Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL, United States.
Accid Anal Prev. 2023 Nov;192:107263. doi: 10.1016/j.aap.2023.107263. Epub 2023 Aug 11.
This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway segment in a specific context. Based on the reviewed literature, this is the first study to investigate the relationship between target speed and crash frequency. Hence, big data including probe-vehicle data, traffic characteristics, geometric features, and land use attributes were utilized to develop crash prediction models. The main contributions of this research are to quantify the impacts of target speed on traffic safety considering context categories and to conclude the potential recommendations to lower different types of crashes. The 85th percentile speed was calculated and utilized in the developed models. Three crash prediction models were developed for pedestrian, bike, and speeding-related crashes. They were used in the analysis to quantify the impact of adopting target speed on different crash types. The results showed a significant reduction in the three crash types when using the target speed. Most of the improvements took place in three context categories: C3C: Suburban Commercial Segments, C3R: Suburban Residential Segments, and C4: Urban General Segments. Hence, this research recommends adopting target speed specifically in urban and suburban areas. Further, it suggests considering some measures to lower vulnerable road users' and speeding-related crashes. Following the recommendations of this research would help to reduce different types of crash frequency, hence, improving the mobility and safety for all users in different context classifications.
本研究旨在调查采用目标速度概念对不同类型的碰撞的影响，包括行人、自行车和与超速相关的碰撞。目标速度是车辆在特定环境下在道路段上应运行的最高速度。基于已审查的文献，这是第一项研究目标速度与碰撞频率之间关系的研究。因此，利用大数据包括探针车数据、交通特征、几何特征和土地利用属性来开发碰撞预测模型。本研究的主要贡献是量化目标速度对交通安全的影响，同时考虑上下文类别，并得出降低不同类型碰撞的潜在建议。计算并在开发的模型中使用了 85 百分位速度。为行人、自行车和与超速相关的碰撞开发了三个碰撞预测模型。它们用于分析中，以量化采用目标速度对不同碰撞类型的影响。结果表明，采用目标速度时，三种碰撞类型的数量显著减少。大多数改进发生在三个上下文类别中：C3C：郊区商业路段、C3R：郊区住宅路段和 C4：城市一般路段。因此，本研究建议在城市和郊区采用目标速度。此外，建议考虑一些措施来降低弱势道路使用者和与超速相关的碰撞。遵循本研究的建议将有助于降低不同类型的碰撞频率，从而提高不同上下文分类下所有用户的机动性和安全性。
