Abstract

Underground road systems are becoming popular in cites because they can overcome urban space constraints and increase capacity and accessibility for urban transport systems. In cities with rivers and seas, the construction of cross-river tunnels can preserve land resources and reduce traffic congestion without affecting navigation. However, tunnel traffic safety has become an increasing concern due to frequent and serious tunnel traffic crashes. The severity of crashes and the difficulty of rescue in tunnels are higher than those of other road sections. To improve the safety of tunnel operation, this paper analyzes the crash data of 14 river-crossing tunnels in Shanghai from 2015 to 2016. A negative binomial (NB) model is employed for crash frequency, and a tobit model is employed for crash rate. With respect to possible spatial and temporal correlations in accident data and unobserved heterogeneity across observations, random-effect (RE) and random-parameter (RP) regression models are utilized. The tunnel geometry characteristics, traffic conditions and crash location are considered as independent variables. The results of the crash frequency show that annual average daily traffic (AADT), speed limit, grade, grade differences and the ratio of the vertical grade to the curve radius (RGR) are likely to increase the crash frequency in cross-river tunnels while horizontal curve radius, vertical curve radius and long tunnel are associated with fewer crashes. This study also explored the use of crash rate instead of crash frequency as a dependent variable by using a random-parameter tobit model. The results indicate that the significance of most independent variables is consistent with the results obtained from the random-parameter negative binomial model based on crash frequency.

摘要

地下道路系统在城市中越来越受欢迎，因为它们可以克服城市空间限制并提高城市交通系统的容量和可达性。在有江海的城市，修建过江隧道可以在不影响通航的情况下保护土地资源，减少交通拥堵。然而，由于隧道交通事故频发且严重，隧道交通安全问题日益受到关注。隧道内撞车事故严重程度和救援难度均高于其他路段。为提高隧道运营的安全性，本文对2015-2016年上海14条过江隧道的碰撞数据进行分析。碰撞频率采用负二项式（NB）模型，碰撞率采用tobit模型。关于事故数据中可能存在的空间和时间相关性以及观察到的未观察到的异质性，使用了随机效应 (RE) 和随机参数 (RP) 回归模型。隧道几何特征、交通状况和碰撞位置被视为独立变量。碰撞频率结果表明，年平均日交通量（AADT）、限速、坡度、坡度差异以及垂直坡度与弯道半径之比（RGR）可能会增加跨江隧道的碰撞频率，而水平弯道半径、垂直弯道半径和长隧道与较少的事故相关。本研究还通过使用随机参数 tobit 模型探索了使用崩溃率而不是崩溃频率作为因变量。