R
Ram M. Pendyala
Researcher at Arizona State University
Publications - 269
Citations - 9647
Ram M. Pendyala is an academic researcher from Arizona State University. The author has contributed to research in topics: Travel behavior & Mode choice. The author has an hindex of 53, co-authored 251 publications receiving 8344 citations. Previous affiliations of Ram M. Pendyala include Sewanee: The University of the South & Georgia Institute of Technology.
Papers
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Joint Model of Accident Type and Severity for Two-VehicleCrashes
TL;DR: Results show significant presence of error correlations, i.e., the presence of common unobserved factors that influence accident type and severity, thus supporting the jointness in modeling these two accident characteristics.
Analysis of Weekly Out-of-Home Discretionary Activity Participation and Time Use Behavior
TL;DR: In this paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity travel behavior data set collected in and around Zurich, Switzerland, with a view to understand the inter-personal and intra-personal variability in weekly activity engagement at a detailed level.
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How many trip requests could we support? An activity-travel based vehicle scheduling approach
TL;DR: Three different versions of network representation and mathematical models for the activity-based vehicle routing problem to connect activity-travel graphs of passengers (demand layer) to spatio-temporal networks of vehicles (supply layer) are proposed.
A holistic view on history, development, assessment, and future of an open courseware in numerical methods
Duc T. Nguyen,Ram M. Pendyala,Autar Kaw,Ali Yalcin,Corina M. Owens,Melinda R. Hess,Gwen Lee-Thomas,Glen H. Besterfield,James A. Eison +8 more
TL;DR: The history, philosophy, development, refinement, assessment process, and future of the open courseware are discussed and the summarized assessment results include those of comparing several instructional modalities, measuring student learning, effect of collecting homework for a grade, and interpreting summative ratings of the courseware.
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Introducing Latent Psychological Constructs in Injury Severity Modeling: Multivehicle and Multioccupant Approach:
TL;DR: In this paper, a comprehensive model of injury severity that accounts for unmeasured driver behavior attributes is presented, which has important implications for the design of safety interventions and advanced vehicular features and technologies.