Travel time reliability (TTR) is widely used to evaluate transportation system performance. Adverse weather condition is an important factor for affecting TTR, which can cause traffic congestions and crashes. Considering the traffic characteristics under different traffic conditions, it is necessary to explore the impact of adverse weather on TTR under different conditions. This study conducted an empirical travel time analysis using traffic data and weather data collected on Yanan corridor in Shanghai. The travel time distributions were analysed under different roadway types, weather, and time of day. Four typical scenarios (i.e., peak hours and off-peak hours on elevated expressway, peak hours and off-peak hours on arterial road) were considered in the TTR analysis. Four measures were calculated to evaluate the impact of adverse weather on TTR. The results indicated that the lognormal distribution is preferred for describing the travel time data. Compared with off-peak hours, the impact of adverse weather is more significant for peak hours. The travel time variability, buffer time index, misery index, and frequency of congestion increased by an average of 29%, 19%, 22%, and 63%, respectively, under the adverse weather condition. The findings in this study are useful for transportation management agencies to design traffic control strategies when adverse weather occurs.

中文翻译：

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研究不利天气对上海城市走廊出行时间可靠性的影响

行驶时间可靠性（TTR）被广泛用于评估运输系统的性能。恶劣的天气条件是影响TTR的重要因素，它可能导致交通拥堵和交通事故。考虑到不同交通条件下的交通特性，有必要探讨不同条件下不利天气对TTR的影响。本研究使用在上海延安走廊收集的交通数据和天气数据进行了实地旅行时间分析。分析了不同巷道类型，天气和一天中不同时间的出行时间分布。在TTR分析中考虑了四种典型情况（即高架高速公路的高峰时间和非高峰时间，主干道的高峰时间和非高峰时间）。计算了四种措施来评估不利天气对TTR的影响。结果表明对数正态分布是描述行程时间数据的首选。与非高峰时间相比，恶劣天气对高峰时间的影响更大。在不利天气条件下，行驶时间的可变性，缓冲时间指数，痛苦指数和交通拥堵频率分别平均增加了29％，19％，22％和63％。这项研究的发现对于运输管理机构在恶劣天气发生时设计交通控制策略很有用。在不利的天气条件下，分别为22％和63％。这项研究的发现对于运输管理机构在恶劣天气发生时设计交通控制策略很有用。在不利的天气条件下，分别为22％和63％。这项研究的发现对于运输管理机构在恶劣天气发生时设计交通控制策略很有用。