School of Civil Engineering, Chongqing Jiaotong University, Chongqing Rail Transit (Group) Co., Ltd, Chongqing, China.
State Key Laboratory of Mountain Bridge and Tunnel Engineering, School of Civil Engineering, Chongqing Jiaotong University, Chongqing, China.
Traffic Inj Prev. 2022;23(7):410-415. doi: 10.1080/15389588.2022.2087874. Epub 2022 Jun 24.
Operating speeds on roads are critical indicators for evaluating traffic safety. Currently available research on the operating speed's prediction focuses on open roads and highways. Insufficient attention has been paid, so far, to tunnels, which form bottlenecks on expressways. The present research aims to establish an operating speed prediction model for tunnels and analyze the influence of their geometric parameters on the operating speeds of vehicles.
We consider the speed of vehicles collected through field measurements in the portals and lay-bys of six superlong tunnels (length greater than 3000 ). Using linear regression, a prediction model for the speed in an expressway superlong tunnel is obtained considering tunnel's geometric parameters. The influence of various parameters on the operating speed are analyzed through comparisons with existing research findings.
We establish the first operating speed prediction model for tunnels considering geometric parameters and find that the vehicle type is the most important parameter affecting the operating speed. Other important parameters include the preceding curve length up to speed observation point (), preceding tangent length () and preceding tangent length up to speed observation point ().
The influence of geometric parameters on vehicle operating speed in super long tunnels differs from that observed in non-tunnel roadways. The effects of the preceding or subsequent curve radius ( or ) of the tangent section, curvature (), and curve degree () are not important in this case. Furthermore, we find that the influence of the posted speed limit () is closely related to the driving scene and safety awareness of drivers. These findings can improve the design and joint evaluation of tunnel geometric parameters and traffic safety.
道路运行速度是评价交通安全的重要指标。目前关于运行速度预测的研究主要集中在开放道路和高速公路上,而对于高速公路上的瓶颈——隧道,还没有得到足够的关注。本研究旨在建立隧道运行速度预测模型,并分析隧道几何参数对车辆运行速度的影响。
我们考虑了在六个超长隧道(长度大于 3000 米)的入口和停车带通过现场测量收集的车辆速度。使用线性回归,考虑隧道几何参数,获得了高速公路超长隧道速度的预测模型。通过与现有研究结果的比较,分析了各种参数对运行速度的影响。
我们建立了第一个考虑几何参数的隧道运行速度预测模型,发现车型是影响运行速度的最重要参数。其他重要参数包括速度观测点前的曲线长度()、前切线长度()和速度观测点前的切线长度()。
与非隧道道路相比,几何参数对超长隧道中车辆运行速度的影响不同。切线段前后曲线半径(或)、曲率()和曲线度数()的影响并不重要。此外,我们发现限速()的影响与驾驶员的驾驶场景和安全意识密切相关。这些发现可以提高隧道几何参数和交通安全的设计和联合评估。