Sarah V. Hernandez
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Associate Professor
Also affiliated: University of California, Irvine (2013–2015); Korea Transport Institute (2009); University of Florida (2009)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Sarah V. Hernandez's research focuses on the analysis and monitoring of freight transportation systems, with a particular emphasis on truck activity and classification. She has investigated methods for classifying truck body types using various sensor technologies, including weigh-in-motion (WIM) data, inductive signatures, and single-beam lidar sensors. Her work also explores the integration of different data sources to improve the accuracy and comprehensiveness of transportation analysis.
Hernandez has studied the effects of weather events on freight truck traffic using spatial panel regression models and has examined methods for assessing truck parking facility utilization by comparing overnight counts with GPS-derived data. Her research also extends to understanding representative truck activity patterns derived from mobile sensor data. She has received significant funding from the National Science Foundation (NSF) for projects related to passive sensors for freight planning and advanced truck detection with lidar technology. She also serves as a Co-PI on NSF grants focused on developing community-based frameworks for shared micromobility.
With a scholarly output of 82 publications and an h-index of 12, Hernandez actively collaborates with researchers at the University of Arkansas at Fayetteville, including Suman Mitra, Manzi Yves, Sandra D. Ekşioğlu, and Kwadwo Amankwah-Nkyi, with whom she shares multiple publications. Her work has been supported by four federal grants totaling over $1.6 million.
Metrics
- h-index: 12
- Publications: 72
- Citations: 492
Positions
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Associate Professor 2021–presentUniversity of Arkansas Fayetteville Civil Engineering ORCID
Selected Publications
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A Context-Adaptive Algorithm for Truck Stop Detection using Directional Change in Global Positioning System Trajectories (2026)
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Predicting barge tow size on inland waterways using vessel trajectory-derived features: proof of concept (2026)
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Data-driven workforce forecasting for transportation infrastructure: A comparative analysis of deep learning and statistical time series models (2026)
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Traffic Safety from Data to Action: A High School Summer Outreach Experience (2025)
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Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP) (2025)
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Highway Transportation Asset Criticality Estimation Leveraging Stakeholder Input through an Analytical Hierarchy Process (AHP) (2025)
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Highway Transportation Asset Criticality Estimation Leveraging Stakeholder Input through an Analytical Hierarchy Process (AHP) (2025)
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Prediction of waterborne freight activity with Automatic identification System using Machine learning (2024)
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Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network (2024)
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Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways (2024)
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Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning (2024)
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Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study (2024)
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Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States (2024)
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Board 37A: Driving Simulators as Educational Outreach for Freight Transportation (2024)
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Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States (2023)
Federal Grants 4 $1,614,641 total
CAREER: Towards Unbiased Long-Range Freight Planning Through Passive-Sensors and Workforce Diversity
SCC-CIVIC-PG Track A: Shared MicromobIlity for affordabLe-accessIblE houSing (SMILIES)
Collaboration Network
Top Collaborators
- Truck Body-Type Classification using Single-Beam Lidar Sensors
- GIS-based identification and visualization of multimodal freight transportation catchment areas
- Inland waterway network mapping of AIS data for freight transportation planning
- Using Data from a State Travel Demand Model to Develop a Multi-Criteria Framework for Transload Facility Location Planning
- Multicommodity port throughput from truck GPS and lock performance data fusion
Showing 5 of 10 shared publications
- A spatial panel regression model to measure the effect of weather events on freight truck traffic
- Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study
- Assessment of Crash Occurrence Using Historical Crash Data and a Random Effect Negative Binomial Model: A Case Study for a Rural State
- Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP)
- Impact of Truck Parking Facilities on Commercial and Industrial Land Values: A Spatial Hedonic Model
Showing 5 of 10 shared publications
- A spatial panel regression model to measure the effect of weather events on freight truck traffic
- Comparison of Overnight Truck Parking Counts with GPS-Derived Counts for Truck Parking Facility Utilization Analysis
- Representative truck activity patterns from anonymous mobile sensor data
- Truck Parking Usage Patterns by Facility Amenity Availability
- Truck industry classification from anonymous mobile sensor data using machine learning
Showing 5 of 8 shared publications
- Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
- Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP)
- Highway Transportation Asset Criticality Estimation Leveraging Stakeholder Input through an Analytical Hierarchy Process (AHP)
- Board 37A: Driving Simulators as Educational Outreach for Freight Transportation
Showing 5 of 6 shared publications
- A two-stage stochastic optimization model for port infrastructure planning
- Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- GIS-based identification and visualization of multimodal freight transportation catchment areas
- Inland waterway network mapping of AIS data for freight transportation planning
- A two-stage stochastic optimization model for port infrastructure planning
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- A two-stage stochastic optimization model for port infrastructure planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Truck Parking Usage Patterns by Facility Amenity Availability
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
- Impact of Truck Parking Facilities on Commercial and Industrial Land Values: A Spatial Hedonic Model
- Inland waterway network mapping of AIS data for freight transportation planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study
- Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States
- Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States
- Integration of Weigh-in-Motion (WIM) and inductive signature data for truck body classification
- Truck Activity Monitoring System for Freight Transportation Analysis
- Integration of Weigh-in-Motion (WIM) and inductive signature data for truck body classification
- Truck Activity Monitoring System for Freight Transportation Analysis
- A spatial panel regression model to measure the effect of weather events on freight truck traffic
- Assessment of Crash Occurrence Using Historical Crash Data and a Random Effect Negative Binomial Model: A Case Study for a Rural State
- Measures of Freight Network Resiliency During the Covid-19 Pandemic
- Measures of Freight Network Resiliency During the Covid-19 Pandemic
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
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