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Chenyi Chen
Researcher at Princeton University
Publications - 12
Citations - 3053
Chenyi Chen is an academic researcher from Princeton University. The author has contributed to research in topics: Traffic flow & Affordance. The author has an hindex of 9, co-authored 12 publications receiving 2501 citations. Previous affiliations of Chenyi Chen include Tsinghua University & Nvidia.
Papers
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Proceedings ArticleDOI
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
TL;DR: This paper proposes to map an input image to a small number of key perception indicators that directly relate to the affordance of a road/traffic state for driving and argues that the direct perception representation provides the right level of abstraction.
Posted Content
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
TL;DR: In this paper, the authors propose a direct perception approach to estimate the affordance for driving in a video game and train a deep Convolutional Neural Network using recording from 12 hours of human driving.
Book ChapterDOI
R-CNN for Small Object Detection
TL;DR: This paper combines the state-of-the-art R-CNN algorithm with a context model and a small region proposal generator to improve the small object detection performance and conducts extensive experimental validations for studying various design choices.
Journal ArticleDOI
The retrieval of intra-day trend and its influence on traffic prediction
TL;DR: It is shown that the Probabilistic Principal Component Analysis (PPCA) method, which also utilizes the intra-day trend of traffic flow series, can be a useful tool in imputing the missing data and can simultaneously ensure that the prediction error remains at an acceptable level.
Proceedings ArticleDOI
Short-time traffic flow prediction with ARIMA-GARCH model
TL;DR: The results show that the introduction of conditional heteroscedasticity cannot bring satisfactory improvement to prediction accuracy, in some cases the general GARCH(1,1) model may even deteriorate the performance.