Estimation of bicycle crash modification factors (CMFs) on urban facilities using zero inflated negative binomial models

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities.

Development of crash modification factors for changing lane width on roadway segments using generalized nonlinear models

Developing crash modification functions to assess safety effects of adding bike lanes for urban arterials with different roadway and socio-economic characteristics

The continuous growth of automobile traffic on urban and suburban arterials in recent years has created a substantial problem for transit, especially when it operates in mixed traffic conditions. As a result, there has been a growing interest in deploying Transit Signal Priority (TSP) to improve the operational performance of arterial corridors. TSP is an operational strategy that facilitates the movement of transit vehicles (e.g., buses) through signalized intersections that helps transit service be more reliable, faster, and more cost-effective. The goal of this research was to quantify the mobility and safety benefits of TSP. A microscopic simulation approach was used to estimate the mobility benefits of TSP. Microscopic simulation models were developed in VISSIM and calibrated to represent field conditions. Implementing TSP provided significant savings in travel time and average vehicle delay. Under the TSP scenario, the study corridor also experienced significant reduction in travel time and average vehicle delay for buses and all other vehicles. The importance and benefits of calibration of VISSIM model with TSP integration were also studied as a part of the mobility benefits. Besides quantifying the mobility benefits, the potential safety benefits of the TSP strategy were also quantified. An observational before-after full Bayes (FB) approach with a comparison-group was adopted to estimate the crash modification factors (CMFs) for total crashes, fatal/injury (FI) crashes, property damage only (PDO) crashes, rear-end crashes, sideswipe crashes, and angle crashes. The analysis was based on 12 corridors equipped with the TSP system and their corresponding 29 comparison corridors without the TSP system. Overall, the results indicated that the deployment of TSP improved safety. Specifically, TSP was found to reduce total crashes by 7.2% (CMF = 0.928), FI crashes by 14% (CMF = 0.860), PDO crashes by 8% (CMF = 0.920), rear-end crashes by 5.2% (CMF = 0.948), and angle crashes by 21.9% (CMF = 0.781). Alternatively, sideswipe crashes increased by 6% (CMF = 1.060), although the increase was not significant at a 95% Bayesian credible interval (BCI). These results may present key considerations for transportation agencies and practitioners when planning future TSP deployments.

Bicycle crash contributory factors: A systematic review

Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data

Using multivariate adaptive regression splines (MARS) to develop crash modification factors for urban freeway interchange influence areas

Pedestrian and bicycle safety is among the top priorities of many departments of transportation (DOTs), and speeding is a major cause of pedestrian injuries and fatalities. This study investigated the impacts of traffic signal progression speed management and progression quality on the safety of pedestrians and bicyclists. A cross-sectional study design was used to estimate the random parameter negative binomial models and the safety effects of these measures. The study findings show the pronounced impacts of well-designed progression speed management with good progression quality on reducing the frequency and severity of pedestrian and bicycle crashes. Improving poor progression speed management to good or great progression speed management with signal retiming can reduce pedestrian and bicycle crash frequency by 55% and severe pedestrian and bicycle crashes by 75%. Improving poor progression quality to good progression quality can decrease pedestrian and bicycle crash frequency by 52% and severe pedestrian and bicycle crashes by 72%.

Cycling is a cheap and flexible mean of transportation which holds many benefits in terms of personal and public health. However, it still holds risks in term of safety. Several studies have explored factors related to cycling use and cycling safety, but many authors argued that psychosocial factors are still somewhat neglected in cycling studies. The present thesis attempts to address these issues to yield insights that policymakers and professionals can use. Our work comprises four studies. In Study 1, we attempted to identify cyclists' clusters based on cycling motivation and patterns at a European level and profiled the membership to each cluster according to socio-demographics and attitudes. We showed that cycling patterns and habits are linked to culture as well as attitudes and evaluation of the cycling environment, explicitly highlighting the importance of the feeling of discomfort in mixed traffic and the evaluation of cycling infrastructures. In Study 2 we focused on inequalities of the population in bicycle use, particularly investigating gender differences. We found gender differences in attitudes towards cycling to be small in terms of effect size or non-significant, with women having more positive attitudes in personal benefits rather than mobility benefits. In Study 3 we investigated gender differences in bicycle crashes, using routinely recorded crash data. Results revealed that, compared to women, men were more likely to be involved in a crash regardless the age. Lastly, in Study 4 we aimed to investigate the role of attitudes, e-bike use, and perception of driving behaviour of motorists in predicting bicycle crash involvement and severity while controlling for various factors. Bicycle crash severity was associated with lower affective attributes, higher instrumental attributes, and the perception of good driving behaviour of motorists. In the last chapter of the thesis, we discussed the theoretical and practical implication of our results.

Macroscopic spatial analysis of pedestrian and bicycle crashes

In Nigeria, literature on the integration of traffic of pavement condition and traffic characteristics in predicting road traffic accident frequency on 2-lane highways are scanty, hence this article to fill the gap. A comparison of road traffic accident frequency prediction models on IIesha-Akure-Owo road based on the data observed between 2012 and 2014 is presented. Negative Binomial (NB), Ordered Logistic (OL) and Zero Inflated Negative Binomial (ZINB) models were used to model the frequency of road traffic accident occurrence using road traffic accident data from the Federal Road Safety Commission (FRSC) and pavement conditions parameters from pavement evaluation unit of the Federal Ministry of Works, Kaduna. The explanatory variables were: annual average daily traffic (aadt), shoulder factor (sf), rut depth (rd), pavement condition index (pci), and international roughness index (iri). The explanatory variables that were statistically significant for the three models are aadt, sf and iri with the estimated coefficients having the expected signs. The number of road traffic accident on the road increases with the traffic volume and the international roughness index while it decreases with shoulder factor. The systematic variation explained by the models amounts to 87.7, 78.1 and 74.4% for NB, ZINB and OL respectively. The research findings suggest the accident prediction models that should be integrated into pavement rehabilitation.
 
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This paper presents a detailed analysis of the temporal transferability of heterogeneous overdispersion parameter negative binomial models for crash severity types in California. The Furnival–Wilson leaps and bounds algorithm was used to identify optimal safety performance function specifications. The overdispersion parameter was allowed to vary across roadway segments as a function of roadway geometrics. Sixty models were developed for five major severity outcomes for homogeneous roadway segments for each of the periods 2005 to 2010, 2011 to 2012, and 2005 to 2012. Model transferability tests were conducted with likelihood ratio tests, and it was determined that temporal transferability rates (from the 2005–2010 period to the 2011–2012 period) were poor. The findings indicate the potential time instability of safety performance function parameters. The analysis found a higher rate of transferability for rural safety performance functions compared with urban safety performance functions. The rate of transferability was highest for severe injury and fatal injury. This result shows that the role of the overdispersion parameter in the transferability of safety performance functions must be considered. The absence of information on changes in economic, environmental, vehicle fleet, and driver population data limits the specification of the overdispersion parameter to roadway geometrics. Although it is an improvement over the current practice of the use of a constant overdispersion parameter, economic, environmental, and vehicle–driver population data might be useful for improving model transferability over time. The implications are that safety analysis methods such as crash modification factors, network screening, and excess crash estimations must take into account parameter variability over time.

This paper describes the efforts to evaluate the safety impacts of increasing the speed limit from 55 mph to 60 mph on selected two-lane, two-way state highway road segments in Minnesota, U.S. An empirical Bayes (EB) before–after analysis was used to estimate crash modification factors (CMFs) for both segments (1,909.11 mi) and intersections (1,722 3-leg and 1,191 4-leg). Aggregate analysis conducted using all the segment and intersection data showed a 2.9% increase in total crashes, a 2.5% increase in injury (KABC) crashes, and a 0.05% reduction in the injury (KAB) crashes. These results—along with before-and-after operating speed data from another study by Minnesota Department of Transportation (MnDOT) (2019) showing that the 85th percentile operating speed remained the same and that the mean operating speeds increased by 1 mph following the speed limit increase—can lead to a conclusion that the speed limit increase from 55 mph to 60 mph had a minor effect on combined segment and intersection crashes or operating speeds. It is important to note that these results are specific to the corridors that were selected by MnDOT for the increase in speed limit; caution must be exercised when extending these to systemwide increases in speed limits in Minnesota or in other states, and when estimating long-term effects of speed limit increases as operating speeds can change over a longer period of time.

There is a need to better understand and quantify the safety implications of geometric improvements and countermeasures. A commonly accepted measure of safety effectiveness is the crash modification (CMF) defined as the expected number of crashes with a countermeasure divided by the number expected without the countermeasure. This paper evaluates the use of a case-control design to directly estimate the safety effectiveness of lane and shoulder width using the odds ratio: the probability of a crash with the countermeasure divided by the probability of a crash without a countermeasure. The case-control design is well established in epidemiology where it is used to relate factors within a study population to a particular or disease. In the highway safety context, the outcome is defined as a crash, the risk factor is a particular geometric feature or countermeasure and the subjects are roadway segments. This paper describes the of an experiment in which commonly available crash, roadway and traffic data are used to estimate odds ratios which are compared to CMFs from the literature. The comparison of these slightly different effectiveness measures are intended as a test of the efficacy of the case-control method in safety effectiveness evaluation. Geometric, traffic and crash data were obtained for more than 28,000 rural two-lane undivided highway segments in Pennsylvania for years 1997 to 2001 inclusive. A matched case-control design is developed to estimate the safety effectiveness of different lane and shoulder widths while adjusting for the confounding variables: speed limit, average daily traffic and segment length. Conditional logistic regression models are developed to estimate the odds ratio for lane and shoulder width separately. Lane and shoulder width odds ratios compare favorably to CMFs from the literature and have the additional advantage of including confidence intervals on the estimates. The paper concludes with a discussion of strengths and weaknesses of the method and recommendations for future research.

Bicycling is becoming increasingly popular in Oregon and the US in general due to its environment friendliness as well as health benefits. With Oregon's population projected to increase by more than 30% over the next 30 years, improving the safety of the transportation network for persons on bicycles is important. In Oregon, majority of the bicyclist crashes occur at intersections. This thesis seeks to identify the determinant factors that significantly impact bicyclist crash injury severity at intersections. A mixed logit framework that accounts for any unobserved heterogeneity in the data and allows the estimated parameters to randomly vary across observations was applied to three years of bicyclist crash data (2016-2018) with a total of 1502 categorized crashes in Oregon at both unsignalized and signalized intersections. This work reports the relative risk of bicyclist injury severity instead of the absolute injury risk in a bicyclist crash. As part of identifying the significant determinant factors, a parameter transferability test is done to determine that the two types of intersection need to be modeled separately. A total of fourteen variables were found to be significant at unsignalized intersections. Wearing a helmet reduces the probability of slight injury while urban area, winter season, and bicyclists with age 10 or younger have higher chance of slight injury. Clear weather, male bicyclists, speeding, presence of traffic control device, and non-motorist being on a bike lane at intersection have increased likelihood of non-incapacitating injury while crash year 2018 shows lower probability of this injury level. In terms of injury severity, bicyclists of age 65 or older, use of alcohol, and angled collision are associated with high risk for incapacitating and fatal injuries and evening peak hours reduces the likelihood of this injury type. The mixed logit model for crash analysis at signalized intersections found eight significant variables impacting bicyclist crash severity. Using helmet, bicyclists in the age range 26-35 years, spring season, and clear weather lead to decreased likelihood of slight injury; however, driver's failure to yield right of way increases the probability of slight injury. Crashes occurring at cross-signalized intersections have lower probability of non-incapacitating injuries. Speeding-involved crashes significantly increase the chance of incapacitating and fatal injuries and bicyclists traveling straight is associated with lower risk for incapacitating/fatal injuries. Based on these findings, several countermeasures to improve bicyclist safety are recommended.