Accurate vehicle localization is a key technology for autonomous driving tasks in indoor parking lots,such as automated valet parking.Additionally,infrastructure-based cooperative driving systems have become a means t...Accurate vehicle localization is a key technology for autonomous driving tasks in indoor parking lots,such as automated valet parking.Additionally,infrastructure-based cooperative driving systems have become a means to realizing intelligent driving.In this paper,we propose a novel and practical vehicle localization system using infrastructure-based RGB-D cameras for indoor parking lots.In the proposed system,we design a depth data preprocessing method with both simplicity and efficiency to reduce the computational burden resulting from a large amount of data.Meanwhile,the hardware synchronization for all cameras in the sensor network is not implemented owing to the disadvantage that it is extremely cumbersome and would significantly reduce the scalability of our system in mass deployments.Hence,to address the problem of data distortion accompanying vehicle motion,we propose a vehicle localization method by performing template point cloud registration in distributed depth data.Finally,a complete hardware system was built to verify the feasibility of our solution in a real-world environment.Experiments in an indoor parking lot demonstrated the effectiveness and accuracy of the proposed vehicle localization system,with a maximum root mean squared error of 5 cm at 15Hz compared with the ground truth.展开更多
Human beings have been kept pursuing of higher ef-ficiency and better safety to move people and things around since thousands of years ago.In modern soci-ety,vehicles are therefore invented and utilized to boost the s...Human beings have been kept pursuing of higher ef-ficiency and better safety to move people and things around since thousands of years ago.In modern soci-ety,vehicles are therefore invented and utilized to boost the speed and enhance the safety.In recent years,rapid development of information technology has brought hu-man into a new era of connected world.Internet and smartphones have made it extremely easy to get ac-cess to anyone from anywhere any time.In this back-ground,intelligent connected vehicles(ICVs)have been proposed and investigated.展开更多
High-definition(HD)maps are key components that provide rich topologic and semantic information for decision-making in vehicle autonomous driving systems.A complete ground orthophoto is usually used as the base image ...High-definition(HD)maps are key components that provide rich topologic and semantic information for decision-making in vehicle autonomous driving systems.A complete ground orthophoto is usually used as the base image to construct the HD map.The ground orthophoto is obtained through inverse perspective transformation and image mosaicing.During the image mosaicing,multiple consecutive orthophotos are stitched together using pose information and image registration.In this study,wavelet transform is introduced to the image mosaicing process to alleviate the information loss caused by image overlapping.In the orthophoto wavelet transform,high-frequency and low-frequency components are fused using different strategies to form a complete base image with clearer local details.Experimental results show that the accuracy of the orthophotos generated using this method is improved.展开更多
基金the National Natural Science Foundation of China(No.62173228)。
文摘Accurate vehicle localization is a key technology for autonomous driving tasks in indoor parking lots,such as automated valet parking.Additionally,infrastructure-based cooperative driving systems have become a means to realizing intelligent driving.In this paper,we propose a novel and practical vehicle localization system using infrastructure-based RGB-D cameras for indoor parking lots.In the proposed system,we design a depth data preprocessing method with both simplicity and efficiency to reduce the computational burden resulting from a large amount of data.Meanwhile,the hardware synchronization for all cameras in the sensor network is not implemented owing to the disadvantage that it is extremely cumbersome and would significantly reduce the scalability of our system in mass deployments.Hence,to address the problem of data distortion accompanying vehicle motion,we propose a vehicle localization method by performing template point cloud registration in distributed depth data.Finally,a complete hardware system was built to verify the feasibility of our solution in a real-world environment.Experiments in an indoor parking lot demonstrated the effectiveness and accuracy of the proposed vehicle localization system,with a maximum root mean squared error of 5 cm at 15Hz compared with the ground truth.
文摘Human beings have been kept pursuing of higher ef-ficiency and better safety to move people and things around since thousands of years ago.In modern soci-ety,vehicles are therefore invented and utilized to boost the speed and enhance the safety.In recent years,rapid development of information technology has brought hu-man into a new era of connected world.Internet and smartphones have made it extremely easy to get ac-cess to anyone from anywhere any time.In this back-ground,intelligent connected vehicles(ICVs)have been proposed and investigated.
基金the National Natural Science Foundation of China(No.U1764264/61873165)the Shanghai Automotive Industry Science and Technology Development Foundation(No.1807)the Guangxi Key Laboratory of Automobile Components and Vehicle Technology Research Project(No.2020GKLACVTKF02)。
文摘High-definition(HD)maps are key components that provide rich topologic and semantic information for decision-making in vehicle autonomous driving systems.A complete ground orthophoto is usually used as the base image to construct the HD map.The ground orthophoto is obtained through inverse perspective transformation and image mosaicing.During the image mosaicing,multiple consecutive orthophotos are stitched together using pose information and image registration.In this study,wavelet transform is introduced to the image mosaicing process to alleviate the information loss caused by image overlapping.In the orthophoto wavelet transform,high-frequency and low-frequency components are fused using different strategies to form a complete base image with clearer local details.Experimental results show that the accuracy of the orthophotos generated using this method is improved.
