Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain

Bareiss, 2019, Crash and injury prevention estimates for intersection driver assistance systems in left turn across path/opposite direction crashes in the United States, Traffic injury prevention, 20, S133, 10.1080/15389588.2019.1610945 Bärgman, 2020, Holistic assessment of driver assistance systems: how can systems be assessed with respect to how they impact glance behaviour and collision avoidance?, IET Intelligent Transport Systems, 14, 1058, 10.1049/iet-its.2018.5550 W. Baron C. Sippl K.S. Hielscher R. German May). Repeatable Simulation for Highly Automated Driving Development and Testing In 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) 2020. Blincoe, L., Miller, T. R., Zaloshnja, E., & Lawrence, B. A. (2015). The economic and societal impact of motor vehicle crashes, 2010 (Revised) (No. DOT HS 812 013). National Highway Traffic Safety Administration. Blower, D., & Woodrooffe, J. (2013). Real-World Safety Effect of Roll Stability Control (No. 2013-01-2392). SAE Technical Paper. https://doi.org/10.4271/2013-01-2392. Brach, 2011 Cicchino, 2017, Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates, Accident Analysis & Prevention, 99, 142, 10.1016/j.aap.2016.11.009 J. Dobberstein T. Lich D. Schmidt Accident data analysis-remaining accidents and crash configurations of automated vehicles in mixed traffic OSCCAR Project Deliverable D1 2018 1 http://osccarproject.eu/wp-content/uploads/2020/04/OSCCAR_D_1.1.pdf. Feng, 2021, Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment, Nature communications, 12, 1 Fredriksson, 2010, Priorities of pedestrian protection—A real-life study of severe injuries and car sources, Accident Analysis and Prevention, 42, 1672, 10.1016/j.aap.2010.04.006 Funk, J. R., Cormier, J. M., & Gabler, H. C. (2008). Effect of delta-V errors in NASS on frontal crash risk calculations. In Annals of Advances in Automotive Medicine/Annual Scientific Conference (Vol. 52, p. 155). Association for the Advancement of Automotive Medicine. Gennarelli, T. A., & Wodzin, E. (2008). Abbreviated injury scale 2005: update 2008. Russ Reeder, 200. Gordon, T., Sardar, H., Blower, D., Ljung Aust, M., Bareket, Z., Barnes, M., ... & Theander, H. (2010). Advanced Crash Avoidance Technologies (ACAT) Program – Final Report of the Volvo-Ford-UMTRI Project: Safety Impact Methodology for Lane Departure Warning – Method Development and Estimation of Benefits. (No. DOT HS 811 405). United States. National Highway Traffic Safety Administration. M. Gruber H. Kolk E. Tomasch F. Feist C. Klug A. Schneider A. Fredriksson June). The effect of P-AEB system parameters on the effectiveness for real world pedestrian accidents In Proceedings of International Technical Conference on the Enhanced Safety of Vehicles (ESV) 2019. Hamdane, 2015, Issues and challenges for pedestrian active safety systems based on real world accidents, Accident Analysis & Prevention, 82, 53, 10.1016/j.aap.2015.05.014 Haus, S. H., & Gabler, H. C. (2019). The Potential for Active Safety Mitigation of US Vehicle-Bicycle Crashes. In Proceedings of the Future Active Safety Technology Towards Zero Traffic Accidents (FAST-Zero). Presented at the FAST-Zero, Blacksburg, VA. Haus, 2019, Estimated benefit of automated emergency braking systems for vehicle–pedestrian crashes in the United States, Traffic injury prevention, 20, S171, 10.1080/15389588.2019.1602729 Isaksson-Hellman, I., & Lindman, M. (2015). Real-world performance of city safety based on Swedish insurance data. In Proceedings of the 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV) in Göteburg, Schweden. ISO/TR 21974–1:2018 Naturalistic driving studies – Vocabulary – Part 1.. J.S. Jermakian D.S. Zuby Primary pedestrian crash scenarios: factors relevant to the design of pedestrian detection systems 2011 Insurance Institute for Highway Safety Arlington, VA https://www.iihs.org/topics/bibliography/ref/1888. Johansson, 2009, Vision Zero-Implementing a policy for traffic safety, Safety Science, 47, 826, 10.1016/j.ssci.2008.10.023 Kalra, N., & Paddock, S. M. (2016). Driving to Safety: How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?, RAND Corporation, Santa Monica, Calif. RR-1478-RC, 2016. As of February 02, 2021: https://www.rand.org/pubs/research_reports/RR1478.html. Koopman, 2016, Challenges in autonomous vehicle testing and validation, SAE International Journal of Transportation Safety, 4, 15, 10.4271/2016-01-0128 H. Kudlich Beitrag zur Mechanik des Kraftfahrzeug-Verkehrsunfalls. Technische Hochschule Wien 1966. Kusano, 2015, Comparison of expected crash and injury reduction from production forward collision and lane departure warning systems, Traffic injury prevention, 16, S109, 10.1080/15389588.2015.1063619 K.D. Kusano H.C. Gabler October). Real-world driver crash avoidance maneuvers in rear-end collisions using event data recorders In Proceedings of the Road Safety and Simulation International Conference in Rome 2013. Kusano, 2012, Safety benefits of forward collision warning, brake assist, and autonomous braking systems in rear-end collisions, IEEE Transactions on Intelligent Transportation Systems, 13, 1546, 10.1109/TITS.2012.2191542 M. Lindman I. Isaksson-Hellman J. Strandroth September). Basic numbers needed to understand the traffic safety effect of automated cars In Proceedings of the IRCOBI Conference 2017. Prospective Effectiveness Assessment for Road Safety. Accessed 20 January, 2020, from https://pearsinitiative.com/. PEGASUS (n.d.). PEGASUS Research Project. Accessed 20 January, 2020, from https://www.pegasusprojekt.de/en/about-PEGASUS. Menzel, T., Bagschik, G., & Maurer, M. (2018, June). Scenarios for development, test and validation of automated vehicles. In 2018 IEEE Intelligent Vehicles Symposium (IV) (pp. 1821-1827). Mueller, 2020, What humanlike errors do autonomous vehicles need to avoid to maximize safety?, Journal of safety research, 75, 310, 10.1016/j.jsr.2020.10.005 W.G. Najm M.P. daSilva Benefits estimation methodology for intelligent vehicle safety systems based on encounters with critical driving conflicts 2000 Real ResultsIntelligent Transportation Society of America (ITS America). Najm, 2000, Estimation of crash injury severity reduction for intelligent vehicle safety systems, SAE World Congress, 1859–1865, 10.4271/2000-01-1354 Najm, W. G., Smith, J. D., & Yanagisawa, M. (2007). Pre-crash scenario typology for crash avoidance research. (No. DOT-VNTSC-NHTSA-06-02). United States. National Highway Traffic Safety Administration. National Center for Statistics and Analysis. (2020, November). Summary of Motor Vehicle Crashes: 2018 Data. Traffic Safety Facts. (Traffic Safety Facts. No. DOT HS 812 961). National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812961.. J. Nie G. Li J. Yang X. Zhou C. Zhang X. Yu M. Wang September). A study of injury risk of bicyclist and pedestrian in traffic accidents in Changsha of China 2013 Hanover, Germany. Prasad, P., Dalmotas, D., & Chouinard, A. (2015). Side Impact Regulatory Trends, Crash Environment and Injury Risk in the USA. Stapp Car Crash Journal, 59. Radja, G. A., Noh, E. Y., & Zhang, F. (2019). Crash Investigation Sampling System 2017 Analytical User’s Manual. (No. DOT HS 812 803). National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812803. Riedmaier, 2020, Survey on Scenario-Based Safety Assessment of Automated Vehicles, IEEE Access, 8, 87456, 10.1109/ACCESS.2020.2993730 Riexinger, L., Sherony, R., & Gabler, H. (2019). Has Electronic Stability Control Reduced Rollover Crashes? (No. 2019-01-1022). SAE Technical Paper. https://doi.org/10.4271/2019-01-1022. Rosén, 2010, Pedestrian injury mitigation by autonomous braking, Accident Analysis & Prevention, 42, 1949, 10.1016/j.aap.2010.05.018 Rosén, E., (2013). Autonomous Emergency Braking for Vulnerable Road Users. (2013, September) In Proceedings of the IRCOBI Conference. SAE J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. (2018). https://doi.org/https://doi.org/10.4271/J3016_201806. Sander, 2018, Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents, Accident Analysis & Prevention, 115, 178, 10.1016/j.aap.2018.03.025 J.M. Scanlon Evaluating the Potential of an Intersection Driver Assistance System to Prevent US Intersection Crashes (Doctoral dissertation 2017 Virginia Tech). Scanlon, 2015, Analysis of driver evasive maneuvering prior to intersection crashes using event data recorders, Traffic injury prevention, 16, S182, 10.1080/15389588.2015.1066500 Scanlon, J. M., Kusano, K. D., & Gabler, H. C. (2016). The influence of roadway characteristics on potential safety benefits of lane departure warning and prevention systems in the US vehicle fleet. In Transportation Research Board 95th Annual Meeting (No. 16-1893). Scanlon, 2017, Injury mitigation estimates for an intersection driver assistance system in straight crossing path crashes in the United States, Traffic injury prevention, 18, S9, 10.1080/15389588.2017.1300257 Singh, S. (2015). Critical reasons for crashes investigated in the national motor vehicle crash causation survey. (No. DOT HS 812 115). National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115. Schwall, M., Daniel, T., Victor, T., Favaro, F., & Hohnhold, H. (2020). Waymo Public Road Safety Performance Data. arXiv preprint arXiv:2011.00038. https://arxiv.org/abs/2011.00038. Tingvall, C., & Haworth, N. (1999, September). Vision Zero-An ethical approach to safety and mobility. In 6th ITE International Conference Road Safety & Traffic Enforcement: Beyond 2000. Tominaga, S., & Sakurai, M. (2002). Fundamental Analysis of Motorcyclist Injury Risk Using A Statistical Model Based on Real-world Crashes (No. 2002-32-1830). SAE Technical Paper. Van Auken, R. M., Zellner, J. W., Chiang, D. P., Kelly, J., Silberling, J. Y., Dai, R., ... & Sugimoto, Y. (2011). Advanced Crash Avoidance Technologies (ACAT) Program – Final Report of the Honda-DRI Team, Volume I: Executive Summary and Technical Report. (DOT HS 811 454A). National Highway Traffic Safety Administration. Viano, D. C., & Parenteau, C. S. (2008). Serious injury in very-low and very-high speed rear impacts (No. 2008-01-1485). SAE Technical Paper. Webb, N., Smith, D., Ludwick, C., Victor, T., Hommes, Q., Favaro, F., ... & Daniel, T. (2020). Waymo's Safety Methodologies and Safety Readiness Determinations. arXiv preprint arXiv:2011.00054. https://arxiv.org/abs/2011.00054. World Health Organization. (2018). Global status report on road safety 2018: Summary (No. WHO/NMH/NVI/18.20). World Health Organization. https://www.who.int/publications/i/item/9789241565684. Yanagisawa, M., Swanson, E., Azeredo, P., & Najm, W. (2017). Estimation of potential safety benefits for pedestrian crash avoidance/mitigation systems. (No. DOT-VNTSC-NHTSA-15-XX). United States. National Highway Traffic Safety Administration. Zhao, 2017, Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques, IEEE transactions on intelligent transportation systems, 18, 595, 10.1109/TITS.2016.2582208