Mahsa Siegrist


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Siegrist

First Name

Mahsa

ORCID

0000-0003-2871-3056

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2016 - 201912020 - 20227
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Publications 1 - 8 of 8
  • Evaluating the effects of disruptions on travelers' behavior in a multimodal network utilizing agent-based simulation
    Item type: Conference Poster
    Siegrist, Mahsa; Büchel, Beda; Corman, Francesco (2022)
  • Hybrid framework of COBIT and SCOR for the assessment of IT services impact on improvement of a supply chain performance
    Item type: Conference Paper
    Amid, Amin; Siegrist, Mahsa; O'Brien, Christopher (2016)
    Nineteenth International Working Seminar on Production Economics: pre-print
  • Multi-modal management actions for public transport disruptions
    Item type: Conference Paper
    Siegrist, Mahsa; Ghandeharioun, Zahra; Kouvelas, Anastasios; et al. (2021)
    2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
    In a public transport disruption, management of the disruption plays a significant role in reducing passengers’ inconvenience. This research aims to evaluate how the delay that passengers experience in a public transport disruption can be reduced, using multi-modal management actions. We consider various traffic management actions implemented in real-time to mitigate the downsides of a disruption, including route and mode adjustments, and capacity increase. Transport operators can implement disruption management actions, such as assigning more vehicle capacity/frequency to the running services; and can inform passengers about the disruption. The benefits of providing updated information to mitigate the downsides of the disruption are large, and could possibly lead to a better mode and route choice. The simulation of the impacts and dynamics of a real-life disruption in our study is performed by an agent-based framework. We demonstrate how much delay could be avoided by implementing multi-modal management actions and analyzing the extent to which they change passengers’ travel behavior, in terms of travel mode and travel time. Results indicate that employing multi-modal management can lead to a reduction of 18% in the delay of affected passengers, when information and capacity management are used together.
  • Evaluating the effects of disruptions on the behavior of travelers in a multimodal network utilizing agent-based simulation
    Item type: Journal Article
    Siegrist, Mahsa; Büchel, Beda; Corman, Francesco (2022)
    Transportation Research Record
    Disruptions in transport networks have major adverse implications on passengers and service providers, as they can yield delays, decreased productivity, and inconvenience for travelers. Previous studies have considered the vulnerability of connections and infrastructures. Although such studies provide insights on general disruption management approaches, there is a lack of knowledge concerning integrated multi-level traffic management and its effects on travelers to reduce the impacts of disruptions. Integrated multi-level traffic management refers to coordinating individual network operations to create an interconnected mobility management system. This study sought to assess the management of road disruption utilizing multi-level disruption management. Multi-level disruption management is proposed that integrates an information dissemination strategy and allows changing the functionality of parking spaces to traffic lanes to facilitate the movement of travelers. The capacity/frequency of public transport vehicles is also increased to help travelers reach their destinations by changing to public transport mode. To achieve such goals, an extension to an agent-based simulation was developed. Numerical experiments are applied to a part of the city of Zürich. The results indicate that the proposed approach, multi-level disruption management in a multimodal network, can shorten travelers’ delays, especially comparing the effects of disruption management. Results show heterogeneity of behavior among agents. Adding lanes as a disruption management enhances the usage of car-mode by all agents, whereas it reduces the usage of car-mode by the directly affected agents, those who cannot pass the disrupted roads. In the presence of full information and increased capacity of transit vehicles, delay is reduced by 47%.
  • Future traffic control beyond modes
    Item type: Report
    Corman, Francesco; Ghandeharioun, Zahra; Kouvelas, Anastasios; et al. (2020)
  • Evaluating the effects of disruptions on travelers' behavior in a multimodal network utilizing agent-based simulation
    Item type: Other Conference Item
    Siegrist, Mahsa; Büchel, Beda; Corman, Francesco (2022)
    Disruptions in transport networks have major adverse implications on passengers and service providers, as they can yield delays, decreased productivity, and inconvenience for travelers. Previous studies have considered the vulnerability of connections and infrastructures. Although such studies provide insights on general disruption management approaches, there is a lack of knowledge concerning integrated multi-level traffic management and its effects on travelers to reduce the impacts of disruptions. Integrated multi-level traffic management refers to coordinating individual network operations to create an interconnected mobility management system. This study sought to assess the management of road disruption utilizing multi-level disruption management. Multi-level disruption management is proposed that integrates an information dissemination strategy and allows changing the functionality of parking spaces to traffic lanes to facilitate the movement of travelers. The capacity/frequency of public transport vehicles is also increased to help travelers reach their destinations by changing to public transport mode. To achieve such goals, an extension to an agent-based simulation was developed. Numerical experiments are applied to a part of the city of Zürich. The results indicate that the proposed approach, multi-level disruption management in a multimodal network, can shorten travelers’ delays, especially comparing the effects of disruption management. Results show heterogeneity of behavior among agents. Adding lanes as a disruption management enhances the usage of car-mode by all agents, whereas it reduces the usage of car-mode by the directly affected agents, those who cannot pass the disrupted roads. In the presence of full information and increased capacity of transit vehicles, delay is reduced by 47%.
  • Modeling and quantifying interaction of information and capacity in public transport disruptions
    Item type: Journal Article
    Siegrist, Mahsa; Corman, Francesco (2021)
    Journal of Advanced Transportation
    Disruption in public transport networks has adverse implications for both passengers and service managers. To evaluate the effects of disruptions on passengers’ behaviour, various methods, simulation modules, and mathematical models are widely used. However, such methods included many assumptions for the sake of simplicity. We here use multiagent microsimulation modules to simulate complex real-life scenarios. Aspects that were never explicitly modelled together are the capacity of the network and the effect of disruption to on-board passengers, who might need to alight the disrupted services. In addition, our simulation and developed module provide a framework that can be applied for both transport planning and real-time management of disruption for the large-scale network. We formalize the agent-based assignment problem in capacitated transit networks for disrupted situations, where some information is available about the disruption. We extend a microsimulation environment to quantify precisely the impact and the number of agents directly and indirectly affected by the disruption, respectively, those passengers who cannot perform their trip because of disrupted services (directly affected passengers), and those passengers whose services are not disrupted but experience additional crowding effects (indirectly affected passengers). The outcomes are discussed both from passengers’ perspective and for extracting more general planning and policy recommendations. The modeling and solution approaches are applied to the multimodal public transport system of Zürich, Switzerland. Our results show that different information dissemination strategies have a large impact on direct and indirect effects. By earlier information dissemination, the direct effects get milder but larger in space, and indirect negative effects arise. The scenarios with the least information instead are very strongly affecting few passengers, while the less negative indirect effect for the rest of the network.
  • Quantifying the heterogeneity of direct and indirect effects of a public transport disruption with agent-based simulation
    Item type: Conference Paper
    Siegrist, Mahsa; Corman, Francesco (2020)
    This paper studies and quantifies the direct and indirect effects of a disruption in the public transport network on passengers using agent-based simulation. In particular, we study the behavior of agents in the network to measure the spatial and temporal extent of the impacts (delays, disutility) of a disruption. Due to the dynamic nature of public transport systems, disruption’s impact on a particular part of the public transport network propagates through the network in both time and space dimensions. Besides, we attempt to evaluate passengers’ behavior in as realistic as possible scenarios, where information about the disruption is scarce, or the disruption is even completely unexpected, and overcome the difficulties of a real-life passenger’ behavior simulation. For such an aim, we add a new extension to the within-day replanning module in the agent-based simulation for public transport (MATSim). We apply our agent-based simulation to the case of the public transport system of Zürich, Switzerland. Our simulation approach quantifies precisely the number of directly and indirectly affected agents by the disruption, respectively those passengers who cannot carry their trip as planned because the services are disrupted and need to reroute their trip in the network; and those passengers whose services are not disrupted, but experience additional crowding effects due to the rerouted, directly affected, passengers. For both groups of travelers, we also study the delay that they experience, and the variation in their utility score of traveling. We prove how those effects relate to a large spatial and temporal heterogeneity, and moreover, they depend strongly on the information available, and replanning actions that the agents might undertake.
Publications 1 - 8 of 8