Xiaoduan Sun

Quantifying Crash Risk under Inclement Weather with Radar Rainfall Data and Matched-Pair Method

Driving risk under inclement weather has long been considered higher than that under normal weather conditions. Among several weather variables, rainfall is recognized as a critical one that affects traffic crash occurrences. Heavy rainfall often results in reduced visibility, increased stopping distances, hydroplaning, and loss of control of the vehicle. The lack of an accurate, quantitative representation of rainfall effects at a fine resolution has been a problem in past highway safety research on adverse weather. This study used radar rainfall data from the National Weather Services WSR-88D NEXRAD Doppler Radar system that provides a comprehensive data set with large spatial coverage, high spatial resolution (in the order of few kilometers), and continuous temporal sampling to quantify the relative crash risk with a matched-pair method. Four different types of highways were selected for analysis over a 4-year time period. Each highway was divided into segments based on a fine resolution of rainfall data. The results of our analysis have indicated a higher crash risk and a higher injury risk during rain. The magnitude of the risk varies depending upon the type of highway, location of the highway, time of day, crash severity, and crash characteristics. Unlike previous studies, this project was able to identify the risk variations by type of highway and by segment because of the fine resolution of the data. The knowledge acquired by this study can be used to identify effective crash countermeasures.

Factor Association with Multiple Correspondence Analysis in Vehicle–Pedestrian Crashes

In the United States, about 14% of total crash fatalities are pedestrian related. In 2012, 4,743 pedestrians were killed, and 76,000 pedestrians were injured in vehicle–pedestrian crashes in the United States. Vehicle– pedestrian crashes have become a key concern in Louisiana as a result of the high percentage of fatalities there in recent years. In 2012, pedestrians accounted for 17% of total crash fatalities in the state. This study used multiple correspondence analysis (MCA), an exploratory data analysis method used to detect and represent underlying structures in a categorical data set, to analyze 8 years (2004 to 2011) of vehicle–pedestrian crashes in Louisiana. Pedestrian crash data are best represented as transactions of multiple categorical variables, so the use of MCA was a unique choice to determine the relationship of the variables and their significance. The findings indicated several nontrivial focus groups (e.g., drivers with high-occupancy vehicles, female drivers in bad weather conditions, and drivers distracted by mobile phone use). The associated geometric factors were hillcrest roadways, dip or hump aligned roadways, roadways with multiple lanes, and roadways with no lighting at night. Male drivers were seen to be relatively susceptible to severe and moderate injury crashes. Fatal pedestrian crashes were correlated to two-lane roadways with no lighting at night. The MCA method helped measure significant contributing factors and degrees of association between the factors through the analysis of the systematic patterns of variation with categorical data sets of pedestrian crashes. The findings from this study will help transportation professionals improve countermeasure selection strategies.

Speed Difference and Its Impact on Traffic Safety of One Freeway in China

Although speed differential has long been recognized as a contributing factor to highway crashes, its relationship with crash rate has not been quantitatively established. An analysis of the crash data collected from the Jingjintang Expressway, one of the first freeways to be built in China, reveals a clear association between speed gap and crash rate. A difference in average operating speed between large and small vehicles of 10 to 15 km/h, reflecting a specific traffic composition, is associated with an unusually high crash rate. The speed differential problem is worse in developing countries because of the huge demand for freight transportation. Overloading is a common problem on highways. Heavily loaded trucks cannot reach the minimum freeway speed and so cause other vehicles to change lanes frequently; the situation consequently increases crash risks. Analysis results strongly suggest that managing the speed gap between large and small vehicles would be the most crucial step in combating the highway crash problem.

Investigation on the wrong way driving crash patterns using multiple correspondence analysis

Wrong way driving (WWD) has been a constant traffic safety problem in certain types of roads. Although these crashes are not large in numbers, the outcomes are usually fatalities or severe injuries. Past studies on WWD crashes used either descriptive statistics or logistic regression to determine the impact of key contributing factors. In conventional statistics, failure to control the impact of all contributing variables on the probability of WWD crashes generates bias due to the rareness of these types of crashes. Distribution free methods, such as multiple correspondence analysis (MCA), overcome this issue, as there is no need of prior assumptions. This study used five years (2010-2014) of WWD crashes in Louisiana to determine the key associations between the contribution factors by using MCA. The findings showed that MCA helps in presenting a proximity map of the variable categories in a low dimensional plane. The outcomes of this study are sixteen significant clusters that include variable categories like determined several key factors like different locality types, roadways at dark with no lighting at night, roadways with no physical separations, roadways with higher posted speed, roadways with inadequate signage and markings, and older drivers. This study contains safety recommendations on targeted countermeasures to avoid different associated scenarios in WWD crashes. The findings will be helpful to the authorities to implement appropriate countermeasures.

Text Mining and Topic Modeling of Compendiums of Papers from Transportation Research Board Annual Meetings

The collective knowledge system has been advancing rapidly in the recent past. The digitalization of information in many online media—such as blogs, social media, articles, webpages, images, audios, and videos—provides an unprecedented opportunity for the extraction and identification of a knowledge trend. Prominent journal and conference proceedings usually contain extensive amounts of textual data that can be used to examine the research trends for various topics of interest and to understand how this research has helped in the advancement of a subject such as transportation engineering. The exploration of the unstructured contents in journal or conference papers requires sophisticated algorithms for knowledge extraction. This paper presents text mining techniques to analyze compendiums of papers published from TRB annual meetings, the largest and most comprehensive transportation conferences in the world. Topic models are algorithms designed to discover hidden thematic structure from massive collections of unstructured documents. This study used a popular topic model, latent Dirichlet allocation, to reveal research trends and interesting histories of the development of research by analyzing 15,357 compendiums of papers from 7 years (2008 to 2014) of TRB annual meetings.

Investigating Safety Impact of Edgelines on Narrow, Rural Two-Lane Highways by Empirical Bayes Method

Narrow, rural two-lane highways are mostly characterized by low design features, light traffic volumes with high crash rates, and particularly high fatal crash rates. About 5,000 mi of these highways are administered by the Louisiana Department of Transportation and Development. Run-off-roadway (ROR) crashes are the most common type of crashes on narrow, rural two-lane highways. Because the Manual on Uniform Traffic Control Devices does not require edgelines, edgelines are not found on many such highways because of their low traffic volumes. There are two main concerns for edgeline implementation on narrow two-lane highways: the potential increase in head-on collisions and the added maintenance cost to the already constrained annual maintenance budget. The second part of a study that evaluated the safety impact of edgelines on narrow, rural two-lane highways in Louisiana is presented. On the basis of data collected from 10 locations, the first part of the study proved that edge lines centralized the lateral position of vehicles. This second part of the study evaluated the safety performance before and after the implementation of edgelines on roadway segments selected from all Louisiana districts. By using the empirical Bayes method, the study showed that edgeline implementation significantly reduced expected crash frequencies. Edgeline implementation reduced ROR crashes as well as head-on crashes. The implementation of edgelines benefited primarily male drivers and young drivers. Because of the crash-decreasing trend observed in the 3-year period classified as the after period in this study, the final estimated crash modification factor was 0.85 with a standard deviation of 0.039. The high benefit–cost ratio strongly supports edgeline implementation on narrow, rural two-lane highways in Louisiana.

Characteristics of Traffic Crashes on Freeways in China: Case Study of Jingjintang Expressway

As China feverishly builds one of the largest freeway systems in the world to meet its ever-increasing demand for highway transportation–stimulated by the unprecedented economic boom–traffic safety has become a serious concern. The problem of more than 100,000 annual traffic fatalities is threatening the countrys sustainable economic development. The significant differences in road user behavior, level of motorization, traffic enforcement practice, roadside design criteria, and economic development stage make the characteristics of traffic crashes in China somewhat different from those in developed countries. To reduce traffic crashes it is important to investigate what, when, how, and why those crashes occurred. This paper introduces a highway safety project conducted on Jingjintang Expressway, one of the first freeways built in China. Results of the study show that, among other factors, the speed differential between cars and large vehicles is a main cause of high crash fatalities, particularly for rear-end collisions. The lack of real-time enforcement, problematic driver behavior, and substandard roadside design, as well as overloaded trucks all contribute heavily to traffic crashes on Chinas freeways.

Trends in Transportation Research: Exploring Content Analysis in Topics

Proceedings of journal and conference papers are good sources of big textual data to examine research trends in various branches of science. The contents, usually unstructured in nature, require fast machine-learning algorithms to be deciphered. Exploratory analysis through text mining usually provides the descriptive nature of the contents but lacks quantification of the topics and their correlations. Topic models are algorithms designed to discover the main theme or trend in massive collections of unstructured documents. Through the use of a structural topic model, an extension of latent Dirichlet allocation, this study introduced distinct topic models on the basis of the relative frequencies of the words used in the abstracts of 15,357 TRB compendium papers. With data from 7 years (2008 through 2014) of TRB annual meeting compendium papers, the 20 most dominant topics emerged from a bag of 4 million words. The findings of this study contributed to the understanding of topical trends in the complex and evolving field of transportation engineering research.

Supervised association rules mining on pedestrian crashes in urban areas: identifying patterns for appropriate countermeasures

ABSTRACT In 2011, 4,432 pedestrians were killed (14% of total traffic crash fatalities), and 69,000 pedestrians were injured in vehicle-pedestrian crashes in the United States. Particularly in Louisiana, vehicle-pedestrian crashes have become a key concern because of the high percentage of fatalities in recent years. In 2012, pedestrians were accounted for 17% of all fatalities due to traffic crashes in Louisiana. Alcohol was involved in nearly 44% of these fatalities. This research utilized ‘a priori’ algorithm of supervised association mining technique to discover patterns from the vehicle-pedestrian crash database. By using association rules mining, this study aims to discover vehicle-pedestrian crash patterns using eight years of Louisiana crash data (2004–2011). The results indicated that roadway lighting at night helped in alleviating pedestrian crash severity. In addition, a few groups of interest were identified from this study: male pedestrians’ greater propensity towards severe and fatal crashes, younger female drivers (15–24) being more crash-prone than other age groups, vulnerable impaired pedestrians even on roadways with lighting at night, middle-aged male pedestrians (35–54) being inclined towards crash occurrence, and dominance of single vehicle crashes. Based on the recognized patterns, this study recommends several countermeasures to alleviate the safety concerns. The findings of this study will help traffic safety professionals in understanding significant patterns and relevant countermeasures to raise awareness and improvements for the potential decrease of pedestrian crashes.

Four-Lane to Five-Lane Urban Roadway Conversions for Safety

Undivided roadways have consistently exhibited low safety performance, particularly in urban or suburban areas where roadside development is relatively intense. Changing a four-lane undivided road to a divided roadway by either building a boulevard cross-section or installing a physical barrier is a desirable option to improve safety performance of an undivided roadway, but it requires significant resources. This article introduces a crash countermeasure successfully implemented on two different segments of undivided roadways in Louisiana. This crash countermeasure is to change an undivided four-lane roadway to a five-lane roadway with a center lane for left turns by restriping pavement markings without increasing pavement width. Although the five-lane roadway is no longer an acceptable roadway type in Louisiana, the impressive crash reductions on both roadway segments demonstrate it is a feasible solution under constrained conditions. Based on the statistical analysis with 6 years of crash data (3 years before and 3 years after excluding the implementation year), the crash modification factors for both roadways are estimated to be less than 0.5 with a standard deviation less than 0.07. Although it is not surprising to see the biggest crash reduction comes from the rear-end collisions, the other types of collision are also reduced.