A method of extracting information in estimating heading angle of vision system is presented. Integration of grey-level cooccurrence matrix (GLCM) in an area of interest selection is carried out to choose a suitable region that is feasible for optical flow generation. The selected area is employed for optical flow generation by using Horn-Schunck method. From the generated optical flow, heading angle is estimated and enhanced via moving median filter (MMF). In order to ascertain the effectiveness of GLCM, we compared the result with a different estimation method of optical flow which is generated directly from untouched greyscale images. The performance of GLCM is compared to the true heading, and the error is evaluated through mean absolute deviation (MAE). The result ensured that GLCM can improve the estimation result of the heading angle of vision system significantly.
A pilot study was done to evaluate several road safety issues in Malaysia that arerelated to heavy transportation. The project consisted of survey, analyticalcalculations, and computer simulations. The survey was conducted to investigate the use of current active safety features like the warning signs, which include lights, light reflective stickers, and the color of canvas used on heavy vehicles. There were 55 responses collected that showed visibility of trucks was a problem in the dark.Fortunately, light reflective stickers could be an aid to passively illuminate the heavy vehiclesand this has become lawin Malaysia.Another issue is the slow speed like 40km/h commonly maintained by heavy vehicles when climbing up hills with heavy load, whichisa hazard since being too slow may cause a more severe rear-end collision damage. Additionally, computer impact analyses were also done by using ABAQUS, where severalrear-end collisions betweena car and a heavy vehicle were studied. Hence, aconclusion can be made that the slower the speed of a heavy vehicle, the higher the impactexperienced by the car colliding from behind the truck.It is recommended that a longtrailertruckhas about 310kW of enginepower to pull a maximum load of 30,000 kg. Trucks are also suggested to maintain at least 60 km/h speedduring hill climbing with a much lower load.
This paper presents a technique on how to estimate heading direction of a moving vision system such as mobile robot. The heading direction is represented by estimation angle which is generated by optical flow vectors threshold technique (OFVTT). The utilizations of optical flow field generated based on Horn-Schunck and Lucas-Kanade methods are essential in order to compute the threshold value. The performance of the proposed technique was determined through percentage of root mean square error (RMSE). Based on our experimental results, it can be ascertained that combination of Horn-Schunck method together with OFVTT shows the best performance in assisting the heading direction estimation of a moving vision system.
This paper presents a technique of visual feedback system application to interpret heading direction which can be adapted to a moving system such as walking mobile robot. An optical flow is used to extract information obtained from generation of images sequence from the visual feedback system. The generation of optical flow is done by differential based method and the heading direction is represented by angle estimation. The technique was tested in two conditions in which a situation of a static camera with moving object and in a situation where moving camera with static environment. The efficiency of the visual feedback system is evaluated using root mean square error (RMSE) in order to determine the performance of proposed method in angle representation.
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