Front vehicle detection based on improved fusion method for lidar and visual image

Author(s):  
Aijuan Li ◽  
Zhenghong Chen ◽  
Donghong Ning ◽  
Xin Huang ◽  
Gang Liu

In order to ensure the detection accuracy, an improved adaptive weighted (IAW) method is proposed in this paper to fuse the data of images and lidar sensors for the vehicle object’s detection. Firstly, the IAW method is proposed in this paper and the first simulation is conducted. The unification of two sensors’ time and space should be completed at first. The traditional adaptive weighted average method (AWA) will amplify the noise in the fusion process, so the data filtered with Kalman Filter (KF) algorithm instead of with the AWA method. The proposed IAW method is compared with the AWA method and the Distributed Weighted fusion KF algorithm in the data fusion simulation to verify the superiority of the proposed algorithm. Secondly, the second simulation is conducted to verify the robustness and accuracy of the IAW algorithm. In the two experimental scenarios of sparse and dense vehicles, the vehicle detection based on image and lidar is completed, respectively. The detection data is correlated and merged through the IAW method, and the results show that the IAW method can correctly associate and fuse the data of the two sensors. Finally, the real vehicle test of object vehicle detection in different environments is carried out. The IAW method, the KF algorithm, and the Distributed Weighted fusion KF algorithm are used to complete the target vehicle detection in the real vehicle, respectively. The advantages of the two sensors can give full play, and the misdetection of the target objects can be reduced with proposed method. It has great potential in the application of object acquisition.

2014 ◽  
Vol 11 (17) ◽  
pp. 4651-4664 ◽  
Author(s):  
A. Budishchev ◽  
Y. Mi ◽  
J. van Huissteden ◽  
L. Belelli-Marchesini ◽  
G. Schaepman-Strub ◽  
...  

Abstract. Most plot-scale methane emission models – of which many have been developed in the recent past – are validated using data collected with the closed-chamber technique. This method, however, suffers from a low spatial representativeness and a poor temporal resolution. Also, during a chamber-flux measurement the air within a chamber is separated from the ambient atmosphere, which negates the influence of wind on emissions. Additionally, some methane models are validated by upscaling fluxes based on the area-weighted averages of modelled fluxes, and by comparing those to the eddy covariance (EC) flux. This technique is rather inaccurate, as the area of upscaling might be different from the EC tower footprint, therefore introducing significant mismatch. In this study, we present an approach to validate plot-scale methane models with EC observations using the footprint-weighted average method. Our results show that the fluxes obtained by the footprint-weighted average method are of the same magnitude as the EC flux. More importantly, the temporal dynamics of the EC flux on a daily timescale are also captured (r2 = 0.7). In contrast, using the area-weighted average method yielded a low (r2 = 0.14) correlation with the EC measurements. This shows that the footprint-weighted average method is preferable when validating methane emission models with EC fluxes for areas with a heterogeneous and irregular vegetation pattern.


Author(s):  
Yanfen Liao ◽  
Changhong Wu ◽  
Xiaoqian Ma

The slagging process is a popular problem in coal-fired power plants because the coal properties deviate from designed condition, at the same time, power plants is enduring a great pressure with the increasing of coal prices. Power coal blending provides an effective way to solve these two problems. In some traditional methods, blended-coal properties were usually treated by the weighted average method which induced the optimization solutions deviating from the actual results. The reason is that different coal property indexes are based on different benchmarks; for example, the sulphur content in coal is based on applied basis, while the slagging properties of blended-coal are calculated on air-dried basis, which was influenced by the contents of moisture and ash in each coal. In order to study the effects, based on the genetic algorithm, a model considering these two factors was build up to optimum the coal-blending scheme. Compared with the traditional weighted average method, the new model got higher slagging property indexes, as means the former method may include some coal blending schemes into the optimizing process, in which the real slagging parameters go beyond constraint standards. Therefore, in the case of coal-blending optimization to prevent slagging in furnace, these two factors are especially important and should be considered carefully to ensure the precise of slagging parameters, so as to obtain the optimum results both in the prices of coals and in slagging property.


2016 ◽  
Vol 21 (2) ◽  
pp. 101 ◽  
Author(s):  
Bima Anjasmoro ◽  
Suharyanto Suharyanto ◽  
Sri Sangkawati

The Feasibility study potential of small dams in Semarang District has identified 8 (eight) urgent potential small dams. These potential dams here to be constructed within 5 (five) years in order to overcome the problem of water shortage in the district. However, the government has limited funding source. It is necessary to select the more urgent small dams to be constructed within the limited budget. The purpose of the research is determining the priority of small dams construction in Semarang District. The method used to determine the priority in this study is cluster analysis, AHP and weighted average method. The criteria used to determine the priority in this study consist of: vegetation in the inundated area, volume of embankment, land acquisition area, useful storage, recervoir life time, water cost/m³, access road to the dam site, land status at abutment and inundated area, construction cost, operation and maintenance cost, irrigation service area and raw water benefit. Based on results of cluster analysis, AHP and weighted average method can be conclude that the priority of small dams construction is 1) Mluweh Small Dam (0.165), 2) Pakis Small Dam (0.142), 3) Lebak Small Dam (0.134), 4) Dadapayam Small Dam (0.128), 5) Gogodalem Small Dam (0.119), 6) Kandangan Small Dam (0.114), 7) Ngrawan Small Dam (0.102) and 8) Jatikurung Small Dam (0.096). Based on analysis of the order of priority of 3 (three) method showed that method is more detail than cluster analysis method and weighted average method, because the result of AHP method is closer to the conditions of each dam in the field.


2011 ◽  
Vol 225-226 ◽  
pp. 1125-1128
Author(s):  
Qiang Yue ◽  
Fan Gao

Regeneration index of depreciated metal products was the index to describe sufficient degree of metal regenerated resources in metal industry. Two approaches for defining the quantities of old aluminum scrap, methods based on aluminum social stock and aluminum products use life, were given. The average use life of aluminum products in China was calculated to be about fifteen years by the weighted average method. Calculating formula for regenerative index of depreciated aluminum products was given, and regenerative index of depreciated aluminum products in the history of China and USA were analyzed.


BMC Genetics ◽  
2005 ◽  
Vol 6 (Suppl 1) ◽  
pp. S67 ◽  
Author(s):  
Kijoung Song ◽  
Mohammed S Orloff ◽  
Qing Lu ◽  
Robert C Elston

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