Reference health

Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model

https://doi.org/10.1177/1729881420911232
CiteStamped reference-health badge
11/11 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 11 checked references that resolve
resolves10.1109/TII.2018.2822828
Object Classification Using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment
resolves10.1016/j.trc.2016.11.009
Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system
resolves10.1016/j.apergo.2013.01.006
Effectiveness and driver acceptance of a semi-autonomous forward obstacle collision avoidance system
resolves10.1016/j.physa.2017.01.076
Analysis of vehicle’s safety envelope under car-following model
resolves10.1109/TVT.2015.2498949
Longitudinal Collision Avoidance Control of Electric Vehicles Based on a New Safety Distance Model and Constrained-Regenerative-Braking-Strength-Continuity Braking Force Distribution Strategy
resolves10.1007/s00221-017-5008-2
Action ability modulates time-to-collision judgments
resolves10.1049/el.2017.4074
Modified turn algorithm based ground vehicle collision avoidance
resolves10.1109/TVT.2019.2907696
MME-EKF-Based Path-Tracking Control of Autonomous Vehicles Considering Input Saturation
resolves10.1049/iet-its.2018.5351
Hardware and software architecture of intelligent vehicles and road verification in typical traffic scenarios
resolves10.1016/j.eng.2018.07.015
A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain
resolves10.1177/1729881418817162
Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making
The 16 references without a DOI — listed, not checked
no DOI — not checkedbibr4-1729881420911232
no DOI — not checkedInternational Conference on Image, Vision and Computing
no DOI — not checkedbibr8-1729881420911232
no DOI — not checkedIntelligent Vehicles Symposium
no DOI — not checkedIEEE International Conference on Cybernetics
no DOI — not checkedInternational Conference on Control, Automation, Robotics and Vision
no DOI — not checkedProceedings of 1985 IEEE International Conference on Robotics and Automation
no DOI — not checkedRSI International Conference on Robotics and Mechatronics
no DOI — not checkedLongitudinal driver model and collision warning and avoidance algorithms based on human driving databases
no DOI — not checkedbibr16-1729881420911232
no DOI — not checkedbibr17-1729881420911232
no DOI — not checked2017 2nd International Conference on Test, Measurement and Computational Method
no DOI — not checkedbibr20-1729881420911232
no DOI — not checkedInternational Conference on Automatic Control and Artificial Intelligence
no DOI — not checkedIEEE/RSJ International Conference on Intelligent Robots and Systems
no DOI — not checkedbibr26-1729881420911232
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

checked 2026-07-23 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record

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