Pamela Murray-Tuite

Dr. Pamela Murray-Tuite


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2014 in Transportation Research Part C: Emerging Technologies
Verified
Journal Article
Closed access
WYWeihao Yin
Weihao Yin
PMPamela Murray-Tuite
Pamela Murray-Tuite
SUSatish Ukkusuri
Satish Ukkusuri
HGHugh Gladwin
Hugh Gladwin

1 August 2020 in Natural Hazards Review
Verified
Journal Article
Closed access
PDF file
SPScott Parr
Scott Parr
BWBrian Wolshon
Brian Wolshon
JRJohn Renne
John Renne
PMPamela Murray-Tuite
Pamela Murray-Tuite
Karl KimKarl Kim
Karl Kim
The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped by 47.5%. Although decreases were evident across the state, there were also differences between rural and urban areas and between highways and arterials both in terms of the timing and extent. The data and analyses help to demonstrate the early impacts of the pandemic and may be useful for operational and strategic planning of recovery efforts and for dealing with future pandemics.

19 November 2018 in IEEE Transactions on Intelligent Transportation Systems
Verified
Journal Article
Closed access
GHGaby Joe Hannoun
Gaby Joe Hannoun
PMPamela Murray-Tuite
Pamela Murray-Tuite
KHKevin Heaslip
Kevin Heaslip
TCThidapat Chantem
Thidapat Chantem
Emergency response vehicles' (ERVs) travel is risky, as non-ERV drivers are often unsure of the ERV's next maneuver and how to facilitate its movement. An integer linear program (ILP), introduced in this paper, facilitates the ERV's movement through a transportation link. Leveraging vehicle-to-vehicle communications, information is collected about vehicles on a link section. Then, the ILP finds the ERV's fastest intra-link path. To increase safety, the ILP assigns non-ERVs locations as far away from the ERV as possible while avoiding passing and weaving among vehicles. The ILP can be adapted to different ERV sizes, road types, and surrounding conditions. Sensitivity analysis indicated that scenarios with narrower road segments and higher numbers of non-ERVs led to ERV paths with lane changes and higher computation times. When compared with the current practice requiring non-ERVs to move to the nearest road edge when an ERV with lights and sirens is noticed, the proposed formulation improved the ERV speed while reducing the conflicts and confusion experienced by downstream vehicles.

1 May 2020 in Transportation Research Part D: Transport and Environment
Verified
Journal Article
Closed access
JRJohn Renne
John Renne
BWBrian Wolshon
Brian Wolshon
PMPamela Murray-Tuite
Pamela Murray-Tuite
APAnurag Pande
Anurag Pande

1 May 2014 in Transportation Research Part F: Traffic Psychology and Behaviour
Verified
Journal Article
Closed access
PMPamela Murray-Tuite
Pamela Murray-Tuite
KWKris Wernstedt
Kris Wernstedt
WYWeihao Yin
Weihao Yin

15 August 2022 in International Journal of Disaster Risk Reduction
Verified
Journal Article
Closed access
EAEmmanuel Adjei
Emmanuel Adjei
BBBailey C. Benedict
Bailey C. Benedict
PMPamela Murray-Tuite
Pamela Murray-Tuite
SLSeungyoon Lee
Seungyoon Lee
SUSatish Ukkusuri
Satish Ukkusuri
YGYue 'Gurt' Ge
Yue 'Gurt' Ge