mcity. The testing platform integrates the attack study and defense study in a unified framework and is used to evaluate the real-world impact of cyber attacks on CV-TSC systems and the effectiveness of defense strategies.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162931/1/edhuang_1.pd

Intersection Management, Cybersecurity, and Local Government: ITS Applications, Critical Issues, and Regulatory Schemes

This article focuses on the cybersecurity issues of intersection management—an element of transportation management systems—for local governments. Until relatively recently, concerns about and research needs for intersection cybersecurity have been largely ignored, and local governments have focused on other types of cyber threats, relying instead on private sector vendors to provide equipment that is safe against attacks. To address the gap in the literature, this article provides a short overview of the types of components used in intelligent transportation systems (ITS) and reviews the critical issues for local governments. Further, it discusses some current efforts to remediate the vulnerabilities in ITS and examines the current regulatory framework. This review of the issues is augmented by an analysis of local government perspectives using the Delphi method. The article concludes with some recommendations

Generalized Proportional Allocation Policies for Robust Control of Dynamical Flow Networks

We study a robust control problem for dynamical flow networks. In the considered dynamical models, traffic flows along the links of a transportation network --modeled as a capacited multigraph-- and queues up at the nodes, whereby control policies determine which incoming queues at a node are to be allocated service simultaneously, within some predetermined scheduling constraints. We first prove a fundamental performance limitation by showing that for a dynamical flow network to be stabilizable by some control policy it is necessary that the exogenous inflows belong to a certain stability region, that is determined by the network topology, link capacities, and scheduling constraints. Then, we introduce a family of distributed controls, referred to as Generalized Proportional Allocation (GPA) policies, and prove that they stabilize a dynamical transportation network whenever the exogenous inflows belong to such stability region. The proposed GPA control policies are decentralized and fully scalable as they rely on local feedback information only. Differently from previously studied maximally stabilizing control strategies, the GPA control policies do not require any global information about the network topology, the exogenous inflows, or the routing, which makes them robust to demand variations and unpredicted changes in the link capacities or the routing decisions. Moreover, the proposed GPA control policies also take into account the overhead time while switching between services. Our theoretical results find one application in the control of urban traffic networks with signalized intersections, where vehicles have to queue up at junctions and the traffic signal controls determine the green light allocation to the different incoming lanes

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encour-aging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility‐as‐a‐service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope