Vehicle Localization Method for Lateral Position within Lane Based on Vision and HD Map

2021 ◽  
Vol 20 (5) ◽  
pp. 186-201
Author(s):  
Rinara Woo ◽  
◽  
Dae-Wha Seo
Keyword(s):  
Lateral Position ◽  
Vehicle Localization ◽  
Localization Method ◽  
Lane Based

Multi-View and Multi-Scale Localization for Intelligent Vehicles in Underground Parking Lots

2019 ◽  
Vol 2673 (11) ◽  
pp. 791-800
Author(s):  
Gang Huang ◽  
Zhaozheng Hu ◽  
Mengchao Mu ◽  
Xianglong Wang ◽  
Fan Zhang
Keyword(s):  
Intelligent Vehicles ◽  
Visual Localization ◽  
Fingerprint Matching ◽  
Vehicle Localization ◽  
Localization Method ◽  
Parking Lots ◽  
Single View ◽  
Multi Scale ◽  
Parking Lot ◽  
Wifi Localization

Because of limited access to global positioning system (GPS) signals, accurate and reliable localization for intelligent vehicles in underground parking lots is still an open problem. This paper proposes a multi-view and multi-scale localization method aiming at solving this problem. The proposed method is divided into an offline mapping stage and an online localization stage. In the mapping stage, the offline map is generated by fusing 3-D information, WiFi features, visual features, and trajectory from visual odometry (VO). In the localization stage, WiFi fingerprint matching is exploited for coarse localization. Based on the result of coarse localization, multi-view localization is exploited for image-level localization. Finally, metric localization is exploited to refine the localization results. By applying this multi-scale strategy, it is possible to fuse WiFi localization and visual localization and reduce the image matching and error rate to a great extent. Because of exploiting more information, multi-view localization is more robust and accurate than single-view localization. The method is tested in a 2,000 m2 underground parking lot. The result demonstrates that this method can achieve sub-meter localization on average. The proposed localization method can be a supplement to the existing intelligent vehicle localization techniques.

Parametric study of microscopic two-dimensional traffic flow models: A literature review

2018 ◽  
Vol 45 (11) ◽  
pp. 909-921 ◽  
Author(s):  
Geetimukta Mahapatra ◽  
Akhilesh Kumar Maurya ◽  
Partha Chakroborty
Keyword(s):  
Simulation Models ◽  
Lateral Position ◽  
Two Dimensional ◽  
Mixed Traffic ◽  
Lane Changing ◽  
The Real ◽  
Flow Models ◽  
Traffic Stream ◽  
Traffic Flow Models ◽  
Lane Based

Indian traffic is highly heterogeneous consisting of all-inclusive vehicle characteristics, occupying any lateral position over the entire road width which results in vehicles continuous interaction with the neighbouring vehicles (in both longitudinal and lateral directions), indicating two-dimensional (2D) traffic manoeuvre, opposite to the traditional one-dimensional (1D) interaction of vehicles in lane based traffic. Certain modifications were made in the existing 1D models to describe the overtaking and lane changing manoeuvre of the mixed traffic stream. However, the continuous lateral manoeuvre of the no-lane based mixed traffic cannot be described by these parameters. This paper initially provides a brief review of different 2D behavioural models, which describe the longitudinal and lateral movements simultaneously. Also, the various existing commercially available traffic micro-simulation frameworks developed for representing the real traffic are reviewed. Different microscopic traffic parameters used in the existing simulation models to mimic the real-world traffic are identified, which can be used to understand the 2D traffic stream.

scholarly journals Autonomous Underwater Vehicle Localization Using Sound Measurements of Passing Ships

2020 ◽  
Vol 10 (24) ◽  
pp. 9139
Author(s):  
Jonghoek Kim
Keyword(s):  
Autonomous Underwater Vehicle ◽  
A Priori ◽  
Underwater Vehicle ◽  
Vehicle Localization ◽  
Inertial Measurement ◽  
Localization Method ◽  
Long Time ◽  
Measurement Units ◽  
Source Level

This paper introduces the localization method of an Autonomous Underwater Vehicle (AUV) in environments (such as harbors or ports) where there can be passing ships near the AUV. It is assumed that the AUV can access the trajectory and approximate source level of a passing ship, while identifying the ship by processing the ship’s sound. This paper considers an AUV which can localize itself by integrating propeller and Inertial Measurement Units (IMU). Suppose that the AUV has been moving in underwater environments for a long time, under the IMU-only localization. To fix long-term drift in the IMU-only localization, we propose that the AUV localization uses sound measurements of passing ships whose trajectories are known a priori. As far as we know, this AUV localization method is novel in using sound measurements of passing ships of which the trajectories are known a priori. The performance of the proposed localization method is verified utilizing MATLAB simulations. The simulation results show significant estimation improvements, compared to IMU-only localization. Moreover, using measurements from multiple ships gives better estimation results, compared to the case where the measurement of a single ship is used.

Lane-Based Network for Flow Analysis and Inventory Management of Transportation Networks

2005 ◽  
Vol 1935 (1) ◽  
pp. 101-110 ◽  
Author(s):  
Suphawut Malaikrisanachalee ◽  
Teresa M. Adams
Keyword(s):  
Inventory Management ◽  
Data Model ◽  
Flow Analysis ◽  
Lateral Position ◽  
Management Decision ◽  
Practical Implementation ◽  
Department Of Transportation ◽  
Lateral Connectivity ◽  
Management Decision Making ◽  
Lane Based

The widely accepted link–node centerline network model inhibits lane-based traffic analysis and inventory management, specifically the ability to represent the availability of lanes, individual lane properties, connectivity among parallel lanes and at turns, and lane movement restrictions. A lane-based network overcomes the limitations by maintaining lanes as independent topological objects and thus supports data management, decision making, and network analysis at the lane level. The data model for a lane-based network uses a directed graph approach in which a set of unidirectional lanes and nodes is used to model traffic flow connectivity. The model manages the continuous lateral connectivity between parallel lanes by specifying the relative lateral position of the lanes on their parent roadways. This approach provides an efficient way to maintain lane topology and eliminates the requirement of turntables. This paper presents the model along with guidelines for lane-based inventory management and strategies for discretizing continuous lateral connectivity between parallel lanes to enable the use of existing routing algorithms (e.g., Dijkstra's). Finally, the paper presents a practical implementation built on the linear location referencing system of a state department of transportation.

scholarly journals In-Lane Localization and Ego-Lane Identification Method Based on Highway Lane Endpoints

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Kyoungtaek Choi ◽  
Jae Kyu Suhr ◽  
Ho Gi Jung
Keyword(s):  
Low Cost ◽  
Global Navigation Satellite Systems ◽  
Average Error ◽  
Vehicle Localization ◽  
Localization Method ◽  
Satellite Systems ◽  
Identification Method ◽  
Road Sign ◽  
Lane Width ◽  
Global Navigation Satellite

The low-cost global navigation satellite systems combined with an inertial navigation system (GNSS/INS) used most frequently for vehicle localization show errors up to 10 m, approximately, even in open-sky environments such as highways. To reduce this error on highways, this paper proposes a localization method based on lane endpoints. Since a lane endpoint frequently appears on a road and can be detected in close proximity even by a low-cost monocular camera, it is a very useful landmark for precise localization. However, the lane width is generally less than 3.5 m, and the localization error from the GNSS is about 10 m. Therefore, if an ego-lane is not identified, the lane endpoints detected in an ego-lane can be falsely corresponded to the lane endpoints in the other lane of a map. This paper proposes an in-lane localization method that uses lane endpoints, the relation between a camera and a road, and the estimated vehicle’s orientation from a map. In addition, this paper proposes an ego-lane identification method that generates a hypothesis about an ego vehicle position per lane by using the proposed in-lane localization method and verifies each hypothesis by the projection of lane endpoints and an additional landmark such as a road sign. The average error of the proposed in-lane localization method is 0.248 m on highways. The success rate of the proposed ego-lane identification method is 99.28% by one trial and reaches 100% by fusing the results.

Stereo Vision Based Localization Method for Intelligent Vehicle

2013 ◽  
Vol 694-697 ◽  
pp. 1931-1936
Author(s):  
Feng Ping Cao ◽  
Rong Ben Wang ◽  
Liang Xiu Zhang
Keyword(s):  
Stereo Vision ◽  
Probability Model ◽  
Three Dimensional ◽  
Dead Reckoning ◽  
Intelligent Vehicle ◽  
Localization Algorithm ◽  
Vehicle Localization ◽  
Localization Method ◽  
Localization And Mapping ◽  
Slam Algorithm

In order to overcome the accumulated error in traditional localization methods for intelligent vehicle such as dead reckoning and visual odometry, a simultaneous localization and mapping(SLAM) algorithm based on stereo vision was presented in the paper. Firstly, the interrelated elements in the localization method were defined, and the probability model for intelligent vehicle localization was proposed, then the motion and observation model were established, and the detailed implementation of the introduced localization algorithm was given. Finally, an experiment was designed to confirm the effectiveness of the proposed method. Experimental results indicate that the algorithm can realize three-dimensional motion estimation of intelligent vehicle and can improve the positioning precision effectively.

scholarly journals An Underactuated Vehicle Localization Method in Marine Environments

2018 ◽  
Author(s):  
Tauhidul Alam ◽  
Gregory Murad Reis ◽  
Leonardo Bobadilla ◽  
Ryan N. Smith
Keyword(s):  
Marine Environments ◽  
Vehicle Localization ◽  
Localization Method

A simple way for producing holographic filters suitable for image improvement

1978 ◽  
Vol 36 (1) ◽  
pp. 226-227
Author(s):  
K.-H. Herrmann ◽  
E. Reuber ◽  
P. Schiske
Keyword(s):  
Transfer Functions ◽  
Diffraction Order ◽  
Lateral Position ◽  
Simple Method ◽  
Spatial Frequencies ◽  
Resolution Electron ◽  
Wiener Filters ◽  
Image Improvement ◽  
Optical Reconstruction ◽  
Set Up

Aposteriori deblurring of high resolution electron micrographs of weak phase objects can be performed by holographic filters [1,2] which are arranged in the Fourier domain of a light-optical reconstruction set-up. According to the diffraction efficiency and the lateral position of the grating structure, the filters permit adjustment of the amplitudes and phases of the spatial frequencies in the image which is obtained in the first diffraction order.In the case of bright field imaging with axial illumination, the Contrast Transfer Functions (CTF) are oscillating, but real. For different imageforming conditions and several signal-to-noise ratios an extensive set of Wiener-filters should be available. A simple method of producing such filters by only photographic and mechanical means will be described here.A transparent master grating with 6.25 lines/mm and 160 mm diameter was produced by a high precision computer plotter. It is photographed through a rotating mask, plotted by a standard plotter.

Differentiating Processes in Object Completion Using a Dot Localization Method

2014 ◽  
Author(s):  
Susan Carrigan ◽  
Evan Palmer ◽  
Philip J. Kellman
Keyword(s):  
Localization Method
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