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Towards Provably Not-at-Fault Control of Autonomous Robots in Arbitrary Dynamic Environments [article]

Sean Vaskov, Shreyas Kousik, Hannah Larson, Fan Bu, James Ward, Stewart Worrall, Matthew Johnson-Roberson, Ram Vasudevan
2019 arXiv   pre-print
Then, for online receding-horizon planning, the method provides a way to discretize predictions of an arbitrary dynamic environment to enable real-time collision checking.  ...  As autonomous robots increasingly become part of daily life, they will often encounter dynamic environments while only having limited information about their surroundings.  ...  Similar to the approach used by Kousik, Vaskov, Bu, et al.  ... 
arXiv:1902.02851v1 fatcat:c373dfnsefgrlmy6sc2vwyfhky

Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving [article]

Sotirios Diamantas, Kostas Alexis
2018 arXiv   pre-print
In our approach we exploit the optical flow vectors generated by the motion of the camera while keeping parameter assumptions a minimum.  ...  provide a fully autonomous vehicle.  ...  of moving objects in their field of view to avoid collisions and plan a safe path.  ... 
arXiv:1811.06660v1 fatcat:5ikhfmmkand7vkdysmi45bfu4e

From Software-Defined Vehicles to Self-Driving Vehicles: A Report on CPSS-Based Parallel Driving

Shuangshuang Han, Dongpu Cao, Li Li, Lingxi Li, Shengbo Eben Li, Nan-Ning Zheng, Fei-Yue Wang
2019 IEEE Intelligent Transportation Systems Magazine  
self-driving bus, parallel self-driving taxi, parallel self-driving subway and so on.  ...  which necessitates a unified approach for future smart and safe driving.  ... 
doi:10.1109/mits.2018.2876575 fatcat:j3kky4ywpjhuhbpiu2fq5j47nm

Lane-Change Initiation and Planning Approach for Highly Automated Driving on Freeways [article]

Salar Arbabi, Shilp Dixit, Ziyao Zheng, David Oxtoby, Alexandros Mouzakitis, Saber Fallah
2020 arXiv   pre-print
This paper presents a low-complexity approach for lane-change initiation and planning to facilitate highly automated driving on freeways.  ...  Motion planning is formulated as a finite-horizon optimisation problem with safety constraints.  ...  Index Terms-Autonomous Vehicles, Decision Making, Motion Planning I.  ... 
arXiv:2007.14032v2 fatcat:53idpayfxrgttnbxgp7djcrbqm

Explanations in Autonomous Driving: A Survey [article]

Daniel Omeiza, Helena Webb, Marina Jirotka, Lars Kunze
2021 arXiv   pre-print
In this paper, we provide a comprehensive survey of the existing work in explainable autonomous driving.  ...  This survey serves to provide fundamental knowledge required of researchers who are interested in explanation in autonomous driving.  ...  They also thank the Assuring Autonomy International Programme, a partnership between Lloyd's Register Foundation and the University of York.  ... 
arXiv:2103.05154v2 fatcat:dmx6w7qr6vgljpe32s5s4523om

GAMMA: A General Agent Motion Model for Autonomous Driving [article]

Yuanfu Luo and Panpan Cai and Yiyuan Lee and David Hsu
2022 arXiv   pre-print
This paper presents GAMMA, a general motion prediction model that enables large-scale real-time simulation and planning for autonomous driving. GAMMA models heterogeneous, interactive traffic agents.  ...  Further, the computational efficiency and the flexibility of GAMMA enable (i) simulation of mixed urban traffic at many locations worldwide and (ii) planning for autonomous driving in dense traffic with  ...  We develop GAMMA, a General Agent Motion prediction Model for Autonomous driving, that integrates these factors in a unified framework.  ... 
arXiv:1906.01566v5 fatcat:ghhgyjugbvfajkgefbrkdzmqrq

End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners [article]

Simon Hecker, Dengxin Dai, Luc Van Gool
2018 arXiv   pre-print
Finally, we learn a novel driving model by integrating information from the surround-view cameras and the route planner.  ...  We investigate the problem in a more realistic setting, which consists of a surround-view camera system with eight cameras, a route planner, and a CAN bus reader.  ...  of planned routes by two route planners, and GPS-IMU data for the vehicle's odometry; 2) a novel deep network to map directly from the sensor inputs to future driving maneuvers.  ... 
arXiv:1803.10158v2 fatcat:6bgsca7qofhixdvnmwjgzy2idi

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
This is a survey of autonomous driving technologies with deep learning methods.  ...  We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc.  ...  Planning can be classified as route (mission) planning, behaviour planning and motion planning at different levels. • Route planning is referred as finding the point-to-point shortest path in a directed  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

Computing Systems for Autonomous Driving: State-of-the-Art and Challenges [article]

Liangkai Liu, Sidi Lu, Ren Zhong, Baofu Wu, Yongtao Yao, Qingyang Zhang, Weisong Shi
2020 arXiv   pre-print
The key to the success of these autonomous systems is making a reliable decision in real-time fashion.  ...  In this paper, we present state-of-the-art computing systems for autonomous driving, including seven performance metrics and nine key technologies, followed by twelve challenges to realize autonomous driving  ...  Their designs are all based on modules including perception, mission planning, motion planning, and vehicle controls.  ... 
arXiv:2009.14349v3 fatcat:xmo6mxucizf33hu2n2ddoy4xsy

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving [article]

Chenxu Luo, Xiaodong Yang, Alan Yuille
2021 arXiv   pre-print
3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving vehicles.  ...  Our key design is to predict the first-appear location of each object in a given snippet to get the tracking identity and then update the location based on motion estimation.  ...  Extensive experimental results demonstrate the efficacy of our approach. We hope this work can inspire more research toward simple and robust tracking systems for autonomous driving. A.  ... 
arXiv:2108.10312v1 fatcat:42bt4mpumvfxhnvscfm5azykru

A reference architecture for cooperative driving

Sagar Behere, Martin Törngren, De-Jiu Chen
2013 Journal of systems architecture  
Cooperative driving systems enable vehicles to adapt their motion to the surrounding trac situation by utilizing information communicated by other vehicles and infrastructure in the vicinity.  ...  We created a reference architecture that systematically answers these questions and validated it in real world usage scenarios.  ...  A historical review on the longitudinal and lateral control of autonomous vehicle motion is given in [10] .  ... 
doi:10.1016/j.sysarc.2013.05.014 fatcat:xfgm4urx4bdexpkeebnas54x6q

Failure Prediction for Autonomous Driving [article]

Simon Hecker, Dengxin Dai, Luc Van Gool
2018 arXiv   pre-print
The primary focus of autonomous driving research is to improve driving accuracy. While great progress has been made, state-of-the-art algorithms still fail at times.  ...  A camera-based driving model is developed and trained over real driving datasets.  ...  However, route planning has been used to improve driving models in our recent work [21] and a fusion of route planned aware driving models with failure prediction is considered as our next future work  ... 
arXiv:1805.01811v1 fatcat:6c7xit5uu5acvmornvlfcp35eq

Lateral-Acceleration-Based Vehicle-Models-Blending for Automated Driving Controllers

Jose A. Matute-Peaspan, Mauricio Marcano, Sergio Diaz, Asier Zubizarreta, Joshue Perez
2020 Electronics  
for autonomous driving.  ...  This work presents a novel approach based on lateral accelerations, along with a formal procedure and criteria to tune and select blending parameters, for its use on model-based predictive controllers  ...  In this work, a novel approach is proposed.  ... 
doi:10.3390/electronics9101674 fatcat:jzcmk4zs3jap5ob2dzz33hqvwi

MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps [article]

Pengxiang Wu, Siheng Chen, Dimitris Metaxas
2020 arXiv   pre-print
This indicates the potential value of the proposed method serving as a backup to the bounding-box-based system, and providing complementary information to the motion planner in autonomous driving.  ...  The ability to reliably perceive the environmental states, particularly the existence of objects and their motion behavior, is crucial for autonomous driving.  ...  Our results suggest the potential value of MotionNet in serving as a backup system and providing complementary information to the motion planning in autonomous driving. Figure 1 . 1 Figure 1.  ... 
arXiv:2003.06754v1 fatcat:q2lcvh5exjawja2qx5tgxt567u

AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles [article]

Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun
2022 arXiv   pre-print
Our experiments show that our approach is general and can identify thousands of semantically meaningful safety-critical scenarios for a wide range of modern self-driving systems.  ...  Traditionally, those scenarios are generated for a few scenes with respect to the planning module that takes ground-truth actor states as input.  ...  Experimental Setup Dataset We evaluate our approach on a self-driving dataset, UrbanScenarios, which has 5,000 driving logs of 25 seconds each.  ... 
arXiv:2101.06549v3 fatcat:xuhsg67ybbev3ma6ux352wxcea
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