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Cooperatively utilizing both ego-vehicle and infrastructure sensor data via V2X communication has emerged as a promising approach for advanced autonomous driving.
The Hungarian method for the assignment problem
Kuhn, H. W. 1955 · 1955
Earlier work this paper cites.
The Hungarian Method for the Assignment Problem
Kuhn, H. W. 2010 · 2010
Earlier work this paper cites.
End to end learning for self-driving cars
Bojarski, M.; Del Testa, D.; Dworakowski, D.; Firner, B.; Flepp, B.; Goyal, P.; Jackel, L. D.; Monfort, M.; Muller, U.; Zhang, J.; et al. 2016 · 2016
Earlier work this paper cites.
Soft-NMS–improving object detection with one line of code
Bodla, N.; Singh, B.; Chellappa, R.; and Davis, L. S. 2017 · 2017
Earlier work this paper cites.
CARLA: An open urban driving simulator
Dosovitskiy, A.; Ros, G.; Codevilla, F.; Lopez, A.; and Koltun, V. 2017 · 2017
Earlier work this paper cites.
End-to-end driving via conditional imitation learning
Codevilla, F.; Müller, M.; López, A.; Koltun, V.; and Dosovitskiy, A. 2018 · 2018
Earlier work this paper cites.
Cirl: Controllable imitative reinforcement learning for vision-based self-driving
Liang, X.; Wang, T.; Yang, L.; and Xing, E. 2018 · 2018
Earlier work this paper cites.
Microscopic traffic simulation using sumo
Lopez, P. A.; Behrisch, M.; Bieker-Walz, L.; Erdmann, J.; Flötteröd, Y.-P.; Hilbrich, R.; Lücken, L.; Rummel, J.; Wagner, P.; and Wießner, E. 2018 · 2018
Earlier work this paper cites.
Cooper: Cooperative perception for connected autonomous vehicles based on 3d point clouds
Chen, Q.; Tang, S.; Yang, Q.; and Fu, S. 2019 · 2019
Earlier work this paper cites.
Learning to drive in a day
Kendall, A.; Hawke, J.; Janz, D.; Mazur, P.; Reda, D.; Allen, J.-M.; Lam, V.-D.; Bewley, A.; and Shah, A. 2019 · 2019
Earlier work this paper cites.
Controlling steering angle for cooperative self-driving vehicles utilizing CNN and LSTM-based deep networks
Valiente, R.; Zaman, M.; Ozer, S.; and Fallah, Y. P. 2019 · 2019
Earlier work this paper cites.
nuscenes: A multimodal dataset for autonomous driving
Caesar, H.; Bankiti, V.; Lang, A. H.; Vora, S.; Liong, V. E.; Xu, Q.; Krishnan, A.; Pan, Y.; Baldan, G.; and Beijbom, O. 2020 · 2020
Earlier work this paper cites.
End-to-end object detection with transformers
Carion, N.; Massa, F.; Synnaeve, G.; Usunier, N.; Kirillov, A.; and Zagoruyko, S. 2020 · 2020
Earlier work this paper cites.
Perceive, predict, and plan: Safe motion planning through interpretable semantic representations
Sadat, A.; Casas, S.; Ren, M.; Wu, X.; Dhawan, P.; and Urtasun, R. 2020 · 2020
Earlier work this paper cites.
V2vnet: Vehicle-to-vehicle communication for joint perception and prediction
Wang, T.-H.; Manivasagam, S.; Liang, M.; Yang, B.; Zeng, W.; and Urtasun, R. 2020 · 2020
Earlier work this paper cites.
Dsdnet: Deep structured self-driving network
Zeng, W.; Wang, S.; Liao, R.; Chen, Y.; Yang, B.; and Urtasun, R. 2020 · 2020
Earlier work this paper cites.
FIERY: Future Instance Prediction in Bird’s-Eye View From Surround Monocular Cameras
Hu, A.; Murez, Z.; Mohan, N.; Dudas, S.; Hawke, J.; Badrinarayanan, V.; Cipolla, R.; and Kendall, A. 2021 · 2021
Earlier work this paper cites.
Learning distilled collaboration graph for multi-agent perception
Li, Y.; Ren, S.; Wu, P.; Chen, S.; Feng, C.; and Zhang, W. 2021 · 2021
Cited alongside, same era.
Multi-modal fusion transformer for end-to-end autonomous driving
Prakash, A.; Chitta, K.; and Geiger, A. 2021 · 2021
Cited alongside, same era.
A9-dataset: Multi-sensor infrastructure-based dataset for mobility research
Creß, C.; Zimmer, W.; Strand, L.; Fortkord, M.; Dai, S.; Lakshminarasimhan, V.; and Knoll, A. 2022 · 2022
Cited alongside, same era.
Coopernaut: End-to-end driving with cooperative perception for networked vehicles
Cui, J.; Qiu, H.; Chen, D.; Stone, P.; and Zhu, Y. 2022 · 2022
Cited alongside, same era.
Where2comm: Communication-efficient collaborative perception via spatial confidence maps
Hu, Y.; Fang, S.; Lei, Z.; Zhong, Y.; and Chen, S. 2022 · 2022
Cited alongside, same era.
Latency-aware collaborative perception
Roadside LiDAR Assisted Cooperative Localization for Connected Autonomous Vehicles
Jiang, Y.; Javanmard, E.; Nakazato, J.; Tsukada, M.; and Esaki, H. 2023 · 2023
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Robust collaborative 3d object detection in presence of pose errors
Lu, Y.; Li, Q.; Liu, B.; Dianati, M.; Feng, C.; Chen, S.; and Wang, Y. 2023 · 2023
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Learning Cooperative Trajectory Representations for Motion Forecasting
Ruan, H.; Yu, H.; Yang, W.; Fan, S.; Tang, Y.; and Nie, Z. 2023 · 2023
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Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Shao, H.; Wang, L.; Chen, R.; Li, H.; and Liu, Y. 2023 · 2023
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Asynchrony-Robust Collaborative Perception via Bird’s Eye View Flow
Sizhe, W.; Yuxi, W.; Yue, H.; Yifan, L.; Yiqi, Z.; Siheng, C.; and Zhang, Y. 2023 · 2023
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Lei, Z.; Ren, S.; Hu, Y.; Zhang, W.; and Chen, S. 2022 · 2022
Cited alongside, same era.
Dolphins: Dataset for collaborative perception enabled harmonious and interconnected self-driving
Mao, R.; Guo, J.; Jia, Y.; Sun, Y.; Zhou, S.; and Niu, Z. 2022 · 2022
Cited alongside, same era.
Distributed data-sharing consensus in cooperative perception of autonomous vehicles
Qiu, C.; Yadav, S.; Squicciarini, A.; Yang, Q.; Fu, S.; Zhao, J.; and Xu, C. 2022 · 2022
Cited alongside, same era.
Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline
Wu, P.; Jia, X.; Chen, L.; Yan, J.; Li, H.; and Qiao, Y. 2022 · 2022
Cited alongside, same era.
Opv2v: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication
Xu, R.; Xiang, H.; Xia, X.; Han, X.; Li, J.; and Ma, J. 2022c · 2022
Cited alongside, same era.
Dair-v2x: A large-scale dataset for vehicle-infrastructure cooperative 3d object detection
Yu, H.; Luo, Y.; Shu, M.; Huo, Y.; Yang, Z.; Shi, Y.; Guo, Z.; Li, H.; Hu, X.; Yuan, J.; et al. 2022 · 2022
Cited alongside, same era.
BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
Zhang, Y.; Zhu, Z.; Zheng, W.; Huang, J.; Huang, G.; Zhou, J.; and Lu, J. 2022 · 2022
Cited alongside, same era.
Collective PV-RCNN: A Novel Fusion Technique using Collective Detections for Enhanced Local LiDAR-Based Perception
Teufel, S.; Gamerdinger, J.; Volk, G.; and Bringmann, O. 2023 · 2023
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UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Framework
Tianhang, W.; Guang, C.; Kai, C.; Zhengfa, L.; Bo, Z.; Alois, K.; and Jiang, C. 2023 · 2023
Later among the works it cites.
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving
Wang, T.; Kim, S.; Ji, W.; Xie, E.; Ge, C.; Chen, J.; Li, Z.; and Luo, P. 2023 · 2023
Later among the works it cites.
OpenCDA- ∞ \infty : A Closed-loop Benchmarking Platform for End-to-end Evaluation of Cooperative Perception
Chen, C.-J.; Xu, R.; Shao, W.; Zhang, J.; and Tu, Z. 2024 · 2024
Closest in time.
Quest: Query stream for vehicle-infrastructure cooperative perception
Fan, S.; Yu, H.; Yang, W.; Yuan, J.; and Nie, Z. 2024 · 2024
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Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
Li, Z.; Yu, Z.; Lan, S.; Li, J.; Kautz, J.; Lu, T.; and Alvarez, J. M. 2024 · 2024
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V2VFormer: Vehicle-to-Vehicle Cooperative Perception with Spatial-Channel Transformer
Lin, C.; Tian, D.; Duan, X.; Zhou, J.; Zhao, D.; and Cao, D. 2024 · 2024
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Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System
Liu, G.; Hu, Y.; Xu, C.; Mao, W.; Ge, J.; Huang, Z.; Lu, Y.; Xu, Y.; Xia, J.; Wang, Y.; et al. 2024 · 2024
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Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles
Song, R.; Liang, C.; Cao, H.; Yan, Z.; Zimmer, W.; Gross, M.; Festag, A.; and Knoll, A. 2024 · 2024
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LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation
Yang, Z.; Mao, J.; Yang, W.; Ai, Y.; Kong, Y.; Yu, H.; and Zhang, W. 2024 · 2024
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Leveraging temporal contexts to enhance vehicle-infrastructure cooperative perception
Zhong, J.; Yu, H.; Zhu, T.; Xu, J.; Yang, W.; Nie, Z.; and Sun, C. 2024 · 2024
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