Title：Human-Like Driving: Empirical Decision-Making System for Autonomous Vehicles

Date and Time: 15：30—17:00, July 31, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:

Autonomous vehicle, as an emerging and rapidly growing field, has received extensive attention for its futuristic driving experiences. Although the rise of depth sensor technologies and machine learning methods have given a huge boost to self-driving research, existing autonomous driving vehicles do meet with several avoidable accidents during their road testing. The major cause is the misunderstanding between self-driving systems and human drivers. To solve this problem, we propose a human-like driving system in the paper to give autonomous vehicles the ability to make decisions like a human. In our method, a Convolutional Neural Network (CNN) model is used to detect, recognize and abstract the information in the input road scene, which is captured by the on-board sensors. And then a decision-making system calculates the specific commands to control the vehicles based on the abstractions. The most significant advantage in our work is that the proposed method can well adapt to real-life road conditions, in which a massive number of human drivers exist. In addition, we build our perception system only on the depth information, and avoid the unstable RGB data. Simulations demonstrate that our approach is robust and efficient, and outperforms the state-of-the-art in several related tasks.

 

Biography: Mianxiong Dong received B.S., M.S. and Ph.D. in Computer Science and Engineering from The University of Aizu, Japan. He is currently an Associate Professor in the Department of Information and Electronic Engineering at the Muroran Institute of Technology, Japan. Prior to joining Muroran-IT, he was a Researcher at the National Institute of Information and Communications Technology (NICT), Japan. He was a JSPS Research Fellow with School of Computer Science and Engineering, The University of Aizu, Japan and was a visiting scholar with BBCR group at University of Waterloo, Canada supported by JSPS Excellent Young Researcher Overseas Visit Program from April 2010 to August 2011. Dr. Dong was selected as a Foreigner Research Fellow (a total of 3 recipients all over Japan) by NEC C&C Foundation in 2011. His research interests include Wireless Networks, Cloud Computing, and Cyber-physical Systems. He has received best paper awards from IEEE HPCC 2008, IEEE ICESS 2008, ICA3PP 2014, GPC 2015, IEEE DASC 2015 and IEEE VTC 2016-Fall. Dr. Dong serves as an Editor for IEEE Communications Surveys and Tutorials, IEEE Network, IEEE Wireless Communications Letters, IEEE Cloud Computing, IEEE Access, and Cyber-Physical Systems (Taylor & Francis), as well as a leading guest editor for ACM Transactions on Multimedia Computing, Communications and Applications (TOMM), IEEE Transactions on Emerging Topics in Computing (TETC), IEEE Transactions on Computational Social Systems (TCSS), Peer-to-Peer Networking and Applications (Springer) and Sensors, as well as a guest editor for Concurrency and Computation: Practice and Experience (Wiley), IEEE Access, Peer-to-Peer Networking and Applications (Springer), IEICE Transactions on Information and Systems, and International Journal of Distributed Sensor Networks. He has been serving as the Vice Chair of IEEE Communications Society Asia/Pacific Region Meetings and Conference Committee, Program Chair of IEEE SmartCity 2015 and Symposium Chair of IEEE GLOBECOM 2016, 2017. Dr. Dong was a research scientist with A3 Foresight Program (2011-2016) funded by Japan Society for the Promotion of Sciences (JSPS), NSFC of China, and NRF of Korea. He is the recipient of IEEE TCSC Early Career Award 2016.