Infrastructure-Based Vehicle Localization System for Indoor Parking Lots Using RGB-D Cameras

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.

Non-LOS target localization via millimeter-wave automotive radar

This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.

Study on WSN Localization Algorithm and Simulation Model for Intelligent Transportation System

This paper conducts research on the algorithm to improve the location of Wireless Sensor Network （WSN） in Intelligent Transportation System （ITS）. The localization algorithm introduced an improved RSSI vehicle localization algorithm based on multi-path effect and Gaussian white noise. The localization results under different values of Gaussian white noise and different density of beacon nodes are analyzes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, a simulation model of ITS is developed to test the algorithm based on mixed noise and Kalman filtering algorithm, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application

Localization Of Introduced Vehicle Models

1. General Since early 1980s’, Chinese auto plants have successively introducedheavy truck models, light vehicle models, car models and their manufacturing technologies from abroad (see Table Ⅰand Ⅱ). Here is a summary of LCR of different vehicle models introduced. (1) Cars Presently, the economic scale for car production of Shanghai-VW, FAW-VW,

Assessing Local Government Debt Risks in China： A Case Study of Local Government Financial Vehicles

Strong credit expansion in China after the recent global financial crisis has brought local government financial vehicles （LGFV） into the spotlight. Rapid growth of LGFV has triggered concern about local government indebtedness, banks＇ asset quality and, more broadly, China＇s medium-term financial stability and sovereign risk. This paper constructs a unique frm-level dataset to evaluate the country ＂s local government debt. We find an uneven distribution of LGFV, which are concentrated in the coastal areas, and a deterioration of their debt repaying ability from 2010 to 2012. We use principal component analysis （PCA ） along with multivariate discriminate analysis （MDA） to identify the credit risk of LGFV based on conventional financial variables as well as local governments ＇fiscal status. We also estimate the safe boundaries of debt bearing at the provincial government level. The estimations reveal more severe local government debt risks in the middle-western provinces and higher risks associated with LGFV at the municipal and county levels. Although it is very unlikely that there will be a national debt crisis in China, the high risk of LGFV should be noted and effectively controlled by improving the fiscal transparency of local governments and reforming the fiscal system.

Structural design and performance analysis of China’s Local Government Financing Vehicles

In this paper,we investigate the reasons for the establishment and operation models of China’s Local Government Financing Vehicles(LGFVs).We also outline the current literature on the structural arrangement and the developments of LGFVs.Moreover,we employ the empirical analysis to examine the driv-ing factors of the financial performance of LGFVs.Using 1,042 LGFVs that issued debt securities during the period 2011–2016,we find that the financial performance of LGFVs is positively asso-ciated with local tax revenues,local education levels,local saving deposits,and firm size but negatively associated with local gov-ernment spending and firm leverage ratios.Based on our empir-ical findings,we finally propose policy recommendations for the establishment of relevant investment and financing platforms.