ABSTRACT

In this Fuzzy Inference System based study, a model is developed which can present a real-time risk assessment model to the drivers. The model includes parameters car speed, accident frequency, weather conditions, tire tread depth and fatigue. In order to evaluate the performance of the model, the road between Zonguldak and Düzce is chosen, which has a high accident incidence and can cause anxiety on the drivers. The statistical results of the real and artificial data sets that were created to demonstrate the model performance were found as follows; Mean Square Error is 5.07551 for real and 6.43029 for artificial data set, Mean Absolute Error is 1.8 and 1.69864, Correlation Coefficient is 95.594% and 97.412%, and Determination Coefficient is 84.98% and 93.6% respectively. Investigation of the actual accidents reveals that the accident risk ratios in these accidents were between 60% and 80% according to the determined parameters.

摘要

在这项基于模糊推理系统的研究中，开发了一种模型，可以向驾驶员提供实时风险评估模型。该模型包括车速、事故频率、天气条件、轮胎胎纹深度和疲劳等参数。为了评估模型的性能，选择了 Zonguldak 和 Düzce 之间的道路，该道路事故发生率高，会引起驾驶员的焦虑。为证明模型性能而创建的真实和人工数据集的统计结果如下：真实数据集的均方误差为 5.07551，人工数据集为 6.43029，平均绝对误差为 1.8 和 1.69864，相关系数分别为 95.594% 和 97.412%，确定系数分别为 84.98% 和 93.6%。