AutoMan in Media
We debut at the A2RL Autonomous Formula 1 Racing in Abu Dhabi
High speed stakes: hashtag#NTUsg and United Arab Emirates (UAE) tech firm Kintsugi made a debut at the inaugural Abu Dhabi Autonomous Racing League (A2RL) held at the iconic Yas Marina Circuit, a race track renowned in Formula 1 racing... Read more: NTU news, 联合早报
IEEE Spectrum featured our brain-inspired RL solution
A new kind of “fear-inspired” reinforcement learning technique is proving useful in making self-driving cars safer.
Chen Lv, an associate professor and director of the AutoMan Research Lab, at NTU Singapore, helped codesign the new system. He notes that over recent years, the fields of neuroscience and psychology have been digging deeper into the inner workings of the human brain, including the amygdala—the part of the brain that regulates emotions. “Fear may be the most fundamental and crucial emotion for both humans and animals in terms of survival,”... Read more
Chen received the SAE 2023 Ralph R. Teetor Award
The Ralph R. Teetor Educational Award was established by Society of Automotive Engineers (SAE), USA, in 1963. Initiated by a gift from Ralph R. Teetor, 1936 president of SAE, recipients of this award are distinguished for their contributions to engineering teaching, research, and support of student extracurricular activities as early-career educators. Past recipients include faculty members from Stanford, MIT, CMU, etc. Nanyang Asst Prof Lyu Chen is the first recipient from Singapore and South East Asia since the establishment of this award in 1963.
Prof Lyu Chen attended the SAE International Awards ceremony during SAE World Congress 2023, where he was given the Ralph Teetor Award. Read more
AutoMan won a prize in Waymo Competition 2022
Foretelling the future: #NTUsg #AI scientists led by Asst Prof Lyu Chen from the School of Mechanical and Aerospace Engineering clinched 2nd place at this year's Waymo Autonomous Vehicle Competitions, for the Occupancy and Flow Prediction Category.
Congratulations to the #NTUsg team that outperformed other top teams in their category, including those from MIT and Tsinghua University and industry players who specialise in autonomous vehicles.... Read more
AutoMan won VTS Motor Vehicle Challenge
Congratulation to MAE Team AutoMan: Ph.D. students Wu Jingda, Huang Zhiyu, under the supervision of Nanyang Asst Prof Lyu Chen from NTU School of MAE for winning second place in the 2022 IEEE VTS Motor Vehicle Challenge. During the competition, the team was tasked to co-design the sizing and energy management strategy of an intelligent electric vehicle with a hybrid dual-energy storage system, in order to extend the battery life and travel range. The team developed a novel deep learning-based predictive energy management strategy that can accurately predict future energy consumption and manage energy flow accordingly. .... Read more
News Release by NTU
A team of #NTUsg roboticists took home two awards at an autonomous driving competition organised by Waymo, the autonomous-vehicle subsidiary of Google. Using algorithms they developed, the team was able to predict where a vehicle would be eight seconds in the future with high accuracy – about 30 cm away from the actual position in real-world data.
Led by Nanyang Assistant Professor Lyu Chen, the team was the sole winner in the Interaction Prediction category, and also clinched 2nd place in the Motion Prediction category. .... read more
Coverage on Zaobao
联合早报【讯】南洋理工大学的机器人研发团队在谷歌旗下的自动驾驶汽车比赛中斩获两项大奖。助理教授吕辰和机械与航天工程博士生莫小雨、黄志宇，凭借他们的解决方案战胜美国、俄罗斯、德国和中国等团队，获得了交互预测挑战第一名、运动预测挑战的第二名...read more
Coverage on Straits Times
Roboticists from Nanyang Technological University (NTU) who developed an algorithm capable of predicting a vehicle's position eight seconds into the future clinched two awards at a competition organised by Waymo, an autonomous driving technology development firm from the United States...read more
Our work was highlighted as Cover Paper on Advanced Intelligent Systems
In article number 2000229, Chen Lv and co-workers propose a novel human-machine collaboration system based on an intelligent haptic interface for addressing the takeover control problem for automated vehicles. The intelligent haptic torque is applied to the steering wheel and switches its functionality between predictive guidance and haptic assistance according to the varying state and control ability of human drivers. This helps drivers gradually resume manual control during takeover.