Weather and road capacity

The paper presents estimations of the effect of bad weather on the observed speed on a Danish highway section; Køge Bugt Motorvejen. The paper concludes that weather, primarily precipitation and snow, has a clear negative effect on speed when the road is not in hypercongestion mode. Furthermore, the capacity of the highway seems to be reduced in bad weather and there are indications that travel time variability is also increased, at least in free-flow conditions. Heavy precipitation reduces speed and capacity by around 5-8%, whereas snow primarily reduces capacity. Other weather variables such as darkness, frost, wind and fog also have effects, but they are minor and are hard to assess exactly. In general, the effects are less than found in other studies, primarily from North America. The effects are estimated using a two-step procedure. In step 1 the log to travel time is regressed non-parametrically against traffic density and in step 2 the residuals from step 1 are regressed linearly against the weather variables. The choice of a non- parametric method is made to avoid constricting ties from a parametric specification and because the focus here is not on the relationship between traffic flow and speed.

本文针对丹麦高速公路路段克厄湾高速公路（Køge Bugt Motorvejen）的实测车速受恶劣天气的影响程度展开估算。研究结论显示，当道路未处于超拥挤（hypercongestion）状态时，天气因素（主要为降水与降雪）会对车速产生显著负面影响。此外，恶劣天气下高速公路的通行能力会出现下降，且有迹象表明至少在自由流（free-flow）状态下，出行时间变异性亦有所提升。强降水会使车速与通行能力下降约5%至8%，而降雪则主要降低通行能力。其余天气变量，如夜间、霜冻、大风与雾天等同样会产生影响，但影响程度相对微弱，且难以精准量化。总体而言，本次研究得出的影响程度低于其他主要来自北美的相关研究结果。本次影响程度的估算采用两步法完成：第一步以交通密度（traffic density）对出行时间的对数进行非参数回归（non-parametric regression）；第二步将第一步得到的残差（residuals）与天气变量进行线性回归（linear regression）。选择非参数方法的原因在于，一是可规避参数化设定（parametric specification）带来的约束限制，二是本次研究的核心并非聚焦于交通流量（traffic flow）与车速之间的关联。

搜集汇总

背景与挑战

背景概述

该数据集基于丹麦高速公路段的研究，总结恶劣天气（特别是降水和雪）对道路速度和容量的负面影响：降水可降低速度和容量约5-8%，雪主要减少容量，其他天气因素影响较小；研究采用两步回归方法，并发现效应低于北美类似研究。