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Publications: Connected and Automated Vehicles

  • Beak B, Head KL, Feng Y (2017) Adaptive coordination based on connected vehicle technology, Transportation Research Record. 2619:1-12. DOI:10.3141/2619-01
  • Bogard S, Bao S, LeBlanc D, Li J, Qiu S, Liu, B (2017) Performance of DSRC during safety pilot model deployment. SAE International Journal of Passenger Cars – Electronic and Electrical Systems 10(1):165-172. DOI:10.4271/2017-01-0077.
  • Eby DW, Molnar LJ, and Stanciu SC. (2018) Older Adults’ Attitudes and Opinions about Automated Vehicles: A Literature Review. Report No. ATLAS-2019-26. Ann Arbor, MI: University of Michigan Transportation Research Institute. ATLAS-center.org
  • Feng S, Feng Y, Yu C, Zhang Y, and Liu HX. (2020) Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology. IEEE Transactions on Intelligent Transportation Systems.https://arxiv.org/abs/1905.03419
  • Feng Y, Huang S, Chen QA, Liu HX, and Mao ZM. (2018) Vulnerability of traffic control system under cyber-attacks using falsified data. Transportation Research Record 2672(1):1-11. DOI: 10.1177/0361198118756885
  • Feng Y, Yu C, Liu HX (2018) Spatiotemporal intersection control in a connected and automated vehicle environment. Transportation Research Part C Emerging Technologies 89:364-383. DOI: 10.1016/j.trc.2018.02.001
  • Feng Y, Zamanipour M, Head KL, Khoshmagham S. (2016) Connected vehicle based adaptive signal control and applications. Transportation Research Record 2558:11-19. DOI: 10.3141/2558-02
  • Feng Y, Zheng J, and Liu HX. (2018) A real-time detector-free adaptive signal control with low penetration of connected vehicles. Transportation Research Record 2672(18):35-44. DOI: 10.1177/0361198118790860
  • Flannagan C, LeBlanc D, Bogard S, Nobukawa K, Narayanaswamy P, Leslie A, Kiefer R, Marchione M, Beck C, and Lobes K. (2016) Large-Scale Field Test of Forward Collision Alert and Lane Departure Warning Systems. Office of Advanced Safety Research, Washington, D.C. Report No. DOT HS 812 247. Nhtsa.gov
  • Flannagan CA, LeBlanc DJ, Kiefer RJ, Bogard SE, Leslie A, Zagorski CT, Zimmerman CW, Materna WS, and Beck CS. (2018) Field Study of Light-Vehicle Crash Avoidance Systems: Automatic Emergency Braking and Dynamic Brake Support (No. DOT HS 812 615). United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/38817
  • Huang Z, H Lam, DJ LeBlanc, D Zhao (2017) Accelerated evaluation of automated vehicles using piecewise mixture models. IEEE Transactions on Intelligent Transportation Systems 19(9): 2845-2855. DOI: 10.1109/TITS.2017.276617
  • Jones MLH, Ebert SM, Reed MP. (in press) Sensations associated with motion sickness response during passenger vehicle operations on a test track. SAE International Journal of Advances and Current Practices in Mobility. SAE Technical Paper 2019-01-0687. DOI:10.4271/2019-01-0687
  • Jones MLH, Le V, Ebert S, Sienko KH, Reed MP, and Sayer JR. (in press) Motion sickness in passenger vehicles during test track operations. Ergonomics
  • LeBlanc DJ, Flannagan CA, Blower DF, Bogard SE, Sullivan JM, Klinich KD, Bingham CR, Leslie A, Bao S, Flannagan MJ, Zhao D, Misra A, Park L, Zakrajsek J. (2017) Final Technical Report: Crash Avoidance Systems – Safety Evaluation of an Important Class of Electronic Control Systems. https://deepblue.lib.umich.edu/handle/2027.42/151377
  • Li B, Zhang Y, Feng Y, Zhang Y, Ge Y, and Shao Z. (2018) Balancing computational speed and quality: a decentralized motion planning method for cooperative lane changes of connected and automated vehicles. IEEE Transactions on Intelligent Vehicles 3(3):340-350. DOI: 10.1109/TIV.2018.2843159
  • Misra A, Leslie A, Cao A, Molnar JL, Eby DW, and Flannagan C. (2018) Identifying Potential Work Zone Countermeasures Using Connected-Vehicle and Driving Data. Lansing, MI: Michigan Department of Transportation. Michigan.gov
  • Molnar LJ, Pradhan AK, Eby DW, Ryan L, St. Louis RM, Zakrajsek J, Ross B, Lin BT, Liang C, Zalewski B, and Zhang L. (2017) Age-Related Differences in Driver Behavior Associated with Automated Vehicles and the Transfer of Control between Automated and Manual Control: A Simulator Evaluation. Report No. UMTRI-2017-4. Ann Arbor, MI: University of Michigan Transportation Research Institute. https://deepblue.lib.umich.edu/handle/2027.42/137653
  • Molnar LJ, Ryan LH, Pradhan AK, Eby DW, St. Louis RM, and Zakrajsek J. (2018) Understanding trust and acceptance of automated vehicles: An exploratory simulator study of transfer of control between automated and manual driving. Transportation Research Part F: Psychology and Behaviour, 58: 319-328. DOI: 10.1016/j.trf.2018.06.004
  • Pradhan AK, Pulver E, Zakrajsek J, Bao S. and Molnar L. (2018) Perceived safety benefits, concerns, and utility of advanced driver assistance systems among owners of ADAS-equipped vehicles. Traffic Injury Prevention 19:sup2, S135-S1371. DOI: 10.1080/15389588.2018.1532201.
  • Reed MP, Ebert SM, Jones MLH, Park B-KD, Hallman JJ, and Sherony R. (2018) Passenger head kinematics in abrupt braking and lane change events. Traffic Injury Prevention 19(sup2):S70-77. DOI: 10.1080/15389588.2018.1481957
  • Stachowski S, Gaynier R, LeBlanc DJ (2019) An assessment method for automotive intrusion detection system performance DOT HS 812 708 National Highway Traffic Safety Administration, Washington DC. https://rosap.ntl.bts.gov/view/dot/41006
  • Stanciu S, Eby DW, Molnar LJ, St. Louis RM, and Zanier, N (2017) Interpersonal Communication and Issues for Autonomous Vehicles. Report No. ATLAS-2017-20. Ann Arbor, MI: Center for Advancing Transportation Leadership and Safety. https://rosap.ntl.bts.gov/view/dot/32338
  • Stanciu S, Eby DW, Molnar LJ, St. Louis RM, Zanier N, and Kostyniuk LP. (2018) Pedestrians/bicyclists and autonomous vehicles: How will they communicate? Transportation Research Record 2672(22):58–66. DOI: 10.1177/0361198118777091
  • Tan V, Flannagan C, and Elliott M. (2018) Predicting human-driving behavior to help driverless vehicles drive: random intercept Bayesian additive regression trees. Statistics and Its Interface 11(4): 557–572. DOI: 10.4310/SII.2018.v11.n4.a1
  • Wang X, Shen S, Bezzina D, Sayer JR, Liu HX, and Feng Y. (2020) A Data Infrastructure for Connected Vehicle Applications. Transportation Research Record. DOI: 10.1177/0361198120912424
  • Yu B, Bao S, Feng F, Sayer J. (2019) Examination and prediction of drivers’ reaction when provided with V2I communication-based intersection maneuver strategies. Transportation Research Part C: Emerging Technologies, 106:17-28. DOI: 10.1016/j.trc.2019.07.007
  • Yu C, Feng Y, Liu HX, Ma W, and Yang X. (2019) Corridor level cooperative trajectory optimization with connected and automated vehicles. Transportation Research Part C: Emerging Technologies V105: 405-421. DOI: 10.1016/j.trc.2019.06.002
  • Zhao D, Huang X, Peng H, Lam H, and LeBlanc D. (2017) Accelerated evaluation of automated vehicles in car-following maneuvers. IEEE Transactions on Intelligent Transportation Systems 19. DOI: 10.1109/TITS.2017.2701846
  • Zhao D, Lam H, Peng H, Bao S, LeBlanc D, Nobukawa K, and Pan C. (2017) Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques. IEEE Transactions on Intelligent Transportation Systems 18(3):595-607. DOI: 10.1109/TITS.2016.2582208.