Journal: IEEE Transactions on Network Science and Engineering

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IEEE

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2327-4697

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2015 - 201922020 - 20244
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Publications 1 - 6 of 6
  • The +1 Method: Model-Free Adaptive Repositioning Policies for Robotic Multi-Agent Systems
    Item type: Journal Article
    Ruch, Claudio; Gächter, Joel; Hakenberg, Jan; et al. (2020)
    IEEE Transactions on Network Science and Engineering
    Robotic multi-agent systems can efficiently handle spatially distributed tasks in dynamic environments. Problem instances of particular interest, and generality are the dynamic traveling repairman problem, and the dynamic vehicle routing problem. Operational policies for robotic fleets solving these two problems take decisions in an online setting with continuously arriving demands to optimize service level, and efficiency, and can be classified along several lines. First, some require a model of the demand, e.g., based on historical information, while others work model-free. Second, they are designed for different operating conditions from light to heavy system load. Third, they work in a time-invariant or time-varying setting. We present a novel class of model-free operational policies for time-varying demands, which have performance independent of the load factor, a combination of properties not achieved by other operational policies in the literature. The underlying principle of the introduced policies is to send available robots to recent service request locations. In simple terms, they rely on sending more than one robot for every service request arriving to the system. This leads to an advantage in scenarios where demand is non-uniformly distributed, and correlated in space, and time. We provide performance guarantees for both the time-invariant, and the time-varying cases as well as for correlated demand. We verify our theoretical results numerically. Finally, we apply our operational policy to the problem of mobility-on-demand fleet operation, and demonstrate that it outperforms model-based, and complex algorithms across all load ranges, despite its simplicity. © 2020 IEEE.
  • Rigid Network Design Via Submodular Set Function Optimization
    Item type: Journal Article
    Shames, Iman; Summers, Tyler (2015)
    IEEE Transactions on Network Science and Engineering
  • Resilience enhancement of urban roadway network during disruption via perimeter control
    Item type: Journal Article
    Zhu, Chunli; Wen, Guanghui; Li, Nan; et al. (2024)
    IEEE Transactions on Network Science and Engineering
    Frequent happened extreme weather events (EWEs) cause severe disruptions to the operation of large-scale urban road network. Perimeter control is of high application potential in the target scenarios. However, few studies are concerned about the lacking knowledge of the system's response features under EWE. In this work, we proposed a network resilience curve (NRC)-based perimeter control strategy to facilitate the network equilibrium, therefore enhancing the network resilience. The proposed NRC is an extension of the classical macroscopic fundamental diagram (MFD) under disruptions. A real-world trajectory dataset under normal and rainstorm day has been analyzed comparatively by using the present NRC, in which average velocity immediately reduces while average flow reveals the hysteresis effect. We compared the strategies of fixed plan, NRC-based proportional-integral (PI) control without or with connected vehicles, and min-max model predictive control. Case studies show that the proposed NRC-based PI controller improves the average weighted speed by 11.03% over fixed time strategy and recovered 7.14% ahead of the other strategies. Results demonstrate the feasibility and stability of the proposed strategy, which contributes to exploit the reasonable regulatory mechanism of EWE type disruptions.
  • The Value of Coordination in One-Way Mobility-on-Demand Systems
    Item type: Journal Article
    Ruch, Claudio; Richards, Spencer; Frazzoli, Emilio (2020)
    IEEE Transactions on Network Science and Engineering
    In a one-way mobility-on-demand system or distributed transportation system, customer requests for rides are served by a fleet of agents, e.g., taxis or even autonomous vehicles. We present a simplified three-node network model of such a transportation system in an urban agglomeration. The agents in this model play a non-cooperative game as each one tries to maximize their individual expected profit. We compute Nash equilibria in this game for different customer load cases, specifically the light- and heavy-load cases, and compare the social cost of a system with selfish agents to that of a system with coordinated agents. In particular, we establish a lower bound for the price of anarchy as a function of the system parameters, including taxi fares. We investigate the required mechanism design in the form of the fare ratio for a downtown core node and a city outskirts node that minimizes the social cost caused by selfish agents. Furthermore, we show that this optimal fare ratio is required to bring the social cost for the selfish agents as close as possible to that of the coordinated fleet. The chosen level of abstraction for the network with only three nodes is not intended to accomplish completeness; rather, it provides elementary insights into why mobility-on-demand systems with selfish agents in many cities operate at a sub-optimal level of performance. This paper motivates the investigation of the value of coordination in more complex systems, as well as the study and implementation of coordinated one-way mobility-on-demand transportation systems.
  • Incentive Design in Peer Review: Rating and Repeated Endogenous Matching
    Item type: Journal Article
    Xiao, Yuanzhang; Dörfler, Florian; van der Schaar, Mihaela (2019)
    IEEE Transactions on Network Science and Engineering
  • Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions
    Item type: Journal Article
    Zardini, Gioele; Lanzetti, Nicolas; Censi, Andrea; et al. (2023)
    IEEE Transactions on Network Science and Engineering
    The design of future mobility solutions and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management policies. This requires tools to study such a coupling and co-design mobility systems in terms of different objectives. We present a framework to address such co-design problems, leveraging a mathematical theory of co-design to frame and solve the problem of designing and deploying an intermodal mobility system, whereby autonomous vehicles service travel demands jointly with micromobility solutions and public transit, in terms of fleets sizing, vehicle characteristics, and public transit service frequency. Our framework is modular and compositional, allowing one to describe the design as the interconnection of simple components and to tackle it from a systemic perspective. Moreover, it requires general monotonicity assumptions and naturally handles multiple objectives, delivering rational, actionable solutions for policy makers. We showcase our methodology in a case study of Washington D.C., USA. Our work suggests the possibility to create user-friendly optimization tools to systematically assess costs and benefits of interventions, and to inform policy-making in the future.
Publications 1 - 6 of 6