Lane Marking-Based Vehicle Localization Using Low-Cost GPS and Open Source Map

2015 ◽  
Vol 03 (04) ◽  
pp. 239-251 ◽  
Author(s):  
Wenjie Lu ◽  
Sergio A. Rodríguez F. ◽  
Emmanuel Seignez ◽  
Roger Reynaud
Keyword(s):  
Low Cost ◽  
Autonomous Vehicle ◽  
Estimation Method ◽  
Dynamic Environment ◽  
Kernel Estimation ◽  
Complex Problem ◽  
Urban Environments ◽  
Vehicle Localization ◽  
Open Map ◽  
High Level

Autonomous Vehicle applications and Advanced Driving Assistance Systems (ADAS) need scene understanding processes, allowing high-level systems to carry out decision. For such systems, the localization of a vehicle evolving in a structured dynamic environment constitutes a complex problem of crucial importance. However, the low accuracy of the global positioning system (GPS) system in urban environments makes its localization unreliable for further treatments. The combination of GPS data and additional sensors (WSS, IMU or Camera) can improve the localization precision. More and more, digital maps are also used in this process. Generally, these maps are customized or built for a specific application, asking high-cost to design and upgrade. In this paper, we propose a low-cost localization system based on camera, GPS and open map. Starting from the road marking, detected by a multi-kernel estimation method, a particle filter generates the samples taking advantage of lane markings to predict the most probable trajectory of the vehicle and the low-cost GPS position. Then, the accuracy of the localization is improved using an open map. This process was validated through several scenarios with a public database and our experimental platform.

scholarly journals GPS and Stereovision-Based Visual Odometry: Application to Urban Scene Mapping and Intelligent Vehicle Localization

2011 ◽  
Vol 2011 ◽  
pp. 1-17 ◽  
Author(s):  
Lijun Wei ◽  
Cindy Cappelle ◽  
Yassine Ruichek ◽  
Frédérick Zann
Keyword(s):  
Feature Detection ◽  
Reference Frames ◽  
Estimation Method ◽  
Ground Truth ◽  
Urban Environments ◽  
Relative Depth ◽  
Gps Receiver ◽  
Minimization Method ◽  
Vehicle Localization ◽  
Stereoscopic System

We propose an approach for vehicle localization in dense urban environments using a stereoscopic system and a GPS sensor. Stereoscopic system is used to capture the stereo video flow, to recover the environments, and to estimate the vehicle motion based on feature detection, matching, and triangulation from every image pair. A relative depth constraint is applied to eliminate the tracking couples which are inconsistent with the vehicle ego-motion. Then the optimal rotation and translation between the current and the reference frames are computed using an RANSAC based minimization method. Meanwhile, GPS positions are obtained by an on-board GPS receiver and periodically used to adjust the vehicle orientations and positions estimated by stereovision. The proposed method is tested with two real sequences obtained by a GEM vehicle equipped with a stereoscopic system and a RTK-GPS receiver. The results show that the vision/GPS integrated trajectory can fit the ground truth better than the vision-only method, especially for the vehicle orientation. And vice-versa, the stereovision-based motion estimation method can correct the GPS signal failures (e.g., GPS jumps) due to multipath problem or other noises.

Region of Attraction for a Vehicle Pose Estimator Utilizing Monocular Vision and Lane Marker Maps

2016 ◽  
Author(s):  
Robert D. Leary ◽  
Sean Brennan
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Ground Truth ◽  
Estimation Algorithm ◽  
Lane Detection ◽  
Monocular Vision ◽  
Detection Methods ◽  
Region Of Attraction ◽  
Vehicle Localization

Currently, there is a lack of low-cost, real-time solutions for accurate autonomous vehicle localization. The fusion of a precise a priori map and a forward-facing camera can provide an alternative low-cost method for achieving centimeter-level localization. This paper analyzes the position and orientation bounds, or region of attraction, with which a real-time vehicle pose estimator can localize using monocular vision and a lane marker map. A pose estimation algorithm minimizes the residual pixel-level error between the estimated and detected lane marker features via Gauss-Newton nonlinear least-squares. Simulations of typical road scenes were used as ground truth to ensure the pose estimator will converge to the true vehicle pose. A successful convergence was defined as a pose estimate that fell within 5 cm and 0.25 degrees of the true vehicle pose. The results show that the longitudinal vehicle state is weakly observable with the smallest region of attraction. Estimating the remaining five vehicle states gives repeatable convergence within the prescribed convergence bounds over a relatively large region of attraction, even for the simple lane detection methods used herein. A main contribution of this paper is to demonstrate a repeatable and verifiable method to assess and compare lane-based vehicle localization strategies.

Semi-Direct Monocular Visual-Inertial Odometry Using Point and Line Features for IoV

2022 ◽  
Vol 22 (1) ◽  
pp. 1-23
Author(s):  
Nan Jiang ◽  
Debin Huang ◽  
Jing Chen ◽  
Jie Wen ◽  
Heng Zhang ◽  
...  
Keyword(s):  
Direct Method ◽  
Low Cost ◽  
Dynamic Environment ◽  
Autonomous Driving ◽  
Measurement Unit ◽  
Vehicle Localization ◽  
Intelligent Decision Making ◽  
Line Features ◽  
Point Line ◽  
Weak Texture

The precise measuring of vehicle location has been a critical task in enhancing the autonomous driving in terms of intelligent decision making and safe transportation. Internet of Vehicles ( IoV ) is an important infrastructure in support of autonomous driving, allowing real-time road information exchanging and sharing for localizing vehicles. Global positioning System ( GPS ) is widely used in the traditional IoV system. GPS is unable to meet the key application requirements of autonomous driving due to meter level error and signal deterioration. In this article, we propose a novel solution, named Semi-Direct Monocular Visual-Inertial Odometry using Point and Line Features ( SDMPL-VIO ) for precise vehicle localization. Our SDMPL-VIO model takes advantage of a low-cost Inertial Measurement Unit ( IMU ) and monocular camera, using them as the sensor to acquire the surrounding environmental information. Visual-Inertial Odometry ( VIO ), taking into account both point and line features, is proposed, which is able to deal with both weak texture and dynamic environment. We use a semi-direct method to deal with keyframes and non-keyframes, respectively. Dual sliding window mechanisms can effectively fuse point-line and IMU information. To evaluate our SDMPL-VIO system model, we conduct extensive experiments on both an indoor dataset (i.e., EuRoC) and an outdoor dataset (i.e., KITTI) from the real-world applications, respectively. The experimental results show that the accuracy of SDMPL-VIO proposed by us is better than the mainstream VIO system at present. Especially in the weak texture of the datasets, fast-moving datasets, and other challenging datasets, SDMPL-VIO has a relatively high robustness.

scholarly journals Safety Assessment and Simulation of Autonomous Vehicle in Urban Environments

2021 ◽  
Vol 1140 (1) ◽  
pp. 012032
Author(s):  
Mohsen Malayjerdi ◽  
Bariş Cem Baykara ◽  
Raivo Sell ◽  
Ehsan Malayjerdi
Keyword(s):  
Safety Assessment ◽  
Autonomous Vehicle ◽  
Urban Environments

scholarly journals Hybrid mosquitoes? Evidence from rural Tanzania on how local communities conceptualize and respond to modified mosquitoes as a tool for malaria control

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Marceline F. Finda ◽  
Fredros O. Okumu ◽  
Elihaika Minja ◽  
Rukiyah Njalambaha ◽  
Winfrida Mponzi ◽  
...  
Keyword(s):  
Malaria Control ◽  
Technology Development ◽  
Low Cost ◽  
Public Support ◽  
Community Leaders ◽  
Community Perceptions ◽  
Novel Technologies ◽  
Control Programmes ◽  
High Level ◽  
Interpretive Frames

Abstract Background Different forms of mosquito modifications are being considered as potential high-impact and low-cost tools for future malaria control in Africa. Although still under evaluation, the eventual success of these technologies will require high-level public acceptance. Understanding prevailing community perceptions of mosquito modification is, therefore, crucial for effective design and implementation of these interventions. This study investigated community perceptions regarding genetically-modified mosquitoes (GMMs) and their potential for malaria control in Tanzanian villages where no research or campaign for such technologies has yet been undertaken. Methods A mixed-methods design was used, involving: (i) focus group discussions (FGD) with community leaders to get insights on how they frame and would respond to GMMs, and (ii) structured questionnaires administered to 490 community members to assess awareness, perceptions and support for GMMs for malaria control. Descriptive statistics were used to summarize the findings and thematic content analysis was used to identify key concepts and interpret the findings. Results Nearly all survey respondents were unaware of mosquito modification technologies for malaria control (94.3%), and reported no knowledge of their specific characteristics (97.3%). However, community leaders participating in FGDs offered a set of distinctive interpretive frames to conceptualize interventions relying on GMMs for malaria control. The participants commonly referenced their experiences of cross-breeding for selecting preferred traits in domestic plants and animals. Preferred GMMs attributes included the expected reductions in insecticide use and human labour. Population suppression approaches, requiring as few releases as possible, were favoured. Common concerns included whether the GMMs would look or behave differently than wild mosquitoes, and how the technology would be integrated into current malaria control policies. The participants emphasised the importance and the challenge of educating and engaging communities during the technology development. Conclusions Understanding how communities perceive and interpret novel technologies is crucial to the design and effective implementation of new vector control programmes. This study offers vital clues on how communities with no prior experience of modified mosquitoes might conceptualize or respond to such technologies when deployed in the context of malaria control programmes. Drawing upon existing interpretive frames and locally-resonant analogies when deploying such technologies may provide a basis for more durable public support in the future.

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