Lekshmi Sasidharan

Application of propensity scores and potential outcomes to estimate effectiveness of traffic safety countermeasures: Exploratory analysis using intersection lighting data

More than 5.5 million police-reported traffic crashes occurred in the United States in 2009, resulting in 33,808 fatalities and more than 2.2 million injuries. Significant funds are expended annually by federal, state, and local transportation agencies in an effort to reduce traffic crashes. Effective safety management involves selecting highway and street locations with potential for safety improvements; correctly diagnosing safety problems; identifying appropriate countermeasures; prioritizing countermeasure implementation at selected sites; and, evaluating the effectiveness of implemented countermeasures. Accurate estimation of countermeasure effectiveness is a critical component of the safety management process. In this study, a statistical modeling framework, based on propensity scores and potential outcomes, is described to estimate countermeasure effectiveness from non-randomized observational data. Average treatment effects are estimated using semi-parametric estimation methods. To demonstrate the framework, the average treatment effect of fixed roadway lighting at intersections in Minnesota is estimated. The results indicate that fixed roadway lighting reduces expected nighttime crashes by approximately 6%, which compares favorably to other, recent lighting-safety research findings.

Partial proportional odds model—An alternate choice for analyzing pedestrian crash injury severities

The conventional methods for crash injury severity analyses include either treating the severity data as ordered (e.g. ordered logit/probit models) or non-ordered (e.g. multinomial models). The ordered models require the data to meet proportional odds assumption, according to which the predictors can only have the same effect on different levels of the dependent variable, which is often not the case with crash injury severities. On the other hand, non-ordered analyses completely ignore the inherent hierarchical nature of crash injury severities. Therefore, treating the crash severity data as either ordered or non-ordered results in violating some of the key principles. To address these concerns, this paper explores the application of a partial proportional odds (PPO) model to bridge the gap between ordered and non-ordered severity modeling frameworks. The PPO model allows the covariates that meet the proportional odds assumption to affect different crash severity levels with the same magnitude; whereas the covariates that do not meet the proportional odds assumption can have different effects on different severity levels. This study is based on a five-year (2008-2012) national pedestrian safety dataset for Switzerland. A comparison between the application of PPO models, ordered logit models, and multinomial logit models for pedestrian injury severity evaluation is also included here. The study shows that PPO models outperform the other models considered based on different evaluation criteria. Hence, it is a viable method for analyzing pedestrian crash injury severities.

Exploring the Association between Traffic Safety and Geometric Design Consistency Based on Vehicle Speed Metrics

AbstractPast design consistency research has demonstrated the relationship between operating speeds and geometric design features on two-lane rural highways. However, little is known about the relationship between geometric design consistency and traffic safety. In this study, design consistency is referred to as the difference between operating speed and inferred design speed, and design consistency density is measured to account for the effect of elements upstream and downstream of the study element. To perform the design consistency–safety evaluation in the present study, geometric design, roadway inventory, crash, and operating speed data were collected along two case-study highways in central Pennsylvania (U.S. 322 and PA 350). Several count regression model formulations were used to explore the statistical association between design consistency and total crash frequency. A statistically significant positive association between geometric design consistency and safety was found. Design consistency sur...

Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland

One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses.

Use of Pavement Marking Degradation Models to Develop a Pavement Marking Management System

The Pennsylvania Department of Transportation collected periodic pavement marking retroreflectivity data on 88 roadway segments over a 1-year period from May 2007 through May 2008. The purpose of this effort was to use the data collected to develop a series of pavement marking degradation models that could be used to implement a management system. In this study, panel data models were used to estimate the service life of both waterborne and epoxy pavement markings because of the repeated retroreflectivity measurements recorded over time. It was found that pavement marking retroreflectivity decreases as the age of both epoxy and waterborne-paint pavement markings increase. White pavement markings were shown to have higher estimated service lives than yellow pavement markings. Traffic exposure was found to be negatively correlated with pavement marking retroreflectivity in the waterborne-paint analysis, but traffic exposure was not statistically significant in the epoxy pavement marking retroreflectivity model. A life cycle cost analysis showed that waterborne paints are more cost-effective than epoxy pavement markings if applied on a statewide basis.

Application of partial proportional odds model for analyzing pedestrian crash injury severities in Switzerland

ABSTRACT According to the Swiss Microcensus, Switzerland is a place where people choose to walk more than 40% of their daily trip time, resulting in a higher pedestrian crash to total crash ratio when compared to many other developed countries. Furthermore, the high number of old and young pedestrians as well as the large number of pedestrian crashes with higher levels of severity makes the pedestrian crash analysis for Switzerland very important. This study aims to identify the important factors that influence the injury severity levels of pedestrian–vehicle crashes in Switzerland. To address this we employ a partial proportional odds model to analyze pedestrian crash injury severities in Switzerland, based on the 5-year (2008–2012) pedestrian safety data. The study also focuses on a separate analysis for two vulnerable groups of pedestrians (young and old pedestrians) to examine the change in the influence of factors over age. The analysis involves an extensive evaluation based on pedestrian and driver characteristics; main reason for the crash; traffic, temporal, vehicle, roadway geometric and environmental characteristics. The study shows that irrespective of age, dark unlighted areas, sight obstructions, midblock crossings and heavy vehicles adversely affect the injury severity levels of pedestrians.