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Vehicle Localization via Cooperative Channel Mapping [article]

Xinghe Chu, Zhaoming Lu, David Gesbert, Luhan Wang, Xiangming Wen
2021 arXiv   pre-print
An algorithm is derived for reflector selection and estimation, combined with a team particle filter (TPF) so as to achieve high precision simultaneous multiple vehicle positioning.  ...  This paper addresses vehicle positioning, a topic whose importance has risen dramatically in the context of future autonomous driving systems.  ...  ACKNOWLEDGMENT This work is partially supported by Research on the key technology of seamless handover in cloud-RAN for network assisted automatic driving, NSFC project, under grant 61801047.  ... 
arXiv:2102.04852v1 fatcat:kqmgmrrgenh3higgmcbyxkwgni

Radar-based Dynamic Occupancy Grid Mapping and Object Detection [article]

Christopher Diehl, Eduard Feicho, Alexander Schwambach, Thomas Dammeier, Eric Mares, Torsten Bertram
2020 arXiv   pre-print
The approach is evaluated qualitatively and quantitatively with real-world data from a moving vehicle in urban environments.  ...  Subsequently, the clustering of dynamic areas provides high-level object information. For comparison, also a lidar-based method is developed.  ...  Nevertheless, the radar-based method also leads to errors due to noisy measurements caused by multi-path propagation as in areas of a metallic scaffold 4 or fence 5 .  ... 
arXiv:2008.03696v1 fatcat:ucnno2ssanbsvpojjcru2qbsbe

IEEE Access Special Section Editorial: Urban Computing and Intelligence

Rongbo Zhu, Lu Liu, Maode Ma, Hongxiang Li, Shiwen Mao
2021 IEEE Access  
This Special Section has provided a platform for researchers and practitioners from both academia and industry in the area of urban computing and intelligence.  ...  A command-level anomaly detection (CAD) method is proposed for a vehicle-road collaborative 130690 This work is licensed under a Creative Commons Attribution 4.0 License.  ...  He serves as an editorial board member for six international journals and a guest editor for international journals.  ... 
doi:10.1109/access.2021.3111669 fatcat:qmiy5ngnyvfcvbe5is7estlfou

Efficient Techniques for Dynamic Vehicle Detection [chapter]

Anna Petrovskaya, Sebastian Thrun
2009 Springer Tracts in Advanced Robotics  
We present the vehicle detection algorithm developed for our entry in the Urban Grand Challenge, an autonomous driving race organized by the U.S. Government in 2007.  ...  Fast detection of moving vehicles is crucial for safe autonomous urban driving.  ...  The authors thank all team members for their hard work. The Stanford Racing Team is indebted to DARPA for creating the UGC, and for its financial support under the Track A Program.  ... 
doi:10.1007/978-3-642-00196-3_10 fatcat:i4vxkwq5qfeatbax2ruvp6i3da

3D Scene Understanding at Urban Intersection Using Stereo Vision and Digital Map

Prarthana Bhattacharyya, Yanlei Gu, Jiali Bao, Xu Liu, Shunsuke Kamijo
2017 2017 IEEE 85th Vehicular Technology Conference (VTC Spring)  
It is thus crucial for autonomous vehicles to comprehensively understand challenging urban traffic scenes in order to navigate intersections and prevent accidents.  ...  Stereo vision is used to detect, classify and track obstacles, while a 3D digital map is used to improve ego-localization and provide context in terms of road-layout information.  ...  With the particle states and positioning result at 𝑡 − 1, the particle filter will exclude low-weighted particles, and recursively estimate the localization result x 𝑡 for the ego-vehicle at time 𝑡.  ... 
doi:10.1109/vtcspring.2017.8108283 dblp:conf/vtc/BhattacharyyaGB17 fatcat:um42cudbqrhwzkowwgh6lp4ww4

All Weather Perception: Joint Data Association, Tracking, and Classification for Autonomous Ground Vehicles [article]

Peter Radecki, Mark Campbell, Kevin Matzen
2016 arXiv   pre-print
The presented algorithm extends a Rao-Blackwellized Particle Filter originally built with a particle filter for data association and a Kalman filter for multi-object tracking (Miller et al. 2011a) to now  ...  A novel probabilistic perception algorithm is presented as a real-time joint solution to data association, object tracking, and object classification for an autonomous ground vehicle in all-weather conditions  ...  Acknowledgments The authors would like to thank Trimble for providing Omnnistar HP DGPS corrections service, NVIDIA for providing a GTX980 GPU, Kevin Wyffels for insightful discussions on the classification  ... 
arXiv:1605.02196v1 fatcat:rh7tx4x7qfaonb7yoc34qcmziu

Model Based Vehicle Tracking for Autonomous Driving in Urban Environments

Anna Petrovskaya, Sebastian Thrun
2008 Robotics: Science and Systems IV  
Situational awareness is crucial for autonomous driving in urban environments. This paper describes moving vehicle tracking module that we developed for our autonomous driving robot Junior.  ...  Our approach models both dynamic and geometric properties of the tracked vehicles and estimates them using a single Bayes filter per vehicle.  ...  The authors thank all team members for their hard work. The Stanford Racing Team is indebted to DARPA for creating the Urban Challenge, and for its financial support under the Track A Program.  ... 
doi:10.15607/rss.2008.iv.023 dblp:conf/rss/PetrovskayaT08 fatcat:yg5vgvoxs5a57l5dq3fdnwwlji

HybridSLAM: Combining FastSLAM and EKF-SLAM for Reliable Mapping [chapter]

Alex Brooks, Tim Bailey
2009 Springer Tracts in Advanced Robotics  
In addition, the HybridSLAM algorithm is experimentally validated in a real urban environment.  ...  The use of FastSLAM locally avoids linearisation of the vehicle model and provides a high level of robustness to clutter and ambiguous data association.  ...  Live Experiments The HYBRID filter was used to generate a map in a real urban environment, using a Segway RMP equipped with a SICK laser, as shown in Figure 5 .  ... 
doi:10.1007/978-3-642-00312-7_40 fatcat:xdhsrq5ptnhofc4ilg6rx3uoc4

Overview of Environment Perception for Intelligent Vehicles

Hao Zhu, Ka-Veng Yuen, Lyudmila Mihaylova, Henry Leung
2017 IEEE transactions on intelligent transportation systems (Print)  
The state-of-the-art algorithms and modeling methods for intelligent vehicles are given, with a summary of their pros and cons.  ...  A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding.  ...  A joint lanes and vehicles tracking system was proposed by a PDA filter using camera in [147] .  ... 
doi:10.1109/tits.2017.2658662 fatcat:mvfmou6ydjafnjq3ddk5rqi5ia

Obstructed Target Tracking in Urban Environments [article]

Christopher Berry, Donald J. Bucci
2019 arXiv   pre-print
In this paper, we propose the integration of geospatial data for an urban environment into a particle filter realization of a random finite set target tracking algorithm.  ...  The localization error performance improvement for a single target Bernoulli filter under these modifications is presented using freely available building vector data of New York City.  ...  In this paper, we provide a method for integrating urban geographic information system (GIS) data into a Bernoulli random finite set (RFS) tracker [12] for localizing targets within a 2D cartesian plane  ... 
arXiv:1906.02397v1 fatcat:psjsj3vt6jhdzfbx6srle3beq4

Model based vehicle detection and tracking for autonomous urban driving

Anna Petrovskaya, Sebastian Thrun
2009 Autonomous Robots  
Situational awareness is crucial for autonomous driving in urban environments.  ...  Our approach models both dynamic and geometric properties of the tracked vehicles and estimates them using a single Bayes filter per vehicle.  ...  The authors thank all team members for their hard work. The Stanford Racing Team is indebted to DARPA for creating the Urban Challenge, and for its financial support under the Track A Program.  ... 
doi:10.1007/s10514-009-9115-1 fatcat:62rh6ymstje37eynbssm6b2n3y

Enhancement of Low-cost GNSS Localization in Connected Vehicle Networks Using Rao-Blackwellized Particle Filters [article]

Macheng Shen, Ding Zhao, Jing Sun
2016 arXiv   pre-print
A Rao-Blackwellized particle filter (RBPF) was used to jointly estimate the common biases of the pseudo-ranges and the vehicles positions.  ...  An essential function for automated vehicle technologies is accurate localization.  ...  It will be true for most rural areas and some urban areas.  ... 
arXiv:1606.03736v2 fatcat:jwgv566qmvdhhjimcqa7ityt5u

Cross-view and Cross-domain Underwater Localization based on Optical Aerial and Acoustic Underwater Images [article]

Matheus M. Dos Santos, Giovanni G. De Giacomo, Paulo L. J. Drews-Jr, Silvia S. C. Botelho
2022 arXiv   pre-print
The approach is validated on a real dataset acquired by an underwater vehicle in a marina. The results show an improvement in the localization when compared to the dead reckoning of the vehicle.  ...  The method identifies the correlation between color aerial images and underwater acoustic images to improve the localization of underwater vehicles that travel in partially structured environments such  ...  The Monte Carlo Localization, also known as Particle Filter, is a well-known localization method that can model a multi-modal non-Gaussian probabilistic distribution function by spreading hypotheses in  ... 
arXiv:2202.07817v1 fatcat:yznacxxza5ed5l7cvnedawzolu

Robust Autonomous Navigation and World Representation in Outdoor Environments [chapter]

Favio Masson, Juan Nieto, Jose Guivant, Eduardo Nebot
2007 Mobile Robots: Perception & Navigation  
The SLAM algorithm builds a map while the vehicle explores a new area. The map states will be, in most cases, highly correlated in a local area.  ...  A joint state vector with the vehicle pose and the feature positions is maintained and the dense maps are stored in a separate data structure.  ...  In particular, the Jacobians will be calculated properly. In several cases, the filter could behave in a consistent way.  ... 
doi:10.5772/4778 fatcat:ny3um6yitbffvawmpjaejbf36u

Cooperative relative localization using range measurements without a priori information

Anusna Chakraborty, Kevin M. Brink, Rajnikant Sharma
2020 IEEE Access  
In this paper, we extend the 2-vehicle relative localization work [33] to an N-vehicle cooperative relative localization problem using the concept of MHEKF to initialize an Nvehicle joint filter with  ...  In our recent work, [33] , we have proposed a Multi-Hypothesis Extended Kalman Filter (MHEKF) to estimate relative position and relative heading for two vehicles using range-only measurements.  ... 
doi:10.1109/access.2020.3035470 fatcat:cddadk3t4bgitjm32ygssafmq4
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