MIT advanced vehicle technology study: Large-scale naturalistic driving study of driver behavior and interaction with automation L Fridman, DE Brown, M Glazer, W Angell, S Dodd, B Jenik, J Terwilliger, ... IEEE Access 7, 102021-102038, 2019 | 204 | 2019 |
MIT autonomous vehicle technology study: Large-scale deep learning based analysis of driver behavior and interaction with automation L Fridman, DE Brown, M Glazer, W Angell, S Dodd, B Jenik, J Terwilliger, ... arXiv preprint arXiv:1711.06976 1 (9), 2017 | 120 | 2017 |
Arguing machines: Perceptioncontrol system redundancy and edge case discovery in real-world autonomous driving L Fridman, B Jenik, B Reimer arXiv preprint arXiv:1710.04459, 2017 | 65* | 2017 |
DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation L Fridman, J Terwilliger, B Jenik arXiv preprint arXiv:1801.02805, 2018 | 48 | 2018 |
Deeptraffic: Driving fast through dense traffic with deep reinforcement learning L Fridman, B Jenik, J Terwilliger arXiv preprint arXiv:1801.02805, 2018 | 30 | 2018 |
Sideeye: A generative neural network based simulator of human peripheral vision L Fridman, B Jenik, S Keshvari, B Reimer, C Zetzsche, R Rosenholtz arXiv preprint arXiv:1706.04568, 2017 | 12 | 2017 |
MIT autonomous vehicle technology study: large-scale deep learning based analysis of driver behavior and interaction with automation. CoRR 1711.06976 (2019) L Fridman, DE Brown, M Glazer, W Angell, S Dodd, B Jenik, J Terwilliger, ... arXiv preprint arXiv:1711.06976, 2017 | 9 | 2017 |
A fast foveated fully convolutional network model for human peripheral vision L Fridman, B Jenik, S Keshvari, B Riemer, C Zetzsche, R Rosenholtz Verlag nicht ermittelbar, 2017 | 3 | 2017 |