Dr. Kara Kockelman, P.E.
Dr. Kara Kockelman, P.E.
Dewitt Greer Professor of Transportation Engineering, University of Texas at Austin
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Zitiert von
Zitiert von
Travel demand and the 3Ds: Density, diversity, and design
R Cervero, K Kockelman
Transportation research part D: Transport and environment 2 (3), 199-219, 1997
Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations
DJ Fagnant, K Kockelman
Transportation Research Part A: Policy and Practice 77, 167-181, 2015
The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios
DJ Fagnant, KM Kockelman
Transportation Research Part C: Emerging Technologies 40, 1-13, 2014
Assessing public opinions of and interest in new vehicle technologies: An Austin perspective
P Bansal, KM Kockelman, A Singh
Transportation Research Part C: Emerging Technologies 67, 1-14, 2016
Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies
P Bansal, KM Kockelman
Transportation Research Part A: Policy and Practice 95, 49-63, 2017
Travel behavior as function of accessibility, land use mixing, and land use balance: evidence from San Francisco Bay Area
K Maria Kockelman
Transportation research record 1607 (1), 116-125, 1997
Driver injury severity: an application of ordered probit models
KM Kockelman, YJ Kweon
Accident Analysis & Prevention 34 (3), 313-321, 2002
Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas
DJ Fagnant, KM Kockelman
Transportation 45, 143-158, 2018
Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions
TD Chen, KM Kockelman, JP Hanna
Transportation Research Part A: Policy and Practice 94, 243-254, 2016
Operations of shared autonomous vehicle fleet for Austin, Texas, market
DJ Fagnant, KM Kockelman, P Bansal
Transportation Research Record 2563 (1), 98-106, 2015
A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods
J Ma, KM Kockelman, P Damien
Accident Analysis & Prevention 40 (3), 964-975, 2008
Locating Electric Vehicle Charging Stations: Parking-Based Assignment Method for Seattle, Washington
TD Chen, KM Kockelman, M Khan
Transportation Research Record, 28-36, 2013
Are we ready to embrace connected and self-driving vehicles? A case study of Texans
P Bansal, KM Kockelman
Transportation 45, 641-675, 2018
Economic effects of automated vehicles
LM Clements, KM Kockelman
Transportation research record 2606 (1), 106-114, 2017
Carsharing’s life-cycle impacts on energy use and greenhouse gas emissions
TD Chen, KM Kockelman
Transportation Research Part D: Transport and Environment 47, 276-284, 2016
A general framework for modeling shared autonomous vehicles with dynamic network-loading and dynamic ride-sharing application
MW Levin, KM Kockelman, SD Boyles, T Li
Computers, Environment and Urban Systems 64, 373-383, 2017
The propagation of uncertainty through travel demand models: an exploratory analysis
Y Zhao, KM Kockelman
The Annals of regional science 36, 145-163, 2002
Credit-based congestion pricing: a policy proposal and the public’s response
KM Kockelman, S Kalmanje
Transportation Research Part A: Policy and Practice 39 (7-9), 671-690, 2005
Analysis of large truck crash severity using heteroskedastic ordered probit models
JD Lemp, KM Kockelman, A Unnikrishnan
Accident Analysis & Prevention 43 (1), 370-380, 2011
Overall injury risk to different drivers: combining exposure, frequency, and severity models
YJ Kweon, KM Kockelman
Accident Analysis & Prevention 35 (4), 441-450, 2003
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