The Acceptance of Independent Autonomous Vehicles and Cooperative Vehicle-Highway Autonomous Vehicles by Shuang Zhang, Peng Jing, Gang Xu

“…Additionally, risks, performance, existing traffic conditions, and personal innovation awareness also significantly affect autonomous driving acceptance. The research results can provide a theoretical basis for technology developers and industry managers to develop autonomous driving technology and policymaking.…”
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Lightweight Deep Learning for Road Environment Recognition by Han Liang, Suyoung Seo

“…With recent developments in the field of autonomous driving, recognition algorithms for road environments are being developed very rapidly. …”
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Back from the future. A backcasting on autonomous vehicles in the real city by Luca Staricco, Elisabetta Vitale Brovarone, Jacopo Scudellari

“…For this reason, backcasting is often mentioned as suitable to deal with the transition to autonomous driving. However, at present the applications of backcasting to this transition in real-world cases are quite few. …”
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Learning to Drive in the NGSIM Simulator Using Proximal Policy Optimization by Yang Zhou, Yunxing Chen

“…As a popular research field, autonomous driving may offer great benefits for human society. …”
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A Feasibility Study of a Traffic Supervision System Based on 5G Communication by Allan Tengg, Michael Stolz, Joachim Hillebrand

“…At present, autonomous driving vehicles are designed in an ego-vehicle manner. …”
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Priest: Adversarial Attack Detection Techniques for Signal Injection Attacks by Jaehwan Park, Changhee Hahn

“…Machine learning is widely used for autonomous driving because it can recognize surrounding circumstances feasibly from sensor and determine appropriate actions. …”
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Statistical Risk and Performance Analyses on Naturalistic Driving Trajectory Datasets for Traffic Modeling by Ruixue Zong, Ying Wang, Juan Ding, Weiwen Deng

“…The development of autonomous driving technology has made simulation testing one of the most important tools for evaluating system performance. …”
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YOLO MDE: Object Detection with Monocular Depth Estimation by Jongsub Yu, Hyukdoo Choi

“…However, predicting complex output compositions leads a model to have generally low performances, and it is not necessary for risk assessment for autonomous driving. We focused on predicting a single depth per object, which is essential for risk assessment for autonomous driving. …”
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Instance segmentation for roadside objects using a simulation environment by Wang, Sijie

“…In the autonomous driving system, the understanding of traffic is always an important task. …”
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ESTABLISHMENT OF HD MAPS VERIFICATION AND VALIDATION PROCEDURE WITH OPENDRIVE AND AUTOWARE (LANELET2) FORMATS by K.-W. Chiang, M.-L. Tsai, S. Lin, Y.-E. Huang, J.-C. Zeng, Y.-F. Chang, J.-A. Chen, Y.-C. Huang, C.-S. Yang, J.-C. Juang, C.-K. Wang, C.-F. Lin, J. Lee, H. Darweesh, P.-L. Li

“…High-definition (HD) maps are key for autonomous driving because of their high accuracy and rich information of road scenes. …”
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CAM-FRN: Class Attention Map-Based Flare Removal Network in Frontal-Viewing Camera Images of Vehicles by Seon Jong Kang, Kyung Bong Ryu, Min Su Jeong, Seong In Jeong, Kang Ryoung Park

“…In recent years, active research has been conducted on computer vision and artificial intelligence (AI) for autonomous driving to increase the understanding of the importance of object detection technology using a frontal-viewing camera. …”
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Analyzing the inconsistency in driving patterns between manual and autonomous modes under complex driving scenarios with a VR-enabled simulation platform by Zheng Xu, Yihai Fang, Nan Zheng, Hai L. Vu

“…Purpose – With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios. Design/methodology/approach – The simulation environment is established by integrating virtual reality interface with a micro-simulation model. …”
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Visual recognition using deep learning (traffic detection using deep learning) by Chen, Sheng

“…In recent years, with the rapid development of autonomous driving, the objective detection technology in driving assistance has become a major research hotspot. …”
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Toward trustworthy decision-making for autonomous vehicles: a robust reinforcement learning approach with safety guarantees by He, Xiangkun, Huang, Wenhui, Lv, Chen

“…These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.…”
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Quantizing YOLOv5 for Real-Time Vehicle Detection by Zicheng Zhang, Hongke Xu, Shan Lin

“…Autonomous driving has received much attention in the last decade as a key component of intelligent transportation, and vehicle detection serves as a fundamental task for autonomous driving. …”
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Autonomous Vehicles: A Value Proposition for Emerging Markets—The Case of Kuwait by Sam Toglaw, Andri Ottesen, Yamen Nissi

“…The advancements in autonomous driving technology are triggering a worldwide disruption to the transportation industry. …”
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Study on automated driving system for two-stage stop and start operation for intersection collision avoidance in unsignalized intersections by Pongsathorn RAKSINCHAROENSAK, Koichi TSUCHIYA, Akito YAMASAKI, Hiroshi MOURI, Masao NAGAI

“…This paper proposes an autonomous driving system that stops at the stop line automatically before entering intersection, re-start and autonomous brake with safety confirmation against crossing vehicles to reduce intersection collisions. …”
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Review on Functional Testing Scenario Library Generation for Connected and Automated Vehicles by Yu Zhu, Jian Wang, Fanqiang Meng, Tongtao Liu

“…The advancement of autonomous driving technology has had a significant impact on both transportation networks and people’s lives. …”
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Robust Stereo Road Image Segmentation Using Threshold Selection Optimization Method Based on Persistent Homology by Wenbin Zhu, Hong Gu, Zhenhong Fan, Xiaochun Zhu

“…The research holds potential for application in autonomous driving systems.…”
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Adaptive Ultrasound-Based Tractor Localization for Semi-Autonomous Vineyard Operations by Matteo Corno, Sara Furioli, Paolo Cesana, Sergio M. Savaresi

“…Autonomous driving is greatly impacting intensive and precise agriculture. …”
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