104 citations · 157 across the 7 of their papers we have counts for
4 papers · 1 filter
Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches
Wenshuo Wang, Junqiang Xi, Ding Zhao
Analysis and recognition of driving styles are profoundly important to intelligent transportation and vehicle calibration. This paper presents a novel driving style analysis framew…
TrafficNet: An Open Naturalistic Driving Scenario Library
Ding Zhao, Yaohui Guo, Yunhan Jack Jia
The enormous efforts spent on collecting naturalistic driving data in the recent years has resulted in an expansion of publicly available traffic datasets, which has the potential…
From the Lab to the Street: Solving the Challenge of Accelerating Automated Vehicle Testing
Ding Zhao, Huei Peng
As automated vehicles and their technology become more advanced and technically sophisticated, evaluation procedures that can measure the safety and reliability of these new driver…
How Much Data is Enough? A Statistical Approach with Case Study on Longitudinal Driving Behavior
Wenshuo Wang, Chang Liu, Ding Zhao
Big data has shown its uniquely powerful ability to reveal, model, and understand driver behaviors. The amount of data affects the experiment cost and conclusions in the analysis.…