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Probabilistic Grid-Based Collision Risk Prediction for Driving Application
[chapter]
2015
Springer Tracts in Advanced Robotics
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In this paper, we propose a new grid-based approach for collision risk prediction, based on the Hybrid-Sampling Bayesian Occupancy Filter framework. ...
This is necessary for both Advanced Driver Assistance Systems and Autonomous Navigation. Most approach for risk estimation propose to detect and track the dynamic objects in the scene. ...
Another alternative to the object-based approaches are the grid-based approaches, like the Bayesian Occupancy Filter [6] , or its extension Hybrid -Sampling Bayesian Occupancy Filter (HSBOF) [7] , which ...
doi:10.1007/978-3-319-23778-7_54
fatcat:xzwgff7pwbavpkhrjmxqc34x2y
Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application
2006
The international journal of robotics research
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This approach is called Bayesian occupancy filtering; it basically combines a four-dimensional occupancy grid representation of the obstacle state space with Bayesian filtering techniques. ...
Most of today's systems use target tracking algorithms based on object models. They work quite well in simple environments such as freeways, where few potential obstacles have to be considered. ...
Bayesian Occupancy Filter Based Collision Avoidance The goal of this section is to show how the BOF can be used for developing a collision avoidance function on an autonomous vehicle. ...
doi:10.1177/0278364906061158
fatcat:almmqpj3bjhjlk5jqvgoc754we
Awareness of Road Scene Participants for Autonomous Driving
[chapter]
2012
Handbook of Intelligent Vehicles
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This approach utilizes geometric object models and relies on non-parametric filters for inference. Finally, the third class is the grid based approach, which starts by constructing a low level grid ...
First is the traditional approach, which includes data segmentation, data association, and filtering using primarily Kalman filters. ...
In DATMO, separate Bayesian filters are used to track the state of each moving object (or cell). ...
doi:10.1007/978-0-85729-085-4_54
fatcat:lrnbnr4q5vbzrd3pausguhbhom
A Review of the Bayesian Occupancy Filter
2017
Sensors
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In recent years, the Bayesian Occupancy Filter (BOF) method has been developed to evaluate occupancy by tessellation of the environment. ...
In addition, we present a study of implemented use cases to provide a practical understanding on the main uses of the BOF and its taxonomy. ...
The approach presented in [4, 8] combines multiple sensors using a grid model and based on the Bayesian principle. ...
doi:10.3390/s17020344
pmid:28208638
pmcid:PMC5336118
fatcat:lqrveyhxwrhkdlxwf452u6bdmy
A review of recent developments in vision-based vehicle detection
2013
2013 IEEE Intelligent Vehicles Symposium (IV)
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We detail advances in vehicle detection, discussing representative works from the monocular and stereo-vision domains. ...
This document provides a review of the past decade's literature in on-road vision-based vehicle detection. ...
In [68] [78] , scene tracking and recursive Bayesian filtering is used to populate the occupancy grid each frame, while objects are detected via clustering. ...
doi:10.1109/ivs.2013.6629487
dblp:conf/ivs/SivaramanT13
fatcat:z2ygschnajaovcf65g5kur4mq4
Titelei/Inhaltsverzeichnis
[chapter]
2016
Bayesian Environment Representation, Prediction, and Criticality Assessment for Driver Assistance Systems
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Finally, the Advanced Driver Assistance System (ADAS) PRORETA 3 is described, which constitutes an integrated approach to collision avoidance and vehicle automation. ...
They are obtained by a novel method for grid mapping and tracking in dynamic environments. ...
of Moving Objects
DBF
Discrete Bayes Filter
DBN
Dynamic Bayesian Network
DBSCAN
Density Based Spatial Clustering
for Applications with Noise
EKF
Extended Kalman Filter
FN
False Negative
FP ...
doi:10.51202/9783186797124-i
fatcat:lfvf7xy4mzgxdgpzgglth7jlzy
Simultaneous Localization, Mapping and Moving Object Tracking
2007
The international journal of robotics research
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Both SLAM and moving object tracking from a moving vehicle in crowded urban areas are daunting tasks. ...
Such an approach is similar to existing SLAM algorithms, but with additional structure to allow for motion modeling of generalized objects. ...
Acknowledgment Thanks to the members of the CMU Navlab group for their excellent work on building and maintaining the Navlab11 vehicles, and for their helps on collecting data. ...
doi:10.1177/0278364907081229
fatcat:37fszo6ic5htfdtisibop4mymm
Moving ground target tracking in urban terrain using air/ground vehicles
2010
2010 IEEE Globecom Workshops
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Results show the platform can be further used to test more advanced tracking algorithms like the proposed tracking framework. ...
In this paper, we present a framework for tracking a moving target in urban environments using UAVs in cooperation with UGVs. ...
The dynamic occupancy grid approach utilizes Bayesian filtering to implement approximate posterior estimation for each grid cell. Bayesian filtering consists of two phases: prediction and update. ...
doi:10.1109/glocomw.2010.5700254
fatcat:hxytfdq7vba2dj46jhb75wdusq
A Generic Architecture for Dynamic Outdoor Environment
2011
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
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In this paper, we present a generic architecture for perception of an intelligent vehicle in dynamic outdoor environment. ...
This architecture is composed of two levels: a first level dedicated to real-time local simultaneous localization and mapping (SLAM) and a second one is dedicated to detection and tracking of moving objects ...
Regarding tracking techniques, Bayesian filters [2] are generally used. ...
doi:10.1109/ictai.2011.93
dblp:conf/ictai/AycardVBF11
fatcat:cihi2wzg5ncsjasbkzlqbckcb4
Recognize Moving Objects Around an Autonomous Vehicle Considering a Deep-learning Detector Model and Dynamic Bayesian Occupancy
2020
2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)
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scenery. • Fusion of an object detection method with a Bayesian filter framework at a later stage for recognize moving objects in the environment. ...
Moreover, we use a Bayesian occupancy framework with a Highly-parallelized design to obtain the occupancygrid estimations.We validate our approach using experimental results with real-world data on urban ...
In this paper, we propose a new approach to recognize moving objects around an autonomous vehicle by fusing preprocessed information from two sensors. ...
doi:10.1109/icarcv50220.2020.9305328
fatcat:r7hd3awuw5dc3bfq6w27fba5kq
Experiments in Vision-Laser Fusion Using the Bayesian Occupancy Filter
[chapter]
2014
Springer Tracts in Advanced Robotics
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The BOF, an adaptation of Bayesian filtering to the occupancy grid framework, offers several advantages. ...
Stereo vision and laser sensors are both regularly used to create occupancy grids, but unlike other works, this information is fused using the Bayesian Occupancy Filter (BOF) [7] . ...
doi:10.1007/978-3-642-28572-1_62
fatcat:clc66aulnnez7c3elakpugfqzm
Efficient Techniques for Dynamic Vehicle Detection
[chapter]
2009
Springer Tracts in Advanced Robotics
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The algorithm provides reliable detection of moving vehicles from a high-speed moving platform using laser range finders. ...
We present the notion of motion evidence, which allows us to overcome the low signal-to-noise ratio that arises during rapid detection of moving vehicles in noisy urban environments. ...
The Stanford Racing Team is indebted to DARPA for creating the UGC, and for its financial support under the Track A Program. Further, Stanford University thanks its various sponsors. ...
doi:10.1007/978-3-642-00196-3_10
fatcat:i4vxkwq5qfeatbax2ruvp6i3da
Results of a precrash application based on Laserscanner and short range radars
2008
2008 IEEE Intelligent Vehicles Symposium
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In this paper, we present a vehicle safety application based on data gathered by a laser scanner and two short range radars that recognizes unavoidable collisions with stationary objects before they take ...
A comprehensive experimental evaluation based on relevant crash and non-crash scenarios is presented. ...
Module 2 is based on simultaneous localization and mapping techniques (SLAM) together with the detection and tracking of moving objects. The environment is modeled using an Occupancy Grid. ...
doi:10.1109/ivs.2008.4621264
fatcat:v7yt65fywjh7dnzm3gccze5hiy
Simultaneous Localization and Mapping
[chapter]
2008
Springer Handbook of Robotics
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The probabilistic approach to solve the whole problem has been implemented with the Navlab11 vehicle. ...
The simultaneous localization and mapping (SLAM) with detection and tracking of moving objects (DATMO) problem is not only to solve the SLAM problem in dynamic environments but also to detect and track ...
Fig. 2 shows the results of SLAM with moving vehicle detection by our motion-based approach. ...
doi:10.1007/978-3-540-30301-5_38
fatcat:goyxpk4nwbahte7cmximl2dtqe
Traffic Model Evaluation of Ad Hoc Target Tracking Algorithms
2002
The international journal of high performance computing applications
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Experimental evaluation is performed for alternative target-tracking algorithms using the framework. Evaluation uses discrete cellular automata models. ...
In this paper we describe a self-organizing framework for distributed target tracking built on ad hoc publish-subscribe data routing techniques. ...
ACKNOWLEDGEMENTS Efforts sponsored by the Defense Advance Research Projects Agency (DARPA) and Air Force Research Laboratory, Air Force Materiel Command, USAF, under agreement number F30602-99-2-0520 ( ...
doi:10.1177/10943420020160030301
fatcat:6puzo77f4vckhcxapkvao5japi
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