Quantifying the Effect of Rainfall and Visibility Conditions on Road Traffic Travel Time Reliability

Abstract

Abstract This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices. Significance Statement Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.