With the development of technology in the world, vehicles that reach high speeds are produced. In addition, with the increase of road width and quality, faster and more comfortable transportation can be provided. These developments also increase the speed violation rates of road vehicles. Drivers who violate speed limits can endanger both their own lives and the lives of others. Speed violations, of especially heavy vehicles, involve much greater risks than that of light vehicles. Heavy vehicles can cause more serious losses of lives and property in accidents, compared to the ones caused by light vehicles, as they can carry much more freight or passengers than light vehicles. In this study, data regarding the speed violations committed by heavy vehicles in Turkey, were used. Speed violations were divided into 10 classes according to the intensity of speed violation rates. After this process, all provinces were classified according to support vector machines (SVM), naive bayes (NB) and k-nearest neighbors (KNN) algorithms. When the accuracy values and error scales of all three algorithms are examined, it has been determined that the algorithm that gives the most accurate results is the NB algorithm. Based on the classification of this algorithm, speed violation density maps of types of heavy vehicles in Turkey were created by using spatial analysis. According to the density maps, the provinces with the highest speed violations were identified. In the results, it was determined that the rate of heavy vehicle speed violation was highest in the cities such as Erzurum, Konya, and Muğla. Later, these cities were examined in terms of heavy vehicle mobility. At the end of this study, measures were proposed to reduce these violations in cities where speeding violations are intense. Material and moral damages can be prevented, to a great extent, with the implementation of recommendations of policymakers which can reduce speed violations.

随着世界技术的发展，产生了达到高速的车辆。另外，随着道路宽度和质量的增加，可以提供更快和更舒适的运输。这些发展也增加了道路车辆的速度违规率。违反速度限制的驾驶员会危害自己和他人的生命。与轻型车辆相比，特别是重型车辆的超速行驶所带来的风险要大得多。与轻型车辆相比，重型车辆可能在事故中造成更严重的人员伤亡和财产损失，因为与轻型车辆相比，重型车辆可运载更多的货物或乘客。在这项研究中，使用了有关土耳其重型车辆违反速度的数据。根据速度违规率的高低，将速度违规分为10个类别。在此过程之后，根据支持向量机（SVM），朴素贝叶斯（NB）和k近邻（KNN）算法对所有省份进行了分类。当检查所有三种算法的精度值和误差标度时，已确定给出最准确结果的算法是NB算法。基于该算法的分类，通过空间分析创建了土耳其重型车辆类型的速度违规密度图。根据密度图，确定了速度违规最高的省。结果表明，在埃尔祖鲁姆，科尼亚和穆拉等城市，重型车违章率最高。之后，对这些城市进行了重型车辆机动性检查。在本研究结束时，提出了减少在超速行驶的城市中减少此类违规行为的措施。通过执行决策者的建议，可以在很大程度上避免物质和精神上的损失，这些建议可以减少对速度的违反。