Change of Scene: The Geographic Dynamics of Resilience to Vehicular Accidents

Timothy C. Matisziw (), Mark Ritchey and Robert MacKenzie
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Timothy C. Matisziw: University of Missouri
Mark Ritchey: Missouri State Highway Patrol, Statistical Analysis Center
Robert MacKenzie: Missouri State Highway Patrol, Statistical Analysis Center

Networks and Spatial Economics, 2022, vol. 22, issue 3, No 9, 587-606

Abstract: Abstract Most have experienced the impact of vehicular accidents, whether it was in terms of increased commute time, delays in receiving goods, higher insurance premiums, elevated costs of services, or simply absorbing the daily tragedies on the evening news. While accidents are common, the complexity and dynamics of transportation systems can make it challenging to infer where and when incidents may occur, a critical component in planning for where to position resources for emergency response. The use of response resources is critical given that more efficient emergency responses to accidents can decrease the vulnerability of socio-economic systems to perturbations in the transportation system and contribute to greater resilience. To explore the resilience of transportation systems to disruptions due to vehicular accidents, a location modeling approach is described for identifying the origins of optimal responses (and associated response time) over time based upon the location of known accidents and response protocols. The characteristics of the modeled response can then be compared with those of the observed response to gain insights as to how resilience may change over time for different portions of the transportation system. The change in the location of the optimal sites over time or drift, can also be assessed to better understand how changes in the spatial distribution of accidents can affect the nature of the response and system resiliency. The developed approach is applied to investigate the dynamics of accident response and network resiliency over a three year period using vehicular crash information from a comprehensive statewide database.

Keywords: Network modeling; Emergency response; Vulnerability; Infrastructure planning (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11067-020-09513-6

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