Teaching electronics to first-year non-electrical engineering students

Teaching electronics is not only for electrical and electronics students but also for mechanical, aerospace, engineering design, civil and engineering mathematics programmes, which are likely to have electronics units as part of their curriculum. To teach electronics for these non-electronic programmes is very challenging in many aspects. First, the electronics unit has to satisfy the learning outcomes for each programme. Second, the student’s motivation is normally very low since electronics is not the career the students would like to pursue. Third, the timetabling can be an issue when a large number of students are enrolled; for instance, at the University of Bristol, over 340 students are registered for the electronics unit. Due to this large number and the capacity of the electrical laboratory, students will have laboratory experiments timetabled in different weeks and some may have laboratory experiments before the lectures are covered. Finally, a method of assessing this large number of students has to be put into place. In this paper, the content of the unit including the laboratory experiments, the methods of course delivery and the assessment methods are justified. Also, since students learn differently and have a variety of motivations, a combination of teaching methods has to be found to satisfy more students and improve the learning outcomes. </jats:p

A Novel Disparity Transformation Algorithm for Road Segmentation

The disparity information provided by stereo cameras has enabled advanced driver assistance systems to estimate road area more accurately and effectively. In this paper, a novel disparity transformation algorithm is proposed to extract road areas from dense disparity maps by making the disparity value of the road pixels become similar. The transformation is achieved using two parameters: roll angle and fitted disparity value with respect to each row. To achieve a better processing efficiency, golden section search and dynamic programming are utilised to estimate the roll angle and the fitted disparity value, respectively. By performing a rotation around the estimated roll angle, the disparity distribution of each row becomes very compact. This further improves the accuracy of the road model estimation, as demonstrated by the various experimental results in this paper. Finally, the Otsu's thresholding method is applied to the transformed disparity map and the roads can be accurately segmented at pixel level.Comment: 16 pages, 8 figure

Real-Time Stereo Vision-Based Lane Detection System

The detection of multiple curved lane markings on a non-flat road surface is still a challenging task for automotive applications. To make an improvement, the depth information can be used to greatly enhance the robustness of the lane detection systems. The proposed system in this paper is developed from our previous work where the dense vanishing point Vp is estimated globally to assist the detection of multiple curved lane markings. However, the outliers in the optimal solution may severely affect the accuracy of the least squares fitting when estimating Vp. Therefore, in this paper we use Random Sample Consensus to update the inliers and outliers iteratively until the fraction of the number of inliers versus the total number exceeds our pre-set threshold. This significantly helps the system to overcome some suddenly changing conditions. Furthermore, we propose a novel lane position validation approach which provides a piecewise weight based on Vp and the gradient to reduce the gradient magnitude of the non-lane candidates. Then, we compute the energy of each possible solution and select all satisfying lane positions for visualisation. The proposed system is implemented on a heterogeneous system which consists of an Intel Core i7-4720HQ CPU and a NVIDIA GTX 970M GPU. A processing speed of 143 fps has been achieved, which is over 38 times faster than our previous work. Also, in order to evaluate the detection precision, we tested 2495 frames with 5361 lanes from the KITTI database (1637 lanes more than our previous experiment). It is shown that the overall successful detection rate is improved from 98.7% to 99.5%.Comment: 24 pages, 10 figure