TY - GEN
T1 - Exploring Spatial and Temporal Patterns of Large-scale Smartphone-based Dangerous Driving Event Data
AU - Yang, Di
AU - Xie, Kun
AU - Ozbay, Kaan
AU - Yang, Hong
N1 - Funding Information:
Research supported by NYU Tandon School of Engineering and Connected Cities for Smart Mobility towards Accessible and Resilient Transportation (C2SMART) Center.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Dangerous driving events data are widely used as surrogates to traffic crashes. Large-scale dangerous driving events data collected from smartphones are explored in this study. Clustering analysis is performed on dangerous driving events counted in spatial cells. Spatial and temporal patterns of the cluster distributions are then explored. Both the existence of spatial autocorrelation and the similarity of cluster distributions for different time periods are uncovered.
AB - Dangerous driving events data are widely used as surrogates to traffic crashes. Large-scale dangerous driving events data collected from smartphones are explored in this study. Clustering analysis is performed on dangerous driving events counted in spatial cells. Spatial and temporal patterns of the cluster distributions are then explored. Both the existence of spatial autocorrelation and the similarity of cluster distributions for different time periods are uncovered.
UR - http://www.scopus.com/inward/record.url?scp=85076799693&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076799693&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2019.8916875
DO - 10.1109/ITSC.2019.8916875
M3 - Conference contribution
T3 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
SP - 116
EP - 121
BT - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Y2 - 27 October 2019 through 30 October 2019
ER -