Reference health
Validation of decision-making in artificial intelligence-based autonomous vehicles
24/24 checkable references clean · checked 2026-07-23
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
16 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 24 checked references that resolve
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APAWSAN: Actor positioning for aerial wireless sensor and actor networks
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Autonomous Vehicles Scenario Testing Framework and Model of
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VerifAI: A Toolkit for the Formal Design and Analysis of Artificial Intelligence-Based Systems
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Examining accident reports involving autonomous vehicles in California
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Virtual Robot Experimentation Platform V-REP: A Versatile 3D Robot Simulator
resolves10.1109/ITSC45102.2020.9294368
Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World
resolves10.1109/ICM.2011.6177404
Performance analysis of constraint solvers for coverage directed test generation
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Street Network Generation with Adjustable Complexity Using k-Means Clustering
resolves10.4271/2018-01-1066
Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles
resolves10.1016/j.tra.2016.09.010
Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?
resolves10.1007/978-3-658-21194-3_51
Framework for interactive testing and development of highly automated driving functions
resolves10.1109/SoutheastCon42311.2019.9020575
Abstract Simulation Scenario Generation for Autonomous Vehicle Verification
resolves10.1007/978-3-030-42058-1_40
Scenario Generation for Validating Artificial Intelligence Based Autonomous Vehicles
resolves10.1109/IVS.2019.8814099
From Functional to Logical Scenarios: Detailing a Keyword-Based Scenario Description for Execution in a Simulation Environment
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Spatially Adaptive Positioning for Molecular Geometry Inspired Aerial Networks
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State of the art: hardware in the loop modeling and simulation with its applications in design, development and implementation of system and control software
The 16 references without a DOI — listed, not checked
no DOI — not checkedATG, U. (n.d.). streetscape.gl. Retrieved April 10, 2020, from https://avs.auto/#/streetscape.gl/overview/introduction.
no DOI — not checkedBehrisch, M., Bieker, L., Erdmann, J. & Krajzewicz, D. (2011). SUMO–simulation of urban mobility: an overview. In Proceedings of SIMUL 2011, the Third International Conference on Advances in System Simulation. ThinkMind.
no DOI — not checkedGoodwin, A. (2019). Nvidia Drive Constellation is an online training ground for autonomous vehicles. Retrieved from https://www.cnet.com/roadshow/news/nvidia-drive-constellation-is-an-online-training-ground-for-autonomous-vehicles/
no DOI — not checkedDolgov, D. (2016). Google self-driving car project-monthly report-September 2016-on the road (Tech. Rep.). Google.
no DOI — not checkedDupuis, M. & Karl, W. (2017). Vtd-vires virtual test drive. Retrieved from https://www.mscsoftware.com/product/virtual-test-drive.
no DOI — not checkedDupuis, M., Strobl, M. & Grezlikowski, H. (2010). OpenDRIVE 2010 and Beyond–Status and Future of the de facto Standard for the Description of Road Networks. In Proceedings of the Driving Simulation Conference Europe (pp. 231–242). INRETS, Arcueil.
no DOI — not checkedHalati, A., Lieu, H. & Walker, S. (1997). CORSIM-corridor traffic simulation model. In Traffic congestion and traffic safety in the 21st century: Challenges, innovations, and opportunities urban transportation division, asce; highway division, asce; federal highway administration, usdot; and national highway traffic safety administration, usdot.
no DOI — not checkedISO, I. (2018). 26262-1: 2018. Road vehicles–Functional safety–Part, 1.
no DOI — not checkedJansson, J., Sandin, J., Augusto, B., Fischer, M., Blissing, B. & Källgren, L. (2014). Design and performance of the VTI Sim IV. In Driving Simulation Conference (pp. 128–138). VINNOVA.
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no DOI — not checkedKoschi, M., Manzinger, S. & Althoff, M. (n.d.). CommonRoad: Documentation of the XML Format.
no DOI — not checkedThe MathWorks, Inc.MATLAB and automated driving system toolbox [Computer software manual]. (Release R2018b).
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no DOI — not checkedNair, V. G. & Wishart, J. (2018). A study of driving simulation platforms for automated vehicles. CAV Final Report, Arizona State University.
no DOI — not checkedNowakowski, C., Shladover, S. & Chan, C. (2015). Behavioral competency requirements methodology project background regulatory issues and potential regulatory strategies for highly Automated Vehicles (AVs) how to ensure safety prior to deployment? In Automated Vehicles Symposium. AVS.
no DOI — not checkedWaymo safety report: On the road to fully self-driving (2018).
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