175 citations as recorded by crossref.

1. A Study on the Effects of Multi-Vehicle Communication Failures and Their Data Compensation in Platooning Operation 睿. 蒙
2. Snow coverage estimation using camera data for automated driving applications N. Goberville et al.
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11. High Speed Surface Illuminated Si Photodiode Using Microstructured Holes for Absorption Enhancements at 900–1000 nm Wavelength Y. Gao et al.
12. Exploring the Mechanism of Crashes with Autonomous Vehicles Using Machine Learning H. Chen et al.
13. Modeling and Simulation of Self-Stabilizing Control Traffic Flow Based on Data Compensation 亚. 李
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16. SOTIF-Oriented Perception Evaluation Method for Forward Obstacle Detection of Autonomous Vehicles J. Chu et al.
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18. A Multivariable Model for Predicting Automotive LiDAR Visibility Under Driving-In-Rain Conditions W. Pao et al.
19. A New Paradigm in High-Speed and High-Efficiency Silicon Photodiodes for Communication—Part I: Enhancing Photon–Material Interactions via Low-Dimensional Structures H. Cansizoglu et al.
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21. Layered SOTIF Analysis and 3σ-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days L. Cao et al.
22. Adaptive strategy for CPPM single-photon collision avoidance LIDAR against dynamic crosstalk F. Zhang et al.
23. Event-triggered autonomous platoon control against probabilistic sensor and actuator failures W. Yue & L. Wang
24. Analysis of Automotive Lidar Sensor Model Considering Scattering Effects in Regional Rain Environments M. Byeon & S. Yoon
25. A Framework to Analyze Noise Factors of Automotive Perception Sensors P. Chan et al.
26. Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems Z. Liu & M. Conde
27. In-Field Measurement and Methodology for Modeling and Validation of Precipitation Effects on Solid-State LiDAR Sensors M. Kettelgerdes & G. Elger
28. 3D ToF LiDAR for Mobile Robotics in Harsh Environments: A Review T. Yang et al.
29. Fog Removal Study on Fog Point Distribution and Multi-Scale Dynamic Thresholding in the Field of Point Cloud Defogging Z. Liu et al.
30. Analysis of Factors Affecting the Severity of Automated Vehicle Crashes Using XGBoost Model Combining POI Data H. Chen et al.
31. Spoofing Attacks on FMCW Radars with Low-Cost Backscatter Tags A. Lazaro et al.
32. Problems related to the operation of autonomous vehicles in adverse weather conditions M. Brzozowski & K. Parczewski
33. Full Waveform LiDAR for Adverse Weather Conditions A. Wallace et al.
34. Parallel LiDARs Meet the Foggy Weather Y. Liu et al.
35. Experimental Analysis of Various Blockage Performance for LiDAR Sensor Cleaning Evaluation S. Son et al.
36. Assessing the Safety of Environment Perception in Automated Driving Vehicles M. Berk et al.
37. LIDAR Point Cloud Augmentation for Dusty Weather Based on a Physical Simulation H. Lian et al.
38. Synthetic Point Cloud Generation for Autonomous Driving: A Survey and Taxonomy A. Iglesias et al.
39. Detection of a target hidden in dense cloud clutter using an echo pattern of pulsed laser radar systems Z. Bahmeh & H. Zangeneh
40. Perceived rain dynamics on hydrophilic/hydrophobic lens surfaces and their influences on vehicle camera performance W. Pao et al.
41. Deep-learning blurring correction of images obtained from NIR single-pixel imaging C. Osorio Quero et al.
42. Reliability Assessment of Safety-Critical Sensor Information: Does One Need a Reference Truth? M. Berk et al.
43. A review of vehicle active safety control methods: From antilock brakes to semiautonomy A. Ahangarnejad et al.
44. Automotive System for Remote Surface Classification A. Bystrov et al.
45. Robust Fusion of LiDAR and Wide-Angle Camera Data for Autonomous Mobile Robots V. De Silva et al.
46. A Detection Method for Open–Close States of High-Voltage Disconnector in Smoky Environments L. Wang et al.
47. 基于光学模型的雾天点云渲染方法 于. Yu Huichun et al.
48. Research on Pulse Linear Array LiDAR Point Cloud Enhancement Algorithm in Snowy Environment X. Shi et al.
49. A Stochastic Physical Simulation Framework to Quantify the Effect of Rainfall on Automotive Lidar M. Berk et al.
50. Weather Classification Using an Automotive LIDAR Sensor Based on Detections on Asphalt and Atmosphere J. Vargas Rivero et al.
51. Investigation and Optimization of a Pulsed Laser Radar Transmitter for Detection Performance in a Cloud Turbulent Medium Z. Bahmeh & H. Zangeneh
52. A new search scheme using multi‐bee‐colony elite learning method for unmanned aerial vehicles in unknown environments W. Yue et al.
53. Innovations in 3D Object Detection: A Comprehensive Review of Methods, Sensor Fusion, and Future Directions G. Abro et al.
54. A Survey of Validation and Verification Methods for AI-Based Vehicle Functions T. Aslandere & U. Durak
55. Analytic and numeric study of polarized light propagation in turbid media for lidar applications M. Petzi et al.
56. DSRC-based rear-end collision warning system – An error-component safety distance model and field test X. Zhao et al.
57. LiDAR Point Cloud Augmentation for Adverse Conditions Using Conditional Generative Model Y. Zhang et al.
58. Characterization of Cubic Zirconia as a Lens Material Suitable for Autonomous Driving J. Lee et al.
59. From clear to snow: realistic LiDAR simulation via physical-statistical modeling C. Sun et al.
60. LiDAR Adverse-Weather Simulation with Ground Effect for Robust 3D Object Detection X. Ju et al.
61. An Overview of Lidar Imaging Systems for Autonomous Vehicles S. Royo & M. Ballesta-Garcia
62. Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation P. Kolar et al.
63. Reliability analysis of IoV-based vehicle monitoring systems subject to cascading probabilistic common cause failures C. Wang et al.
64. Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions M. Jokela et al.
65. A Depth-Buffer-Based Lidar Model With Surface Normal Estimation M. Kirchengast & D. Watzenig
66. Physical model of snow precipitation interaction with a 3D lidar scanner G. Roy et al.
67. An Extremely Low Noise-Equivalent Power Photoreceiver Using High-Gain InGaAs/AlGaAsSb APDs B. Sheridan et al.
68. Sensing with Polarized LIDAR in Degraded Visibility Conditions Due to Fog and Low Clouds A. Ronen et al.
69. Impact of Multi-Scattered LiDAR Returns in Fog D. Hevisov et al.
70. Asymmetric Gaussian Echo Model for LiDAR Intensity Correction X. Ma et al.
71. Spatial Semantic Fuzzing for LiDAR-Based Autonomous Driving Perception Systems A. Guo et al.
72. Function-Specific Uncertainty Communication in Automated Driving A. Kunze et al.
73. The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car S. Zang et al.
74. Stochastic Optimization of Adaptive Cruise Control S. Zhang et al.
75. Model‐guided extremum seeking–case studies Y. Tan et al.
76. Measuring the Influence of Environmental Conditions on Automotive Lidar Sensors C. Linnhoff et al.
77. Common Corruption Robustness of Point Cloud Detectors: Benchmark and Enhancement S. Li et al.
78. An Efficient Adaptive Noise Removal Filter on Range Images for LiDAR Point Clouds M. Le et al.
79. RadarVerses in Metaverses: A CPSI-Based Architecture for 6S Radar Systems in CPSS Y. Liu et al.
80. Method and Applications of Lidar Modeling for Virtual Testing of Intelligent Vehicles J. Zhao et al.
81. Performance Modeling a Near-Infrared ToF LiDAR Under Fog: A Data-Driven Approach T. Yang et al.
82. Photonic-Radar Based Multiple-Target Tracking Under Complex Traffic-Environments V. Sharma & L. Kumar
83. A Comprehensive Review of Autonomous Driving Algorithms: Tackling Adverse Weather Conditions, Unpredictable Traffic Violations, Blind Spot Monitoring, and Emergency Maneuvers C. Xu & R. Sankar
84. Perception and sensing for autonomous vehicles under adverse weather conditions: A survey Y. Zhang et al.
85. Polarised full-waveform warning LIDAR with dust backscattering suppression J. Liu et al.
86. Roadside LiDAR Sensor Configuration Assessment and Optimization Methods for Vehicle Detection and Tracking in Connected and Automated Vehicle Applications Y. Ge et al.
87. Research on Multiple Sensors Vehicle Detection With EMD-Based Denoising J. Li et al.
88. Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors M. Kettelgerdes et al.
89. Effect of principal environmental parameters on performance of LFMCW photonic radar during transmission S. Chen et al.
90. Automatic Vehicle Detection With Roadside LiDAR Data Under Rainy and Snowy Conditions J. Wu et al.
91. SCOPE: Spatial Context-Aware Pointcloud Encoder for Denoising Under the Adverse Weather Conditions H. Kim
92. Performance and Challenges of 3D Object Detection Methods in Complex Scenes for Autonomous Driving K. Wang et al.
93. Object Detection Based on Roadside LiDAR for Cooperative Driving Automation: A Review P. Sun et al.
94. Car2Car Communication Using a Modulated Backscatter and Automotive FMCW Radar A. Lazaro et al.
95. Adaptive Tube-Based Nonlinear MPC for Economic Autonomous Cruise Control of Plug-In Hybrid Electric Vehicles B. Sakhdari & N. Azad
96. Impact of Adverse Weather on Road Safety: A Survey of Test Methods for Enhancing Safety of Automated Vehicles and Sensor Robustness in Challenging Environmental Conditions M. Graf et al.
97. Reconstruction of the Aerosol Scattering Coefficient Profile in the Atmosphere from Echo-Pulse of a Short-Range Lidar A. Lisenko et al.
98. Ship Detection in Maritime Scenes under Adverse Weather Conditions Q. Zhang et al.
99. Measurement of target range and doppler shift by incorporating PDM-enabled FMCW-based photonic radar A. Sharma et al.
100. High Resolution-Based Coherent Photonic Radar Sensor for Multiple Target Detections S. Chaudhary et al.
101. A Survey on the autonomous exploration of confined subterranean spaces: Perspectives from real-word and industrial robotic deployments H. Azpúrua et al.
102. Vehicle Collision Prediction under Reduced Visibility Conditions K. Chen & P. Hsiung
103. Comparing real and simulated performance for an off‐road autonomous ground vehicle in obstacle avoidance D. Carruth et al.
104. Vehicle-Mounted LiDAR Multiobject Detection and Tracking Under Weak Point Cloud W. Liang et al.
105. Simultaneous measurements of velocity and distance via a dual-path FMCW lidar system F. Zhang et al.
106. Precise intrinsic calibration and geometrical stability analysis of automotive solid-state LiDAR sensors over temperature and lifetime M. Kettelgerdes et al.
107. Evaluating weather impact on vehicles: a systematic review of perceived precipitation dynamics and testing methodologies W. Pao et al.
108. GAN-Based LiDAR Translation between Sunny and Adverse Weather for Autonomous Driving and Driving Simulation J. Lee et al.
109. Realistic LiDAR With Noise Model for Real-Time Testing of Automated Vehicles in a Virtual Environment J. Espineira et al.
110. An Automotive LiDAR Performance Test Method in Dynamic Driving Conditions J. Park et al.
111. Event-triggered control of vehicular platoon system with time-varying delay and sensor faults K. Bansal & P. Mukhija
112. Cooperative Multi-Point Vehicular Positioning Using Millimeter-Wave Surface Reflection Z. Zhang et al.
113. Quantifying Automotive Lidar System Uncertainty in Adverse Weather: Mathematical Models and Validation B. Alavi et al.
114. Fault Detection, Isolation, Identification and Recovery (FDIIR) Methods for Automotive Perception Sensors Including a Detailed Literature Survey for Lidar T. Goelles et al.
115. An Adaptive Group of Density Outlier Removal Filter: Snow Particle Removal from LiDAR Data M. Le et al.
116. High-Efficiency SiGe/Si Heterojunction Phototransistor With Photon- Trapping Nanoholes Operating at 600–1000-nm Wavelength Y. Sha et al.
117. Particle polarization lidar for precipitation particle classification Y. Shibata
118. LiDAR-Based NDT Matching Performance Evaluation for Positioning in Adverse Weather Conditions J. Chang et al.
119. Analysis of LiDAR and Camera Data in Real-World Weather Conditions for Autonomous Vehicle Operations N. Goberville et al.
120. Photonic Sensor for Multiple Targets Detection under Adverse Weather Conditions in Autonomous Vehicles A. Sharma et al.
121. Sampled-Data Cooperative Adaptive Cruise Control of Vehicles With Sensor Failures G. Guo & W. Yue
122. A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors A. Haider et al.
123. BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data S. Reitmann et al.
124. Exploiting Redundancy for Reliability Analysis of Sensor Perception in Automated Driving Vehicles M. Berk et al.
125. Technical concepts of automotive LiDAR sensors: a review H. Holzhüter et al.
126. Neural Network-Driven Reliability Analysis in Safety Evaluation of LiDAR-Based Automated Vehicles: Considering Highway Vertical Alignments and Adverse Weather Conditions M. Cai et al.
127. Analysis of Automotive Lidar Corner Cases Under Adverse Weather Conditions B. Alavi et al.
128. A Lightweight Range-Image Network for LiDAR Point-Cloud Denoising in Adverse Weather T. la et al.
129. SS-WDA: Unsupervised Domain Adaptative 3-D Detection From Clear to Fog via Noise Simulation and Self-Training Y. Huang et al.
130. Research on a DSRC-Based Rear-End Collision Warning Model X. Xiang et al.
131. Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces A. Kunze et al.
132. Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes H. Tan et al.
133. Gated Recurrent Fusion to Learn Driving Behavior from Temporal Multimodal Data A. Narayanan et al.
134. Through-the-Wall Micro-Doppler De-Wiring Technique via Cycle-Consistent Adversarial Network S. Wang et al.
135. Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems Y. Liu et al.
136. Challenges and Innovations in 3D Object Recognition: The Integration of LiDAR and Camera Sensors for Autonomous Applications G. Abro et al.
137. Architecture and Potential of Connected and Autonomous Vehicles M. Pipicelli et al.
138. CMHT autonomous dataset: A multi-sensor dataset including radar and IR for autonomous driving H. Zhang et al.
139. Real-Time LiDAR Signal Augmentation for Testing and Evaluation of Autonomous Systems in Virtual Adverse Weather S. Hwang et al.
140. Advancing low-carbon smart cities: Leveraging UAVs-enabled low-altitude economy principles and innovations H. Tan et al.
141. A General Approach for Simulating Rain Effects on Sensor Data in Real and Virtual Environments S. Hasirlioglu & A. Riener
142. Detection and Tracking of MAVs Using a Rosette Scanning Pattern LiDAR S. Gazdag et al.
143. Fast and Accurate Desnowing Algorithm for LiDAR Point Clouds J. Park et al.
144. Reconstruction and Synthesis of Lidar Point Clouds of Spray Y. Shih et al.
145. Review and evaluation of recent advancements in image dehazing techniques for vision improvement and visualization S. Shit & D. Ray
146. A Quantitative Analysis of Point Clouds from Automotive Lidars Exposed to Artificial Rain and Fog K. Montalban et al.
147. Life-threatening alcohol-related traffic crashes in adverse weather: a double-matched case–control analysis from Canada D. Redelmeier & F. Manzoor
148. A Study on Recent Developments and Issues with Obstacle Detection Systems for Automated Vehicles X. Yu & M. Marinov
149. Bayesian inference of visibility in fog and smoke artificial conditions from 3D-LiDAR point clouds K. Montalban et al.
150. What Happens for a ToF LiDAR in Fog? Y. Li et al.
151. Characterisation of the Tyre Spray Ejected Downstream of a Bluff Automotive Body C. Crickmore et al.
152. Event-triggered platoon control of vehicles with time-varying delay and probabilistic faults Y. Wei et al.
153. Performance Test of Autonomous Vehicle Lidar Sensors Under Different Weather Conditions L. Tang et al.
154. Real-time Contaminated Surface Determination Algorithm for Automotive LiDAR Sensors J. Won et al.
155. CIDM: A comprehensive inpainting diffusion model for missing weather radar data with knowledge guidance W. Zhang et al.
156. A Review of Testing Object-Based Environment Perception for Safe Automated Driving M. Hoss et al.
157. Simulation of LiDAR Under Fog with Generative Adversarial Networks for Robust 3D Object Detection Y. Park et al.
158. Cooperative Adaptive Cruise Control of Vehicles Using a Resource-Efficient Communication Mechanism S. Wen et al.
159. Point cloud processing under adverse weather: a survey of datasets, enhancement, and denoising methods Z. Gu et al.
160. Predicting the Influence of Rain on LIDAR in ADAS C. Goodin et al.
161. Learn to Model and Filter Point Cloud Noise for a Near-Infrared ToF LiDAR in Adverse Weather T. Yang et al.
162. Deep Learning-Based Real-Time Vehicle Tire and Tank Temperature Monitoring Using Thermal Cameras Y. Hu et al.
163. The Effect of Spray Water on an Automotive LIDAR Sensor: A Real-Time Simulation Study J. Vargas Rivero et al.
164. Swept-wavelength lasers based on GaSb gain-chip technology for non-invasive biomedical sensing applications in the 1.7–2.5 μm wavelength range A. Vizbaras et al.
165. Full Physics Simulation Study of Guardrail Radar-Returns for 77 GHz Automotive Radar Systems U. Chipengo
166. Hierarchical Attention-Based Sensor Fusion Strategy for Depth Estimation in Diverse Weather M. Xiong et al.
167. Rear-End Collision Avoidance-Based on Multi-Channel Detection Y. Xiang et al.
168. A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges M. Ahangar et al.
169. A Cost-Effective Photonic Radar Under Adverse Weather Conditions for Autonomous Vehicles by Incorporating a Frequency-Modulated Direct Detection Scheme A. Sharma et al.
170. Control Architecture for Connected Vehicle Platoons: From Sensor Data to Controller Design Using Vehicle-to-Everything Communication R. Lazar et al.
171. Automotive Lidar Modelling Approach Based on Material Properties and Lidar Capabilities S. Muckenhuber et al.
172. A Hierarchical LiDAR Simulation Framework Incorporating Physical Attenuation Response in Autonomous Driving Scenarios T. Huang et al.
173. CNN-Based Lidar Point Cloud De-Noising in Adverse Weather R. Heinzler et al.
174. Virtual Testing of Automated Driving Systems. A Survey on Validation Methods R. Dona & B. Ciuffo
175. 3D vehicle detection improving method fusing image and LiDAR in foggy environment S. Niu et al.