Analysis of Impact of Adverse Weather on Freeway Free-Flow Speed in Spain, TRB 89th Annual Meeting Compendium of Papers DVD, 10‑2195 [1]

F. Torregrosa, A. Garcia, and E. Esplugues

“Spain”

Polytechnic University of Valencia, Spain

Weather conditions have an effect over traffic flow characteristics, including speed and capacity. Several previous researches have stated that rain, snow, wind speed, and visibility loss make the speed and capacity to reduce. The knowledge of these relationships is important in order to manage appropriately the traffic flow. In this paper, a new research is presented that evaluates the free-flow speed reduction caused by inclement weather conditions, including rain, snow, wind speed, and visibility loss. There were 15 selected freeway locations in the northwestern Spain. Data was collected in a 15-minute interval by weather and traffic stations during almost three years, from 2006 to 2008. All the individual correlations between the weather and traffic variables were examined in order to select the most important weather variables, and to identify the speed trends and thresholds. All climate conditions were divided into four groups: no precipitation and temperatures above 0ºC, no precipitation and temperatures below 0ºC, rain, and snow conditions. With the final variables choice, a multiple nonlinear regression analysis was performed. Results showed that rain and snow made the speed to reduce in a similar way, but the speed reduction was more dramatic at snow conditions. Wind speed was affected when it was over 8 m/s, while the effect of visibility loss presented a logarithmical form. It also was determined that the location made the variables to affect the speed in a very different way, so for further researches it is recommended to select a big number of sites.

Category 1 – The paper investigates the effect of different weather conditions on the traffic speed and flow for different freeways in Spain. It provides direct measurement of traffic conditions at 15-minute intervals under a variety of weather conditions.

Status – A sample of the data were obtained and reviewed for this project. The results of that review are documented in Section 3.2.

Comparison of Driving Behavior and Safety in Car-Following Platoons Under Icy and Dry Surface Conditions, TRB 89th Annual Meeting Compendium of Papers DVD, 10‑0504 [2]

M. Tanaka, and P. Ranjitkat

“New Zealand”

T. Nakatsuji

“Japan”

University of Auckland, Hokkaido University

Road surface condition is one of the most significant factors that influence driving behavior. Drivers often get nervous and drive differently when they encounter an unusual roadway surface and feel they could not control their vehicle, as well as they normally could. There have been many data in the past showing how the roadway friction factor changes on wet, snow, or other unusual surface conditions. However, there are only some data showing how drivers change their car-following behavior on such unusual surfaces. In this study, we utilized rare car-following data on icy surface condition and compared the vehicle safety and car-following behavior on such a slippery surface to the normal dry asphalt surface condition. In order to evaluate the vehicle safety in the car-following conditions, we defined three safety indicators: potential collision index, impact speed, and expected impact speed. Our outcomes in these safety indicators showed a significant difference between the icy and dry surface conditions. We investigated further for what caused this difference even after considering a range of possible maximum deceleration rates and reaction times. We found that speed-spacing relationships were significantly different and drivers were creating much longer spacing to avoid rear-end collisions on the icy surface more than necessary. As a result, the icy surface showed significantly safer indicator values than the dry surface. At the same time, the result let us consider that drivers may have too much confidence and take very high rear-end collision risks on the dry surface.

Category 1 – This study addressed car-following behavior under icy conditions in a test track environment. This data was recommended for further evaluation since data on car-following behavior in icy conditions is very difficult to find. In addition, this research was conducted under very rigorous conditions, providing a high level of confidence in the results.

Status – The authors provided the data to the study team and an analysis was conducted that was documented in the report “Microscopic Analysis of Traffic Flow in Inclement Weather: Impact of Icy Roadway Conditions on Driver Car-Following Behavior,” prepared for FHWA by Virginia Tech Transportation Institute and Cambridge Systematics, February 2010.

Variation in Impact of Cold Temperature and Snowfall and Their Interaction on Traffic Volumes, TRB 89th Annual Meeting Compendium of Papers DVD, 10‑3182 [3]

S. Datla

“Canada”

University of Regina

Presented in this paper is a detailed investigation of highway traffic variations with severity of cold, amount of snow, and various combinations of cold and snow intensities. Separate analysis for starting, middle, and ending months of winter seasons is conducted to understand the variations in traffic-weather relationships within the winter season. The study is based on hourly traffic flow data from 350 permanent traffic counter sites located on the provincial highway system of Alberta, Canada, and weather data obtained from nearby Environment Canada weather stations, during the period of 1995 to 2005. Multiple regression analysis is used in the modeling process. The model parameters include three sets of variables: amount of snowfall as a quantitative variable, categorized cold as a dummy variable and an interaction variable formed by the product of the above variables. The developed models closely fit the real data with R‑square values greater 0.99. The study results indicate that the association of highway traffic flow with cold and snow varies with day of week, hour of day, and severity of weather conditions. A reduction of 1 percent to 2 percent in traffic volume for each centimeter snowfall is observed when the mean temperatures are above 0°. For the days with zero precipitation, reductions in traffic volume due to mild and severe cold are 1 percent and 31 percent, respectively. An additional reduction of 0.5 percent to 3 percent per each centimeter of snowfall results when snowfall occurs during severe cold conditions. Study results show lesser impact of adverse weather conditions on highway traffic volumes during severe winter months and the months thereafter as compared to starting months.

Category 1 – This paper investigates the effect of snow and cold on traffic flow variation using empirical weather and traffic flow data; providing the data could be relevant if it will be related to the freeway capacity and car-following models.

This report was recommended for evaluation pending further review since models developed for WRTM strategies need to take into account reductions in overall volume that may occur due to adverse weather. It appears this research successfully modeled this relationship in Alberta.

Status – While the paper provided some useful parameters, the authors could not be reached to obtain the full dataset.

The Impact of Rain on Travel Characteristics in Korean Freeways, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑1743 [4]

S. Baek, B. Kim, Y. Lim, and J. Kang

“South Korea”

Korea Expressway Corporation

Several factors such as accidents, road maintenance, and bad weather contribute to traffic congestion. Among them, weather greatly affects road safety through the increased risk of crashes, as well as the increased exposure to weather-related hazards. It also is known that inclement weather conditions decrease the demand for transport while also decreasing the capacities of freeways. However, it is still unclear exactly how much transport demand and freeway capacity decrease under adverse weather conditions. Moreover, traffic congestion that arises due to bad weather may alter the destinations of travelers or cause them to altogether forego their trips. Although information on trips by origin and destination is required for analyzing transportation planning in urban areas, few studies have examined the relationship between weather conditions and travel patterns. This work examines changes in expressway travel patterns that arise due to adverse weather conditions, and analyzes the effect of weather conditions on the volume of traffic and the travel distance. We compare normal travel patterns with those of rainy days with regard to the travel distance for each type of vehicle. Results show that, as expected, the traffic volume and travel distance decrease in rainy days; the findings also reveal differing travel patterns for weekdays as compared with weekends.

Category 1 – This study looks at travel patterns and traffic volumes during adverse weather. While it can be termed macroscopic, it is a more general study than others conducted for WRTM in that it addresses broad changes in trip generation and trip distribution.

Status – As this information appeared to duplicate that in other studies, the dataset was not requested.

Multilevel Assessment of the Impact of Rain on Drivers’ Behavior: Standardized Methodology and Empirical Analysis, Transportation Research Record No. 2107 [5]

R. Billot, N. El Faouzi, and F. De Vuyst

“France”

Institut National de Recherche sur les Transports et leur Securite (INRETS), Ecole Centrale de Paris

This study deals with the analysis of the impact of rain on drivers’ behavior and traffic operations. First, a generic methodology for assessing the effect of weather on traffic is proposed through a multilevel approach: from individual traffic data, the rain impact is assessed at a microscopic level (time, headways, and spacing). Next, the same data were used to extend the study to a mesoscopic and a macroscopic level. The mesoscopic level deals with the effects of rain on platoons, and the macroscopic level resides in the analysis of the impact of rain on the fundamental diagram enabling weather-responsive macroscopic traffic simulation. Second, following this approach, an empirical study is carried out from individual data collected on a French interurban motorway. Weather data were provided by a weather station located near the test site. The results suggest a significant impact of rain on drivers’ behavior and traffic operations, which increases with the intensity of rainfall.

Category 1 – This study involved a simulation effort. The impact of rain on traffic flow at microscopic level was estimated using data from a French interurban motorway. The test site included a nearby weather station.

Status – The detailed dataset was requested but unavailable due to confidentiality restrictions.

Integrating the Effects of Adverse Weather Conditions on Traffic: Methodology, Empirical Analysis, and Bayesian Modeling, European Conference of Transportation Research Institutes, Young Researchers Conference ’09 [6]

R. Billot

“France”

Institut National de Recherche sur les Transports et leur Securite (INRETS), Ecole Centrale de Paris

One of the characteristics of an efficient traffic management resides in the abundance of situations to which the road managers are able to adapt and react in real-time. In this respect, as many sources of uncertainty as possible have to be mastered in order to alleviate negative impacts of congestion, and hence increase the level of service of associated networks. Inclement weather conditions are considered as one key factor which can affect traffic operations and safety. Whereas the impact on traffic safety is well known (frequency and severity of crashes), the effects of adverse weather conditions on traffic mobility need to be quantified and account for in the development of weather-responsive traffic management strategies. The objective of the research reported in this paper is twofold: first, it intends to exhibit the significant impact of adverse weather conditions on traffic operations and its quantification based on a rigorous methodology we have proposed in a previous work. More precisely, the assessment of the rain effects on the main traffic characteristics are achieved following a multilevel approach: microscopic level, mesoscopic level, and finally macroscopic one. Second, from an empirical analysis, the quantified adverse weather impact on traffic is then taken into account into a macroscopic traffic stream model to serve as a decision support system for on-line traffic management strategies. The Bayesian approach is used as a modeling framework through the use of particle filtering methods, which are suitable for solving the traffic state estimation issue. The results clearly demonstrate how the knowledge about the weather effects on traffic enables a more accurate traffic state estimation. The potential of the weather-responsive traffic model prototype appears as the core of a new generation of traffic management decision support systems (DSS).

Category 1 – This project included the development of a theoretical framework, as well as an empirical analysis of weather impact on traffic flow, using a Bayesian modeling technique. Data were obtained from a motorway in France.

Status – This dataset was requested but was not available due to confidentiality agreements.

Assessing the Impact of Weather on Traffic Intensity, TRB 87th Annual Meeting Compendium of Papers DVD, 08‑1903 [7]

M. Cools, E. Moons, and G. Wets

“Belgium”

Transportation Research Institute, Hasselt University

The investigation of weather effects on traffic intensity is important from a road safety point of view, because traffic intensity is noted as the first and primary determinant of traffic safety. Next to traffic safety, weather conditions affect other predominant traffic variables, namely traffic demand and traffic flow. Therefore, the main objective of this study is the identification and comparison of weather effects on traffic intensity at different site locations. To assess the impact of weather conditions on traffic intensity, the upstream and downstream traffic of four traffic count locations are considered. The traffic intensity data originate from minute data coming from single inductive loop detectors, collected by the Flemish Traffic Control Center. Data concerning weather events were recorded by the Royal Meteorological Institute of Belgium. The main modeling philosophy envisaged in this study to identify and quantify weather effects is the linear regression approach. Most appealing result of this study for policy-makers is the heterogeneity of the weather effects between different traffic count locations, and the homogeneity of the weather effects on upstream and downstream traffic at a certain location. The results also indicated that snowfall, rainfall, and wind speed have a clear diminishing effect on traffic intensity, while maximum temperature significantly increases traffic intensity. Further, generalizations of the findings are possible by studying weather effects on local roads, and by shifting the scope towards travel behavior. Simultaneously modeling of weather conditions, traffic intensity rates, collision risk, and activity travel behavior is certainly a key challenge for further research.

Category 1 – This is a study that used detailed, empirical measurements of traffic and weather conditions to address adverse weather impacts. As it parallels some of the macroscopic research being conducted through the WRTM, this dataset could be useful for review and analysis.

Status – This dataset was recommended for further analysis, but was unavailable due to confidentiality restrictions.

The Impact of Adverse Weather on Travel Time Variability of Freeway Corridors; TRB 2007 Annual Meeting CD‑ROM, 07‑1642 [8]

H. Tu, J. W. C. van Lint, and H. J. van Zuylen

“Holland”

Delft University of Technology

Over the last two decades, travel-time reliability has become an important aspect of transportation system performance. One group of factors affecting travel-time variability is adverse weather, such as rain, snow, ice, fog, and storm. Empirical investigation on the basis of a large database of travel times on various freeways and one year of weather data shows that adverse weather not only increases average travel time, but clearly also influences travel-time variability of freeway corridors. On average, adverse weather results in twice the travel-time variability compared with that under normal weather conditions. It also is found that rain has little or no effect on travel-time variability below a certain critical inflow, but progressively impacts travel-time variability above it. In general, adverse weather conditions make travel time less reliable. This might imply that different traffic control strategies and applications should be considered under different weather conditions.

Category 1 – This study used a large database of travel-time information on various freeways and a year’s worth of weather data to estimate the impact of weather on both travel time and travel-time reliability. The research findings indicated that adverse weather did have a significant impact of travel-time variability, but only at higher levels of traffic flow.

Status – The data were not considered to be of sufficient detail for further research and were not requested.

Impact of Rain to Highway Traffic and Drivers’ Deceleration Behavior, Master of Science thesis, Transportation and Logistics Department, Malaysia University of Science and Technology [9]

Tay Hong Yet

“Malaysia”

Malaysia University of Science and Technology

The objective of this research is to study the impact of rain to the surface traffic and to also understand drivers’ deceleration behavior by calibrating the car-following model to take into account the effects of rain in slowing down vehicular traffic. The method for collecting and processing data, analysis of the results, and the estimation of the parameters for car-following model are reported. Data was collected using video image processing whilst statistical analysis and parameter estimation were utilized to analyze the results. Theoretically, rain affects traffic flow by reducing visibility, decreasing pavement friction, changing driver behavior, and vehicle performance. Hence, it is important to identify the relationship between rain conditions and traffic parameters. At the fixed flow level, speed and clear gap was decreased up to 28 percent and 45 percent. Gap time has greatest change at 22 percent. However, the equivalent value in time is about 0.38 second, which might not be noticeable for a driver to response differently. Density increased up to 39 percent, which exhibits a transition from stable to unstable region under flow-density relationship. This study is based on data from Video Image Processor (VIP) to conduct calibration for car- following deceleration model. The calibrated car-following deceleration model is important in modeling of vehicles’ slow down process during rain. The calibrated model has returned a satisfying result at small error term of -0.089 m/s2 with standard deviation of 0.13 m/s2. This model can be used in traffic flow forecast for Intelligent Transportation System (ITS) applications specifically for traffic simulation during rain.

Category 1 – This study is of significant interest to the WRTM as it used video-image processing data on a segment of Malaysian freeway to collect data on drivers’ deceleration behavior under rainy conditions. A car-following model was calibrated using the data. Estimates were developed of a series of car-following model parameters. The research also captures the effect of rain on the flow-density relationship and deceleration behavior.

Status – While this study appeared to be potentially useful, the authors could not be contacted to request the data.

Including Weather Condition Factors in the Analysis on the Highway Capacity, TRB 83rd Annual Meeting Compendium of Papers DVD, 04‑0548 [10]

N. Okamoto, H. Ishida, and H. Furuya and K. Furukawa

“Japan”

University of Tsukuba, Toyo University

There are many congestion points where the highway structure is considered as one of the main factors of congestion in Japan. The relationship between the structure and the capacity should be analyzed in order to decrease the influence of structural problem on the highway. Moreover, the weather condition is considered as another factor of congestion. But there are few studies which mention the relationship between the weather condition and highway capacity. This paper shows the analysis by modeling on the highway capacity considering the road structure and weather condition. The data on traffic count and the volume of precipitation were used for the modeling. The K‑V function is estimated using the variables of precipitation, curvature, clothoid, and gradient. Finally, from the model estimation results, the significant differences of the road capacity with the different weather conditions, as well as the effect of permeable pavement were shown.

Category 1 – This study modeled highway capacity as a function of both road structure and weather conditions. Traffic counts and precipitation intensity were used.

Status – While the study appears to have modeled the impacts of precipitation intensity on weather flow this was not its primary focus and as a result the data were not requested.

Relationship Between Winter Road Surface Conditions and Vehicular Motions, Measured by GPS-Equipped Probe Vehicles, TRB 82nd Annual Meeting Compendium of Papers DVD, 03‑0757 [11]

T. Nakatsuji, and A. Kawamura

“Japan”

Hokkaido University, Kitami Institute of Technology

In winter, one of the major concerns of drivers is the current road condition. Taxis, which move around ceaselessly over a wide area, have great potential as a sensor for detecting what the road surface conditions are like across a given area. In order to establish a method to estimate road conditions based on the vehicular motion of taxis, some field experiments were conducted using probe vehicles that fitted with vehicular motion sensors and a GPS device prior to the implementation to taxis. Some preliminary analyses were performed using the data measured on a test track, urban streets, and an expressway. The slip ratio, defined as the relative difference in speed between vehicle and tire wheel, was effective in indicating how slippery roads surfaces were. Taxi vehicular motion data also were collected for more than one month, although unlike the probe vehicles the wheel speed was not measured. Some features of vehicular motion specific to slippery roads were identified; and the discriminability of road conditions, whether icy or dry, without using wheel speed data, also was examined.

Category 1 – The researchers used taxis outfitted with GPS devices and vehicular motion sensors to try to estimate vehicular motion parameters specific to dry, wet, or icy road conditions.

Status – This dataset was not requested due to age.

Effect of Weather Conditions to Traffic Flow on Freeway, KSCE Journal of Civil Engineering, Volume 6, Number 4 [12]

J. Sam, Y. Shim, and Y. Cho

“South Korea”

Korea Institute of Construction Technology, New Airport Highway Company, Chung‑Ang University

Traffic speed along a roadway segment is the function of a number of factors like geometry, traffic, and weather conditions. In this paper, the effect of weather conditions on both the speed-flow and flow-occupancy relationships was studied. The data used in the analysis were obtained from traffic management system installed in the Incheon International Airport Expressway.

In order to quantify how seriously weather affects traffic flow conditions, the impact in term of traffic speed was described. Regression analyses were performed to select proper models representing the speed-flow and flow-occupancy relationship for congested operation. From the research, weather conditions reduced the slope of flow-occupancy function and caused a downward shift in the speed-flow function. That is, the free-flow speeds are reduced. Increase of traffic volume by weather event at the YeongJong Grand Bridge (site2) is much larger than at the BwangHwa Grand Bridge (site2), which makes travel speed down significantly. The ratio of free- flow speed reduction was observed 7 percent and 2 percent by snow and rain, respectively. Meanwhile, the ratio of speed reduction was shown that snowy and rainy nights are each 5 percent and 6 percent drop. That is, the effect of snowy day and night is similar, while the effect of rainy night is larger than rainy day in terms of speed reduction.

In case of site2, during daytime, the ratio of speed reduction in snowy and rainy conditions has no difference. However, the ratio of speed reduction during nighttime was decreased 3 percent and 7 percent in each snowy and rainy condition.

Category 1 – This study used empirical data from a major expressway to estimate the impact of weather on speed-flow and flow-occupancy relationships. This study of weather-related adjustment factors is similar to those that recent WRTM research has been exploring but is not recommended for further evaluation due to age of the data.

Status – This dataset was not requested due to its age.

An Experimental Study on the Luminous Intensity Required for LED Roadway Delineators in Foggy Conditions, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑0079 [13]

K. Munehiro, R. Tokunaga, and T. Hagiwara

“Japan”

Hokkaido University and Civil Engineering Research Institute for Cold Weather

Since visibility distances are used in determining the geometric structure of roads, ensuring the visibility necessary for driving is very important in providing safe, comfortable conditions for drivers. However, since foggy conditions make it difficult to ensure the level of visibility needed for driving, a method to make it easier for drivers to see the line of the road is required. For this purpose, retro reflective or light-emitting delineators are installed at roadsides, and delineators with light-emitting diodes (LEDs) are used to improve visibility on routes where high-level service is required for sections with reduced visibility. However, there is no mention of luminous intensity for delineators in any current guidelines, and literature on the luminosity of LED delineators and driver visibility is limited. As a result, the level of luminous intensity required for LED delineators in conditions of poor visibility remains unclear. This study investigated the role that fog plays in reduced visibility, and an experiment was conducted to evaluate the visibility of LED (light-emitting diode) delineators in natural foggy conditions. The experiment was conducted over a two-month period in July and August 2004 on Marine Street, a public road in the Shiranuka area of Hokkaido, using three types of LED delineator. Twenty subjects were tested in each of three cases (one in clear conditions and two in fog) during the day and at nighttime. Based on the results, the luminous intensity required for LED delineators in different conditions of fog was simulated with varying road service speeds.

Category 2 – Although this study is focused primarily on the effectiveness of specific technology, the datasets and analysis could be helpful in assessing the impact of low visibility on driver behavior. The WRTM already is utilizing data from Hokkaido University to address driver behavior under icy conditions.

Impact of Snowy and Icy Weather on Freeway Operation and Improvement Countermeasure Studies of South China, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑1540 [14]

S. Dong, G. Jianping, Y. Nan, and T. Boming

“China”

Chongqing Expressway Development Corporation and Chongqing Jiatong University

At the beginning of 2008, a serious snow and ice disaster attacked most areas in South China and had great impact on road traffic due to the traditional Chinese Spring Festival holiday, and millions of people cannot go home to reunite with their families. Moreover, the damage caused by the disaster has been incalculable. Chongqing, located in southwest China, was inevitably greater impacted. This paper has made a description about the serious impact by the disaster on freeway transportation, compared the gap in management for the snow and ice disaster between South China and developed countries, pointed out the insufficiency in the emergency management of freeway operation under adverse weather conditions, and then proposed a modern weather disaster prewarning system improving the emergency-response plans. Meanwhile, some constructive proposals are presented.

Category 2 – This study addresses safety and emergency response issues during a major disruption resulting from a snow/ice storm. While this study does not appear to include either detailed microscopic or macroscopic analysis, it does include useful findings regarding weather-related traffic management under severe conditions.

Effects of Winter Weather and Maintenance Treatments on Highway Safety, TRB 85th Annual Meeting Compendium of Papers DVD, 06‑0728 [15]

L. Fu, M. Perchanok, L. Moreno, and Q. Shah

“Canada”

University of Waterloo, Ontario Ministry of Transportation

This research has conducted an analysis of the effects of winter weather and maintenance treatments on the safety of highways as related to factors such as weather, road, and treatment characteristics. The ability to assess and quantify these effects is essential for a comprehensive cost-benefit analysis of alternative maintenance strategies and methods and effective communication of the impacts of these strategies and methods to the decision-makers and the public. Two highway routes from Ontario, Canada were selected and data on daily accident occurrences, weather conditions, and winter maintenances operations were obtained for this analysis. A statistical analysis was performed on the integrated dataset with the goal of identifying those weather and maintenance factors that had a significant impact on crash frequency. The modeling results indicate that weather conditions, such as temperature and precipitation (mainly snow fall), had a significant effect on the crash risk. Anti-icing and prewetting operations were found to have improved road safety at one of the study sites. Sanding operations were found to have a positive effect on the safety at both maintenance routes. The research, however, could not statistically confirm the safety effect of conventional maintenance operations – plowing and salting with dry salt.

Category 2 – This research used empirical data to assess the impact of different highway maintenance strategies on crash rates.

A Temporal Analysis of Weather-Related Collision Risk for Ottawa, Canada: 1990 to 1998, TRB 82nd Annual Meeting Compendium of Papers DVD, 03‑3488 [16]

J. Andrey, B. Mills, and J. Vandermolen

“Canada”

University of Waterloo

Past research provides evidence that collision and injury risk increase during precipitation relative to normal driving conditions, although estimates vary due to differences in driving context and research methods. Less effort has been devoted to studying how weather-related risks vary over time, and what these variations tell us about interactions between weather and other risk factors. This study examines temporal variations in weather-related collision and injury risk using collision and weather data for Ottawa, Canada, over the period 1990 to 1998. A matched-pair approach was used to define precipitation events and corresponding controls in order to estimate and compare the risk of collision and injury during precipitation relative to normal seasonal conditions for weekdays versus weekends, nighttime versus daytime, peak period versus other daytime; and early winter season versus late-winter season. Results indicate that collision risk increased significantly – by more than 100 percent for rain and approximately 50 percent for winter precipitation events. Injury risk also was elevated, but to a lesser extent. Increases in precipitation-related collision risk during the winter were higher on weekends relative to weekdays. Also, collision risks were especially high during the early part of the winter season.

Category 2 – Empirical data were utilized to estimate variation in crash and injury rates for different weather conditions and different temporal periods.

Weather and traffic accidents in Montreal, Canada, Climate Research, Volume 9, pages 225-230. [17]

M. Andreescu, and D. Frost

“Canada”

McGill University, Concordia University

Impact of weather conditions on traffic accidents is an insufficiently understood and poorly quantified phenomenon in Canada, and recent research results reflect conditions that are not entirely characteristic of the Canadian climatic setting. This study analyzed the effects of rain, mean temperature, and snow on automobile accidents in Montreal, Canada, from 1990 to 1992. Three timeframes were used – monthly, annual, and the entire study period. All three weather variables impacted road accidents significantly. Snow was shown to be the leading variable, as the number of accidents increased sharply with increased snowfalls. This finding is important in light of recent provincial and municipal proposals to reduce spending on winter snow cleaning as a way of cutting operating costs.

Category 2 – This study estimated the impact of snow, rain, and mean temperature on automobile crashes in Montreal during the period 1990 to 1992.

Developing Traffic and Weather Responsive Signal Control for Isolated Intersections, TRB 87th Annual Meeting Compendium of Papers DVD, 08‑2262 [18]

N. Setala, D. Kosonen, and T. Luttinen

“Finland”

Helsinki University of Technology

Adaptive traffic control systems are used to improve the performance of intersections with highly variable traffic volumes or other conditions. This paper describes a traffic and weather responsive adaptive signal control system developed to enhance an existing intelligent signal control system based on fuzzy logic. Built on top of a real-time microscopic simulation model, the adaptation is carried out not only by changing the signal timings and control schemes of an isolated intersection, but by also adapting the traffic model to fit the current traffic and weather situation. The system has been tested with simulations, and the results suggest that improvements in the performance of intersections as well as in safety can be achieved. Finally, some further research is suggested.

Category 3 – This study addresses an important aspect of WRTM, adaptive signal timing. However, the analysis is based on simulation.

Modeling Impacts of Adverse Weather Conditions on a Road Network with Uncertainties in Demand and Supply, Transportation Research Part B [19]

W. Lam, H. Shao, and A. Sumalee

“China”

The Hong Kong Polytechnic University, China University of Mining and Technology

This paper proposes a novel traffic assignment model considering uncertainties in both demand and supply sides of a road network. These uncertainties are mainly due to adverse weather conditions with different rainfall intensities on the road network. A generalized link travel-time function is proposed to capture these effects. The proposed model allows the risk-averse travelers to consider both an average and uncertainty of the random travel time on each path in their path choice decisions, together with the impacts of weather forecasts. Elastic travel demand is considered explicitly in the model responding to random traffic condition in the network. In addition, the model also considers travelers’ perception errors using a logit-based stochastic user equilibrium framework formulated as fixed point problem. A heuristic solution algorithm is proposed for solving the fixed point problem. Numerical examples are presented to illustrate the applications of the proposed model and efficiency of the solution algorithm.

Category 3 – This study addresses several important aspects of WRTM, including adaptive signal timing. However, the analysis is based on simulation.

Performance Measures for Snow and Ice Control in the Province of Alberta, TRB 85th Annual Meeting Compendium of Papers DVD, 06‑0548 [20]

L. Falls, R. Jurgens, and J. Chan

“Canada”

Alberta Infrastructure and Transportation, University of Calgary

Performance measurement is a vital component of asset management, which is used in planning and programming to identify assets that are under or over performing and to assess overall performance over time. As part of the move to asset management, Alberta Transportation has implemented performance-based planning and monitoring of the provincial highway network. Three performance measures, based upon technical measurement, have been adopted which characterize network condition, functional adequacy and utilization. However, Alberta, like the rest of Canada, is a winter province, yet no clear suite of performance measure has been developed for snow and ice control. Traditionally, agencies have measured inputs (such as salt or sand) or outputs (such as plowing frequencies), but none of the existing measures address effectiveness. This paper presents the results of a project to develop winter performance measures that address both the planning and operations of a large rural highway network. Preliminary results indicate that traffic volumes and speed data can be used to identify major storm events, and as such may hold promise as repeatable, robust, relevant, and responsive performance measures.

Category 3 – The purpose of this effort was to develop a set of performance measures related to snow and ice control. Some of the measures address the data that are being mined in this project, such as traffic volumes and speed. The primary purpose was to identify potential measures; not to actually develop or evaluate them.

Climate Change – A Challenge for Norwegian Roads, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑1780 [21]

G. Petkovic, and J. O. Larsen

“Norway”

This short paper offers some preliminary information about the work on adaptation to climate change currently being carried out by the Norwegian Public Roads Administration.” Climate and Transport,” a four-year R&D program initiated in 2007, addresses all the topics considered to be important for effective adaptation of planning, design, operation, and maintenance of roads under changed climate conditions. The program consists of seven projects; the results of which will be formulated as amendments to Road Administration manuals and projects on the road network demonstrating necessary action for adaptation to climate change. The main objectives of the program are to evaluate the effect of climate change on the road network and recommend remedial action concerning planning, design, construction, and maintenance of the road network.

Category 4 – This paper focuses on long-term impacts of climate change on the roadway network.

Context-Sensitive Design for Nanjing‑Changzhou Expressway, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑2429 [22]

Q. Guochao, Z. Min, Z.Jiankang, C. Jingya, and C.Jianchuan

“China”

In recent years, China has made great achievements in expressway construction, which do attract worldwide attention. To enhance expressway’s capacity, safety, environmental-friendliness, landscape view and so on, new concepts like context-sensitive solution and flexibility for highway design have been encouraged here. And Nanjing‑Changzhou Expressway (hereinafter the NingChang Expy) is just designed with such considerations. Flanking the Expy are varied terrains and unique landscapes along with rich humanistic resources. The present paper focuses upon some of the key technologies employed in its design based on the context-sensitive principle, covering such main issues as safe and harmonious alignment, natural protection engineering, flexible and ecologic drainage, unique landscape, human-centered service area design, as well as public participation. The solutions we propose here aim to further build the NingChang Expy into a fully modernized one characterized by its great safety, satisfying environmental protection, ecological balance, and attractive landscapes for booming tourism, its design believed to be of valuable reference for future projects of the kind.

Category 4 – This paper focuses on environmental issues related to design, although safety issues are included.

Long-Term Analysis of Reductions in Traffic Volume Across New Hampshire During Winter Storms, Transportation Research Circular EC‑126, Surface Transportation Weather and Snow Removal and Ice Control Technology; Weather 08-011 [23]

M. G. Wellman, S. Miller, S. Gray, and J. Zabransky

New Hampshire DOT, Hometown Forecasting Services, Plymouth State University

Snow, sleet, freezing rain, and rain are all common occurrences throughout the northeastern United States. These hazardous weather conditions can paralyze communities statewide. Reductions in traffic volume during these hazardous events can be used to quantify the number of people affected by a particular winter storm, and provide a measure of how people perceive the severity of individual winter storms. Traffic counts were provided by the New Hampshire DOT for 15 locations across the State. These counts were then correlated with nearby weather observations, provided by the National Climatic Data Center and Plymouth State University’s on‑line database. There were 51 storm events between November 1999 and March 2004. The reductions in traffic volume were calculated hourly and by day, and compared with individual storm characteristics. The hourly reductions were compared to temperature, dew point, relative humidity, wind speed, wind direction, wind gusts, pressure, sky cover, visibility, precipitation type, and precipitation intensity. In addition, the daily reductions were compared to snowfall amounts. A statewide average hourly reduction in traffic volume of 22.2 percent was found for all winter storms. Reductions in traffic volume were found to be most related to storm characteristics related to storm intensity. Storm hours with a northeast wind component were more likely to have the greatest reductions in traffic volume. Likewise, the intensity of snowfall on average across the State doubled the reductions in traffic volume. Reductions in traffic volume also held a strong relationship with visibility: the lower the visibility the greater the reductions in traffic volume. Hourly reductions also were closely correlated to diurnal pattern. The greatest reductions in traffic volume occurred after the evening commute; however, the greatest reductions in vehicles occurred during the evening commute. The comparisons between storm total snowfall and average storm reduction in traffic volume proved to be the most significant relationships. Storm average reductions were found to be related to storm total snowfall. However, they are most related to locations with the greatest average daily traffic volume. In addition, a direct relationship was found between the statewide storm average reductions and the statewide storm total snowfall, and an even stronger relationship with statewide average snowfall amounts greater than five inches.

Category 1 – This study compared weather observations from the National Climatic Data Center and Plymouth State University to traffic counts at 15 locations across the State. Fifty-one storm events were evaluated over a two-year period, and reductions in traffic volume correlated with snowfall and visibility reductions.

Status – This dataset was not requested since data were aggregated over large areas.

Gap Acceptance for Vehicles Turning Left Across Oncoming Traffic: Implications for Intersection Decision Support Design, TRB 85th Annual Meeting Compendium of Papers DVD, 06‑2696 [24]

D. Ragland, S. Arroyo, S. Shladover, J. Misener, and C. Chan

“University of California, USA”

A left-turning vehicle (Subject Vehicle, SV) attempting to cross the path of an oncoming vehicle (Principal Other Vehicle, POV) at an intersection typically does not have the right-of-way. The main task of the SV driver is to find an adequate opportunity in opposing traffic to initiate the left-turn maneuver. To reduce the probability of a conflict, warning systems, such as Intersection Decision Support (IDS) systems, are being developed. These systems alert drivers of SV vehicles attempting to negotiate a left-turn about traffic approaching from the opposite direction. The current paper 1) describes a video system that was used to assess gap length, gap acceptance, and gap rejection in a Left Turn Across Path/Opposite Direction (LTAP‑OD) scenario, 2) describes a way to characterize gap distribution (log-normal) presented to the SV driver, and 3) illustrates how a logistic model often used to describe dose-response curves can be used to characterize gap acceptance by the SV driver. These results are used as the basis for a discussion of implications for IDS systems for alerting left-turning drivers about oncoming vehicles.

Category 1. This paper studies left-turn gap acceptance behavior at five different intersections in California. In addition, the IDS (Intersection Decision Support) concept is introduced in this paper. It will be very useful, if the data of this paper are provided for validation purposes of gap acceptance models.

Status – While the paper could potentially be useful for validation purposes, it does not involve analysis of weather and therefore was not requested.

The Use of Weather Data to Predict Nonrecurring Congestion, Technical Report, Agreement T2695, Task 54, Washington State Transportation Center (TRAC) [25]

D. J. Dailey

Washington State Transportation Center, University of Washington

This project demonstrates the quantitative relationship between weather patterns and surface traffic conditions. The aviation and maritime industries use weather measurements and predictions as a normal part of operations, and this can be extended to surface transportation. Data from two data mines on the University of Washington campus were combined to evaluate the quantitative relationship between freeway speed reduction and rainfall rate as measured by Doppler radar. The University of Washington’s Atmospheric Science department maintains an archive of Nexrad radar data, and the Electrical Engineering department maintains a data mine of 20-second averaged inductance loop data. The radar data were converted into rainfall rate, and the speed data from the inductance loop speed traps were converted into a deviation from normal performance measure. The deviation from normal and the rainfall rate were used to construct an impulse response function that can be applied to radar measurements to predict traffic speed reduction. This research has the potential to accomplish: 1) prediction of nonrecurring traffic congestion, and 2) prediction of conditions under which incidents or accidents can have a significant impact on the freeway system. This linkage of weather to traffic may be one of the only nonrecurring congestion phenomena that can be accurately predicted. This project created algorithms and implementations to correlate weather with traffic congestion. Furthermore, it may provide a means for traffic management to determine where and when to proactively place resources to clear incidents.

Category 1 – This project used freeway speed data and rainfall rates measured by Doppler Radar to estimate the impact of rainfall intensity on speeds and traffic congestion. The research addressed the possibility of predicting nonrecurring congestion based on weather conditions. While the factors developed may be considered in developing weather-related adjustment factors, the radar data used does not necessarily represent ground conditions. ESS observations would be preferable.

Status – This dataset was not requested due to the fact that weather radar data were used.

Impact of Weather on Urban Freeway Traffic Flow Characteristics and Facility Capacity, Aurora Project/‍Midwest Transportation Consortium, Center for Transportation Research and Education, Iowa State University [26]

M. Agarwal, T. H. Maze, and R. Souleyrette

Iowa State University

Adverse weather reduces the capacities and operating speeds on roadways, resulting in congestion and productivity loss. A thorough understanding of the mobility impacts of weather on traffic patterns is necessary to estimate speed and capacity reductions. Nearly all traffic engineering guidance and methods used to estimate highway capacity assume clear weather. However, for many northern states, inclement weather conditions occur during a significant portion of the year. This paper describes how the authors quantified the impact of rain, snow, and pavement surface conditions on freeway traffic flow for the metro freeway region around the Twin Cities. The research database includes four years of traffic data from in‑pavement system detectors, weather data over the same period from three automated surface observing systems (ASOS), and two years of available weather data from five road weather information systems (RWIS) sensors at the freeway’s roadside. The research classifies weather events by their intensities and identifies how changes in weather type and intensities impact the speed, headways, and capacity of roadways. Results indicate that severe rain, snow, and low visibility cause the most significant reductions in capacities and operating speeds. Rain (more than 0.25 in./hr), snow (more than 0.5 in./hr), and low visibility (less than 0.25 mi) showed capacity reductions of 10 percent to 17 percent, 19 percent to 27 percent, and 12 percent and speed reductions of 4 percent to 7 percent, 11 percent to 15 percent, and 10 percent to 12 percent, respectively. Speed reductions due to heavy rain and snow were found to be significantly lower than those specified by the Highway Capacity Manual 2000.

Category 1 – This research utilized traffic speed and volume data and a mix of ASOS and RWIS weather station data to estimate capacity and speed reductions due to adverse weather. Snow, rain, and pavement condition were all evaluated in the Twin Cities region of Minnesota.

Status – Analysis of this dataset was not considered for this project since the results of this study were documented in other WRTM projects related to driver behavior in adverse weather.

Analysis of Weather Impacts on Traffic Flow in Metropolitan Washington, D.C., Institute of Transportation Engineers 2003 Annual Meeting and Exhibit, CD‑ROM [27]

V. P. Shah, A. D. Stern, L. Goodwin, and P. Pisano

Federal Highway Administration (FHWA)

Anyone who uses surface transportation has been affected by delays caused by various forms of weather. Whether it is rain or snow, ice or fog, the result is usually the same. Travel delay rises as traffic congestion increases. The FHWA’s RWMP has been sponsoring research into the impacts of weather on surface transportation. One specific research task involved attempting to quantify the amount of travel delay imposed upon drivers due to the effects of inclement weather. This paper describes two different methods used to approximate the average travel delay impacts of weather along approximately 712 directional miles of roadway around metropolitan Washington, D.C. based on weather and travel-time data spanning from December 1999 to May 2001. Each method uses meteorological data sets of differing temporal and spatial resolutions in conjunction with travel-time data archived from a real-time publicly available Internet-based travel advisory source. The average increase in travel time due to precipitation for peak-period traffic in the Washington, D.C. region is estimated to be 25 percent based on radar data specific to particular roadways. The less refined analysis based on regional measurements of weather suggest a 12 percent increase in travel time due to factors of precipitation, visibility, and wind. During the off-peak periods in the daytime, travel time increases by approximately 13 percent due to the array of weather attributes. Measuring the impact of only precipitation, suggests that during the off-peak periods, precipitation causes a 3.5 percent increase in travel time. This estimate, however, is likely to be lower than reality due to the limitations in travel-time data.

Category 1 – This study estimated the amount of delay due to inclement weather using three years of data from the Washington, D.C. area.

Status – This dataset was not reviewed due primarily to age.

Safety Effects of Winter Weather: The State of Knowledge and Remaining Challenges, TRB 88th Annual Meeting Compendium of Papers DVD, 09‑3353 [28]

C. Strong, X. Shi, and Z. Ye

City of Oshkosh, Montana State University

In recent years, there has been growing recognition of the effects of weather on the surface transportation system. Although considerable work has been done in quantifying the effects of weather on the highway system, there is still much that remains unknown about the relationship between weather and highway system performance. This paper synthesizes the findings from some of the major efforts in this area. A table is presented which estimates the change in crash frequency and vehicle travel speed resulting from various winter weather conditions, based on a synthesis of earlier work. Recognizing the lack of comparability between the results of the studies, the paper concludes with a detailed discussion of avenues for future research which could help to address some of the gaps which currently exist.

Category 3 – This study is a compendium of various research findings on the impact of weather on traffic flow and concludes with recommendations for further research.

Whether Weather Matters to Traffic Demand, Traffic Safety, and Traffic Operations and Flow, Transportation Research Record 1948, pages 170-176 [29]

T. Maze, M. Agarwal, and G. Burchett

Iowa State University

Weather affects many aspects of transportation, but three dimensions of weather impact on highway traffic are predominant and measurable. Inclement weather affects traffic demand, traffic safety, and traffic flow relationships. Understanding these relationships will help highway agencies select better management strategies and create more efficient operating policies. For example, it was found that severe winter storms bring a higher risk of being involved in a crash by as much as 25 times – much higher than the increased risk brought by behaviors that state governments already have placed sanctions against, such as speeding or drunk driving. Given the heightened risk of drivers’ involvement in a crash, highway agencies might wish to manage better and restrict use of highways during times of extreme weather, to reduce safety costs and costs associated with rescuing stranded and injured motorists in the worst weather conditions. However, the first step in managing the transportation systems to minimize the weather impact is to quantify its impact on traffic. This paper reviews the literature and recent research work conducted by the Center for Transportation Research and Education on the impact of weather on traffic demand, traffic safety, and traffic flow relationships. Included are new estimates of capacity and speed reduction due to rain, snow, fog, cold, and wind by weather intensity levels (e.g., snowfall rate per hour).

Category 3 – This paper includes a literature search that compiles and summarizes research on the impact of adverse weather on crash rates and traffic flow.

Temporary Losses of Highway Capacity and Impacts on Performance: Phase 2, ORNL/TM‑2004/209 [30]

S. M. Chin, O. Franzese, R. C. Gibson, D. L. Greene, and H. L. Hwang

University of Tennessee

This report describes the second phase of the Temporary Losses of Capacity (TLC) study (TLC2). Oak Ridge National Laboratory, sponsored by the FHWA, made an initial attempt to provide nationwide estimates of the capacity losses and delay caused by temporary capacity-reducing events (Chin et al. 2002). This study, called the Temporary Loss of Capacity (TLC) study, estimated capacity loss and delay on freeways and principal arterials resulting from fatal and nonfatal crashes, vehicle breakdowns, and adverse weather, including snow, ice, and fog. In addition, it estimated capacity loss and delay caused by suboptimal signal timing at intersections on principal arterials. It also included rough estimates of capacity loss and delay on Interstates due to highway construction and maintenance work zones. TLC2 improves upon the first study by expanding the scope to include delays from rain, toll collection facilities, railroad crossings, and commercial truck pickup and delivery (PUD) activities in urban areas. It includes estimates of work zone capacity loss and delay for all freeways and principal arterials, rather than for Interstates only. It also includes improved estimates of delays caused by fog, snow, and ice, which are based on data not available during the initial phase of the study. Finally, computational errors involving crash and breakdown delay in the original TLC report are corrected.

Category 3 – This report was part of a research effort to estimate TLC on a national basis. Weather was only one of a wide range of factors examined. Others include breakdowns, construction activity crashes, and poor signal timing.

Analysis of Impact of Adverse Weather on Freeway Free-Flow Speed in Spain, TRB 89th Annual Meeting Compendium of Papers DVD, 10‑2195 [1]

F. Torregrosa, A. Garcia and E. Esplugues

“Spain”

Polytechnic University of Valencia, Spain

The paper investigates the effect of different weather conditions on the traffic speed and flow for different freeways in Spain. It provides direct measurement of traffic conditions at 15‑minute intervals under a variety of weather conditions.

Status – A sample of the data were obtained and reviewed for this project. The results of that review are documented in Section 3.2.

Comparison of Driving Behavior and Safety in Car-Following Platoons Under Icy and Dry Surface Conditions, TRB 89th Annual Meeting Compendium of Papers DVD, 10‑0504 [2]

M. Tanaka, and
P. Ranjitkat

“New Zealand”

T. Nakatsuji

“Japan”

University of Auckland,
Hokkaido University

This study addressed car-following behavior under icy conditions in a test track environment. This data was recommended for further evaluation since data on car-following behavior in icy conditions is very difficult to find. In addition, this research was conducted under very rigorous conditions, providing a high level of confidence in the results.

Status – The authors provided the data to the study team and an analysis was conducted that was documented in the report “Microscopic Analysis of Traffic Flow in Inclement Weather: Impact of Icy Roadway Conditions on Driver Car-Following Behavior,” prepared for FHWA by Virginia Tech Transportation Institute and Cambridge Systematics, February 2010.

Variation in Impact of Cold Temperature and Snowfall and Their Interaction on Traffic Volumes, TRB 89th Annual Meeting Compendium of Papers DVD, 10-3182 [3]

S. Datla

“Canada”

University of Regina

This paper investigates the effect of snow and cold on traffic flow variation using empirical weather and traffic flow data; providing the data could be relevant if it will be related to the freeway capacity and car-following models.

This report was recommended for evaluation pending further review since models developed for WRTM strategies need to take into account reductions in overall volume that may occur due to adverse weather. It appears this research successfully modeled this relationship in Alberta.

Status – While the paper provided some useful parameters, the authors could not be reached to obtain the full dataset.

Assessing the impact of weather on traffic intensity, TRB 87th Annual Meeting Compendium of Papers DVD, 08‑1903 [7]

M. Cools, E. Moons,
and G. Wets

“Belgium”

Transportation Research Institute, Hasselt University

This is a study that used detailed, empirical measurements of traffic and weather conditions to address adverse weather impacts. As it parallels some of the macroscopic research being conducted through the WRTM, this dataset could be useful for review and analysis.

Status – This dataset was recommended for further analysis, but was unavailable due to confidentiality restrictions.

Multilevel Assessment of the Impact of Rain on Drivers’ Behavior: Standardized Methodology and Empirical Analysis, Transportation Research Record No. 2107 [5]

R. Billot, N. El Faouzi,
and F. De Vuyst

“France”

Institut National de Recherche sur les Transports et leur Securite (INRETS), Ecole Centrale de Paris

This study deals with the analysis of the impact of rain on drivers’ behavior and traffic operations. First, a generic methodology for assessing the effect of weather on traffic is proposed through a multilevel approach: from individual traffic data, the rain impact is assessed at a microscopic level (time, headways, and spacing). Next, the same data were used to extend the study to a mesoscopic and a macroscopic level. The mesoscopic level deals with the effects of rain on platoons, and the macroscopic level resides in the analysis of the impact of rain on the fundamental diagram enabling weather-responsive macroscopic traffic simulation. Second, following this approach, an empirical study is carried out from individual data collected on a French interurban motorway. Weather data were provided by a weather station located near the test site. The results suggest a significant impact of rain on drivers’ behavior and traffic operations, which increases with the intensity of rainfall.

This study involved a simulation effort. The impact of rain on traffic flow at microscopic level was estimated using data from a French interurban motorway. The test site included a nearby weather station.

Status – The detailed dataset was requested but unavailable due to confidentiality restrictions.