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Publications: 2021

  • Brynskog, E., Iraeus, J., Reed, M. P., & Davidsson, J. (2021). Predicting pelvis geometry using a morphometric model with overall anthropometric variables. Journal of Biomechanics, 126. https://doi.org/10.1016/j.jbiomech.2021.110633
  • Cantilina, K., Daly, S. R., Reed, M. P., & Hampshire, R. C. (2021). Approaches and Barriers to Addressing Equity in Transportation: Experiences of Transportation Practitioners: Https://Doi.Org/10.1177/03611981211014533, 2675(10), 972–985. https://doi.org/10.1177/03611981211014533
  • Cao, Y., Zhou, F., Pulver, E. M., Molnar, L. J., Robert, L. P., Tilbury, D. M., & Yang, X. J. (2021). Towards standardized metrics for measuring takeover performance in conditionally automated driving: A systematic review: Https://Doi.Org/10.1177/1071181321651213, 65(1), 1065–1069. https://doi.org/10.1177/1071181321651213
  • Cao, Z., Yang, D., Xu, S., Peng, H., Li, B., Feng, S., & Zhao, D. (2021). Highway Exiting Planner for Automated Vehicles Using Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 22(2), 990–1000. https://doi.org/10.1109/TITS.2019.2961739
  • Di, X., Shi, R., DiGuiseppi, C., Eby, D. W., Hill, L. L., Mielenz, T. J., Molnar, L. J., Strogatz, D., Andrews, H. F., Goldberg, T. E., Lang, B. H., Kim, M., & Li, G. (2021). Using Naturalistic Driving Data to Predict Mild Cognitive Impairment and Dementia: Preliminary Findings from the Longitudinal Research on Aging Drivers (LongROAD) Study. Geriatrics (Basel, Switzerland), 6(2). https://doi.org/10.3390/geriatrics6020045
  • Fabusuyi, T., & Johnson, M. P. (2021). Enhancing the quality and social impacts of urban planning through community-engaged operations research: Https://Doi.Org/10.1177/23998083211054851, 49(4), 1167–1183. https://doi.org/10.1177/23998083211054851
  • Feng, S., Feng, Y., Sun, H., Bao, S., Zhang, Y., & Liu, H. X. (2021). Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies. IEEE Transactions on Intelligent Transportation Systems, 22(9), 5635–5647. https://doi.org/10.1109/TITS.2020.2988309
  • Feng, S., Feng, Y., Yu, C., Zhang, Y., & Liu, H. X. (2021). Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology. IEEE Transactions on Intelligent Transportation Systems, 22(3), 1573–1582. https://doi.org/10.1109/TITS.2020.2972211
  • Feng, S., Song, Z., Li, Z., Zhang, Y., & Li, L. (2021). Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control. IEEE Transactions on Intelligent Vehicles, 6(4), 711–722. https://doi.org/10.1109/TIV.2021.3060626
  • Feng, S., Yan, X., Sun, H., Feng, Y., & Liu, H. X. (2021). Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment. Nature Communications 2021 12:1, 12(1), 1–14. https://doi.org/10.1038/s41467-021-21007-8
  • Jones, M. L. H., Ebert, S. M., Varban, O., Hu, J., Reed, M. P., Weerappuli, P., Sundarajan, S., & Barbat, S. (2021). Effect of Class I-III obesity on driver seat belt fit. Traffic Injury Prevention, 22(7), 547–552. https://doi.org/10.1080/15389588.2021.1945590
  • Kannoth, S., Mielenz, T. J., Eby, D. W., Molnar, L. J., Jia, H., Li, G., & Strogatz, D. (2021). Adapted Stopping Elderly Accidents, Deaths, and Injuries Questions for Falls Risk Screening: Predictive Ability in Older Drivers. American Journal of Preventive Medicine, 61(1), 105–114. https://doi.org/10.1016/j.amepre.2021.02.013
  • Klinich, K. D., Leslie, A., Hariya, S., Flannagan, C. A. C., Reed, M. P., & Hallman, J. (2021). U.S. vehicle occupancy trends relevant to future automated vehicles and mobility services. Traffic Injury Prevention, 22, S116–S121. https://doi.org/10.1080/15389588.2021.1964491
  • Klinich, K. D., Manary, M. A., Boyle, K. J., & Orton, N. R. (2021). Dynamic metrics to differentiate booster performance. Traffic Injury Prevention, 22(7), 530–535. https://doi.org/10.1080/15389588.2021.1941910
  • Koh, S. W., & Hu, J. (2021). Occupant kinematics in a high-speed vehicle-to-vehicle rear-end collision. International Journal of Vehicle Safety, 12(2), 166–176. https://doi.org/10.1504/IJVS.2021.121453
  • Koh, S. W., & Hu, J. (2021). Physical Evidence of Airbag Performance in a High-Speed Frontal Crash. International Journal of Automotive Technology 2021 22:4, 22(4), 1109–1118. https://doi.org/10.1007/S12239-021-0099-Y
  • Larsson, K.-J., Pipkorn, B., Iraeus, J., Forman, J., & Hu, J. (2021). Evaluation of a diverse population of morphed human body models for prediction of vehicle occupant crash kinematics. Computer Methods in Biomechanics and Biomedical Engineering, 1–31. https://doi.org/10.1080/10255842.2021.2003790
  • Le, V. C., Jones, M. L. H., & Sienko, K. H. (2021). Post-drive standing balance of vehicle passengers using wearable sensors: The effect of on-road driving and task performance. Sensors, 21(15). https://doi.org/10.3390/s21154997
  • Lee, B., Park, B.-K. (Daniel), Jung, K., & Park, J. (2021). Effects of a Bolster Curvature on an Automobile Seat Fit: Https://Doi.Org/10.1177/1071181321651180, 65(1), 423–426. https://doi.org/10.1177/1071181321651180
  • Leslie, A. J., Kiefer, R. J., Meitzner, M. R., & Flannagan, C. A. (2021). Field effectiveness of general motors advanced driver assistance and headlighting systems. Accident Analysis and Prevention, 159. https://doi.org/10.1016/j.aap.2021.106275
  • Li, G., Ouyang, D., Yuan, Y., Li, W., Guo, Z., Qu, X., & Green, P. (2022). An EEG data processing approach for emotion recognition. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2022.3168572
  • Li, G., Yang, L., Li, S., Luo, X., Qu, X., & Green, P. (2021). Human-Like Decision Making of Artificial Drivers in Intelligent Transportation Systems: An End-to-End Driving Behavior Prediction Approach. IEEE Intelligent Transportation Systems Magazine. https://doi.org/10.1109/MITS.2021.3085986
  • Lynch, L., Mielenz, T. J., Li, G., Eby, D. W., Molnar, L. J., Betz, M. E., DiGuiseppi, C., Hill, L. L., Jones, V., & Strogatz, D. (2021). Rate of Social Isolation by Geographic Location Among Older Adults: AAA LongROAD Study. Frontiers in Public Health, 9. https://doi.org/10.3389/fpubh.2021.791683
  • Mielenz, T. J., Whalen, A. M., Xue, Q. L., Andrews, H., Molnar, L. J., Eby, D. W., & Li, G. (2022). Associations of Self-Care Health Behaviors With Driving Cessation Among Older Drivers. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.794639
  • Molnar, L. J., W., E. D., Zakrajsek, J. S., Kostyniuk, L. P., Zanier, N., LeBlanc, D. J., Nriagu, E., & Sayer, T. (2021). Guidelines for Development of Evidence-Based Countermeasures for Risky Driving – Final Technical Report, Volume 1.
  • Molnar, L. J., W., E. D., Zakrajsek, J. S., Kostyniuk, L. P., Zanier, N., LeBlanc, D. J., Nriagu, E., & Sayer, T. (2021). Guidelines for Development of Evidence-Based Countermeasures for Risky Driving – Final Technical Report, Volume 2.
  • Park, B. K. D., Corner, B. D., Hudson, J. A., Whitestone, J., Mullenger, C. R., & Reed, M. P. (2021). A three-dimensional parametric adult head model with representation of scalp shape variability under hair. Applied Ergonomics, 90. https://doi.org/10.1016/j.apergo.2020.103239
  • Pei, H., Zhang, Y., Tao, Q., Feng, S., & Li, L. (2021). Distributed cooperative driving in multi-intersection road networks. IEEE Transactions on Vehicular Technology, 70(6), 5390–5403. https://doi.org/10.1109/TVT.2021.3079272
  • Pei, H., Zhang, Y., Zhang, Y., & Feng, S. (2021). Optimal Cooperative Driving at Signal-Free Intersections With Polynomial-Time Complexity. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2021.3118592
  • Peterson, C. M., & Gaugler, J. E. (2021). To speed or not to speed: Thematic analysis of American driving narratives. Journal of Safety Research, 78, 129–137. https://doi.org/10.1016/j.jsr.2021.04.005
  • Peterson, C. M., Gaugler, J. E., Nelson, T. F., & Pereira, M. A. (2021). “Slowed for several months”: A mixed methods comparison of minor, moderate, and extreme speeders. Transportation Research Interdisciplinary Perspectives, 12, 100511. https://doi.org/10.1016/J.TRIP.2021.100511
  • Peterson, C. M., Nelson, T. F., & Pereira, M. A. (2021). Driver speeding typologies by roadway behaviours and beliefs: A latent class analysis with a multistate sample of U.S. adults. Transportation Research Part F: Traffic Psychology and Behaviour, 81, 373–383. https://doi.org/10.1016/J.TRF.2021.06.016
  • Rupp, J. D., Zaseck, L., Miller, C. S., Bonifas, A. C., Reed, M. P., Sherman, D., Cavanaugh, J. M., Ott, K., & Demetropolous, C. K. (2021). Whole Body PMHS Response in Injurious Experimental Accelerative Loading Events. Annals of Biomedical Engineering, 49(11), 3031–3045. https://doi.org/10.1007/S10439-021-02803-1
  • Schindler, R., Flannagan, C., Bálint, A., & Bianchi Piccinini, G. (2021). Making a few talk for the many – Modeling driver behavior using synthetic populations generated from experimental data. Accident; Analysis and Prevention, 162, 106331. https://doi.org/10.1016/j.aap.2021.106331
  • Shen, S., Bao, S., & Zhu, M. (2021). Validating the representativeness assumption of the quasi-induced exposure method using a national representative field observation survey. Traffic Injury Prevention, 22(2), 133–138. https://doi.org/10.1080/15389588.2020.1869223
  • Sun, H., Feng, S., Yan, X., & Liu, H. X. (2021). Corner Case Generation and Analysis for Safety Assessment of Autonomous Vehicles: Https://Doi.Org/10.1177/03611981211018697, 2675(11), 587–600. https://doi.org/10.1177/03611981211018697
  • Sun, W., Aguirre, M., Jin, J. (Judy), Feng, F., Rajab, S., Saigusa, S., Dsa, J., & Bao, S. (2021). Online distraction detection for naturalistic driving dataset using kinematic motion models and a multiple model algorithm. Transportation Research Part C: Emerging Technologies, 130, 103317. https://doi.org/10.1016/J.TRC.2021.103317
  • Sun, W., Plumlee, M., Hu, J., & Jin, and J. (Judy). (2021). Robust System Design with Limited Experimental Data and an Inexact Simulation Model. Https://Doi.Org/10.1137/20M1316287, 9(2). https://doi.org/10.1137/20M1316287
  • Vivoda, J. M., Molnar, L. J., Eby, D. W., Bogard, S., Zakrajsek, J. S., Kostyniuk, L. P., St. Louis, R. M., Zanier, N., LeBlanc, D., Smith, J., Yung, R., Nyquist, L., DiGuiseppi, C., Li, G., & Strogatz, D. (2021). The Influence of Hearing Impairment on Driving Avoidance Among a Large Cohort of Older Drivers. Journal of Applied Gerontology, 40(12), 1768–1777. https://doi.org/10.1177/0733464821999223
  • Vivoda, J., Molnar, L., Eby, D., Diguiseppi, C., Jones, V., Li, G., Mielenz, T., Strogatz, D., Dickerson, A., Leonardo, J., Cuevas, H., Zuñiga, J., & Morgan, S. (2021). Comparing Nighttime to Rush Hour Avoidance as Initial Driving Self-Regulation Behaviors. Innovation in Aging, 5(Supplement_1), 264–264. https://doi.org/10.1093/GERONI/IGAB046.1019
  • Xu, Y., Bao, S., & Pradhan, A. K. (2021). Modeling drivers’ reaction when being tailgated: A Random Forests Method. Journal of Safety Research, 78, 28–35. https://doi.org/10.1016/J.JSR.2021.05.004
  • Xue, Y., Chihuri, S., Andrews, H. F., Betz, M. E., DiGuiseppi, C., Eby, D. W., Hill, L. L., Jones, V., Mielenz, T. J., Molnar, L. J., Strogatz, D., Lang, B. H., Kelley-Baker, T., & Li, G. (2021). Potentially Inappropriate Medication Use and Hard Braking Events in Older Drivers. Geriatrics (Basel, Switzerland), 6(1), 20. https://doi.org/10.3390/geriatrics6010020
  • Yu, B., Bao, S., Chen, Y., & LeBlanc, D. J. (2021). Effects of an integrated collision warning system on risk compensation behavior: An examination under naturalistic driving conditions. Accident Analysis & Prevention, 163, 106450. https://doi.org/10.1016/J.AAP.2021.106450
  • Zhang, Y., Angell, L., & Bao, S. (2021). A fallback mechanism or a commander? A discussion about the role and skill needs of future drivers within partially automated vehicles. Transportation Research Interdisciplinary Perspectives, 9, 100337. https://doi.org/10.1016/J.TRIP.2021.100337
  • Zhu, H., Song, Z., Zhuang, W., Hofmann, H., & Feng, S. (2021). Multi-objective Optimization for Connected and Automated Vehicles Using Machine Learning and Model Predictive Control. SAE International Journal of Electrified Vehicles, 11(2). https://doi.org/10.4271/14-11-02-0014