Sledovat
Wenwen Zhang
Wenwen Zhang
Associate Professor at Rutgers University
E-mailová adresa ověřena na: scarletmail.rutgers.edu - Domovská stránka
Název
Citace
Citace
Rok
Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach
W Zhang, S Guhathakurta, J Fang, G Zhang
Sustainable Cities and Society 19, 34-45, 2015
4832015
Machine learning approaches for estimating commercial building energy consumption
C Robinson, B Dilkina, J Hubbs, W Zhang, S Guhathakurta, MA Brown, ...
Applied Energy 208, 889-904, 2017
4122017
The impact of private autonomous vehicles on vehicle ownership and unoccupied VMT generation
W Zhang, S Guhathakurta, EB Khalil
Transportation Research Part C: Emerging Technologies 90, 156-165, 2018
1962018
Parking spaces in the age of shared autonomous vehicles: How much parking will we need and where?
W Zhang, S Guhathakurta
Transportation Research Record: Journal of the Transportation Research Board …, 2017
1812017
Residential location choice in the era of shared autonomous vehicles
W Zhang, S Guhathakurta
Journal of Planning Education and Research 41 (2), 135-148, 2021
972021
Firebird: Predicting fire risk and prioritizing fire inspections in atlanta
M Madaio, ST Chen, OL Haimson, W Zhang, X Cheng, M Hinds-Aldrich, ...
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016
78*2016
The performance and benefits of a shared autonomous vehicles based dynamic ridesharing system: An agent-based simulation approach
W Zhang, S Guhathakurta, J Fang, G Zhang
Transportation Research Board 94th Annual Meeting 15, 2919, 2015
782015
What type of infrastructures do e-scooter riders prefer? A route choice model
W Zhang, R Buehler, A Broaddus, T Sweeney
Transportation Research Part D: Transport and Environment 94, 102761, 2021
772021
Listen to E-scooter riders: Mining rider satisfaction factors from app store reviews
JJC Aman, J Smith-Colin, W Zhang
Transportation Research Part D: Transport and Environment 95, 102856, 2021
702021
Combining expert and crowd-sourced training data to map urban form and functions for the continental US
M Demuzere, S Hankey, G Mills, W Zhang, T Lu, B Bechtel
Scientific data 7 (1), 264, 2020
692020
Parking futures: Shared automated vehicles and parking demand reduction trajectories in Atlanta
W Zhang, K Wang
Land Use Policy 91, 103963, 2020
652020
Estimating residential energy consumption in metropolitan areas: A microsimulation approach
W Zhang, C Robinson, S Guhathakurta, VM Garikapati, B Dilkina, ...
Energy 155, 162-173, 2018
552018
Changes in travel behavior, attitudes, and preferences among e-scooter riders and nonriders: first look at results from pre and post e-scooter system launch surveys at Virginia …
R Buehler, A Broaddus, T Sweeney, W Zhang, E White, M Mollenhauer
Transportation research record 2675 (9), 335-345, 2021
372021
Predicting bicycling and walking traffic using street view imagery and destination data
S Hankey, W Zhang, HTK Le, P Hystad, P James
Transportation Research Part D: Transport and Environment 90, 102651, 2020
332020
THE INTERACTION BETWEEN LAND USE AND TRANSPORTATION IN THE ERA OF SHARED AUTONOMOUS VEHICLES: A SIMULATION MODEL
W Zhang
Georgia Institute of Technology, 2017
302017
How should urban planners be trained to handle big data?
SP French, C Barchers, W Zhang
Seeing cities through Big data: Research, methods and applications in urban …, 2017
292017
Risk priorities and their co-occurrences in smart city project implementation: Evidence from India’s Smart Cities Mission (SCM)
K Gupta, W Zhang, RP Hall
Environment and Planning B: Urban Analytics and City Science 48 (4), 880-894, 2021
192021
Synthesizing neighborhood preferences for automated vehicles
W Zhang, K Wang, S Wang, Z Jiang, A Mondschein, RB Noland
Transportation Research Part C: Emerging Technologies 120, 102774, 2020
192020
Moving beyond operations: Leveraging big data for urban planning decisions
S French, C Barchers, W Zhang
56th Annual Conference of Association of College Schools of Planning (ACSP …, 2015
192015
Land Use Regression models for 60 volatile organic compounds: Comparing Google Point of Interest (POI) and city permit data
T Lu, J Lansing, W Zhang, MJ Bechle, S Hankey
Science of The Total Environment 677, 131-141, 2019
172019
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Články 1–20