| A contextual and temporal algorithm for driver drowsiness detection AD McDonald, JD Lee, C Schwarz, TL Brown Accident Analysis & Prevention 113, 25-37, 2018 | 122 | 2018 |
| Steering in a random forest: Ensemble learning for detecting drowsiness-related lane departures AD McDonald, JD Lee, C Schwarz, TL Brown Human factors 56 (5), 986-998, 2014 | 117 | 2014 |
| Real-time detection of drowsiness related lane departures using steering wheel angle AD McDonald, C Schwarz, JD Lee, TL Brown Proceedings of the human factors and ergonomics society annual meeting 56 (1 …, 2012 | 117 | 2012 |
| The role of digital twins in connected and automated vehicles C Schwarz, Z Wang IEEE Intelligent Transportation Systems Magazine 14 (6), 41-51, 2022 | 102 | 2022 |
| The detection of drowsiness using a driver monitoring system C Schwarz, J Gaspar, T Miller, R Yousefian Traffic injury prevention 20 (sup1), S157-S161, 2019 | 71 | 2019 |
| Evaluating driver drowsiness countermeasures JG Gaspar, TL Brown, CW Schwarz, JD Lee, J Kang, JS Higgins Traffic injury prevention 18 (sup1), S58-S63, 2017 | 56 | 2017 |
| Distraction detection and mitigation through driver feedback JD Lee, J Moeckli, TL Brown, SC Roberts, C Schwarz, L Yekhshatyan, ... | 56 | 2013 |
| Creating pedestrian crash scenarios in a driving simulator environment ST Chrysler, O Ahmad, CW Schwarz Traffic injury prevention 16 (sup1), S12-S17, 2015 | 48 | 2015 |
| The effect of reliability on drivers’ trust and behavior in conditional automation C Schwarz, J Gaspar, T Brown Cognition, Technology & Work 21, 41-54, 2019 | 46 | 2019 |
| Review of automated vehicle technology: Policy and implementation implications. DV McGehee, M Brewer, C Schwarz, BW Smith Iowa. Dept. of Transportation, 2016 | 42 | 2016 |
| On computing time-to-collision for automation scenarios C Schwarz Transportation research part F: traffic psychology and behaviour 27, 283-294, 2014 | 39 | 2014 |
| NADS-Net: A nimble architecture for driver and seat belt detection via convolutional neural networks S Chun, N Hamidi Ghalehjegh, J Choi, C Schwarz, J Gaspar, D McGehee, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 37 | 2019 |
| Towards autonomous vehicles C Schwarz, G Thomas, K Nelson, M McCrary, N Sclarmann, M Powell Mid-America Transportation Center, 2013 | 34 | 2013 |
| Motion characteristics of the national advanced driving simulator C Schwarz, T Gates, Y Papelis Proceedings of the driving simulation conference, 2003 | 33 | 2003 |
| Assessing the feasibility of vehicle-based sensors to detect drowsy driving T Brown, J Lee, C Schwarz, D Fiorentino, A McDonald | 29 | 2014 |
| Steer or brake?: Modeling drivers’ collision-avoidance behavior by using perceptual cues V Venkatraman, JD Lee, CW Schwarz Transportation research record 2602 (1), 97-103, 2016 | 27 | 2016 |
| Detection of driver distraction using vision-based algorithms J Lee, J Moeckli, T Brown, S Roberts, T Victor, D Marshall, C Schwarz, ... Proc. 23rd Enhanced Safety Veh. Conf, 2013 | 27 | 2013 |
| Two mitigation strategies for motion system limits in driving and flight simulators CW Schwarz IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2007 | 25 | 2007 |
| Gaze position modulates the effectiveness of forward collision warnings for drowsy drivers JG Gaspar, CW Schwarz, TL Brown, J Kang Accident Analysis & Prevention 126, 25-30, 2019 | 23 | 2019 |
| Designing for the extremes: Modeling drivers’ response time to take back control from automation using Bayesian quantile regression A DinparastDjadid, JD Lee, J Domeyer, C Schwarz, TL Brown, ... Human factors 63 (3), 519-530, 2021 | 19 | 2021 |
Tim BrownDriving Safety Research Institute在 uiowa.edu 的电子邮件经过验证
