Vulnerability Assessment and Capacity Scan of Alberta’s Provincial Highway Network

• Author / Creator

  Mahajan, Kasturi

• Extreme events can have serious consequences, ranging from economic losses to loss of life. Past natural disaster events have shown that highway networks are critical to transporting people from danger, but are also not immune to direct disruption and damage by these events. This is certainly true for the highway system in the province of Alberta, Canada, which is sparsely serviced and prone to wildfires and floods. It is critical for transportation authorities to understand which communities are likely to be susceptible during emergency events, as well as where transportation facility disruptions will have a greater impact on the overall network performance.
  In this thesis, I have developed and/or calculated several topological and network scanning measures to assess the performance of provincial highway system in northeastern Alberta under emergencies. The measures provide insights about the transportation network topology and locations of communities (within the network) with respect to their vulnerability to extreme events, as well as the network’s capabilities to respond (i.e. transport people to safety) during these events. The measures are based on vulnerability and robustness, well-accepted definitions in the literature for network performance assessment. In the context of this work, vulnerability is defined as inability of the transportation network to perform its intended function during emergencies. The function of transportation network during emergencies is transporting individuals to a safe location where basic and emergency services may be available. The measures based on vulnerability identify susceptible communities based on their location in the network (connectivity) such that they may be distant from all services in the province. Robustness is defined as defined as the ability of the transportation system to maintain capacity and connectivity in face of threats. The measures based on robustness determine system’s connectivity and reduction in capacity for multiple link removal.
  I constructed a representation of the network and communities, as well as a grid-based network scanning method to implement the proposed measures. The results of the vulnerability measures indicate that communities in the Regional Municipality of Wood Buffalo are highly susceptible to network disruptions and natural disasters, given that relatively significant populations are located quite far from designated emergency service centers, and served by a very limited transportation network. The measures also suggest that some communities may have difficulty evacuating during an emergency because of a high ratio of population versus immediate exits. The results can provide guidance on where (along the network) placement of interim emergency supplies may be beneficial, as well as identify key aerodromes/airstrips that are well-located to provide alternate transport means during network disruptions.
  The results of robustness measures identify sections of provincial highways that, if disrupted, will result in significant capacity reductions for larger population evacuating to Edmonton (the key service center when evacuating from northeastern Alberta). The capacity scanning measure also identifies isolating links in the study area – network facilities that, if disrupted, isolate entire communities.
  The findings of this work can be useful to provincial emergency planners in strategically placing emergency services and alternate transport modes for multi-modal evacuations. The proposed measures assess the performance of the transportation network under emergencies i.e. identify communities and highways susceptible to emergency events and disruptions, and hence may be useful in considering locations for future infrastructure investments.

• Subjects / Keywords

  • Highway capacity scanning
  • Emergency planning
  • Transportation network vulnerability

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3ST7FC83

• License

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