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

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

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

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.

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

Reducing vehicle lane widths has been proposed as an effective strategy to decrease vehicle speeds and enhance road safety. However, the safety benefits of narrower travel lanes remain a topic of debate due to mixed findings in the literature. This study examines the relationship between lane width, vehicle speed, and crash occurrence to comprehensively understand their impact on road safety and transportation planning. Using data from 320 urban arterial sections in Utah, the analysis reveals that narrower lane widths are associated with reduced vehicle speeds. For every additional foot of lane width, 85th and 95th percentile speeds increase by 1.012 mph and 1.088 mph, respectively. Furthermore, injury crash modeling indicates that a one-foot increase in lane width is associated with a 38.3% increase in the odds of an injury crash on a roadway section. These findings contribute to the growing evidence supporting the implementation of narrower lane widths as a strategy to improve road safety, foster multimodal infrastructure, and promote sustainable urban transportation systems. We recommend that UDOT adopt a minimum lane width of 10 or 11 feet for arterials in highly urbanized areas, such as downtowns and major activity centers.

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.

Driving speed and the risk of road crashes: A review

HighlightsWhat are the main findings?Using 11,399 OpenBikeSensor (OBS) overtaking records linked to Austria’s national GIS road graph (GIP), the study reveals statistically robust patterns in lateral passing distance (LPD) between motor vehicles and cyclists related to infrastructure.LPD is significantly higher in rural areas than in urban ones, with compliance to Austria’s 2023 legal thresholds averaging ~40% in cities (≥1.5 m) and ~19% in rural areas (≥2.0 m). Small but consistent positive correlations were found between LPD and lane width, speed limit, and functional road class.What are the implications of the main findings?The results highlight that road geometry and network hierarchy shape overtaking safety, emphasising the need for more explicit cyclist allocation and physical separation in constrained or high-speed environments.The study demonstrates how sensor-based, GIS-linked nonparametric analysis can support evidence-based road design and policy evaluation regarding safe passing distances.Lateral passing distance (LPD) when motor vehicles overtake cyclists is a key safety metric, yet infrastructure-aware evidence remains limited. This study analyses 11,399 overtaking measurements from Austria’s OpenBikeSensor (OBS) project, spatially linked to the national road graph (GIP), with urban and rural networks examined separately. LPD was treated as a continuous dependent variable, and bivariate relationships were tested using nonparametric methods: Spearman’s rho/Kendall’s tau for metric predictors (speed limit, lane width, number of lanes) and Kruskal–Wallis tests with Dunn–Holm post hoc adjustments for categorical factors (Functional Road Class, Road Configuration, Infrastructure Type). Effect sizes and confidence intervals supported substantive interpretation. LPD was higher in rural than urban contexts, with compliance to Austria’s 2023 legal thresholds averaging 40% in cities (≥1.5 m) and 19% in rural areas (≥2.0 m). Positive correlations were found between LPD and lane width, speed limit, and functional class. The findings highlight infrastructure-sensitive patterns in sensor-generated LPD and emphasise the importance of clear cyclist allocation or physical separation, especially where high speeds or spatial constraints increase close-passing risk.

Construction of the bypass lanes at rural intersections has usually been considered as a low cost way to improve safety. Crash Modification Factor (CMF) is an acceptable measure for evaluating the safety effectiveness of a countermeasure, which is defined as the expected number of crashes with a countermeasure divided by the number of crashes expected without the countermeasure. This study evaluates the use of a case-control method to estimate CMF for safety effectiveness of the construction of bypass lanes at unsignalized rural intersections in the state of Kansas. In addition to looking at a number of crashes at each intersection, this study evaluates the changes in crash rate and crash severity at intersections with the bypass lane versus intersections without it. Crash data were obtained for more than 700 rural unsignalized intersections from the Kansas Crash Database which is maintained by the Kansas Department of Transportation (KDOT) for the years 2009 to 2011. The paper concludes that the expected number of crashes is lower at intersections with bypass lanes in comparison to intersections without bypass lanes, while it has no significant effect on reducing crash severity.

Traffic collision on the highway has become a serious issue because they delay the sustainable development of society. Highway accidents on I-69 have one of the highest crash rates in the U.S. in Michigan and a higher fatality rate than average. This study aimed to identify the factors contributing to highway user crashes on I-69 in Flint, Michigan. This study also aims to find the relationship between the change in the speed limit in certain weather conditions and the number of crashes that are likely to occur as a sequence of this change. A multi-user driving simulator is applied in this study with ten driving simulator scenarios. The multinomial logistic regression (MNL) model has been investigated in this study to identify statistically significant factors that contribute to crashes. The analyses indicated that speeding and speed limits during inclement road/weather conditions significantly affected crashes. Most frequent crashes occur during snowy and icy weather conditions and by changing the speed limit during these weather conditions. Therefore, driver speed is suspected to be the most factor that caused the Vehicle crash on I-69. The method of developing Crash modification factors (CMFs) used in this study will help to reduce crashes and improve traffic system safety performance on highways in Michigan.

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.

The objective of this study was to identify the influencing factors of road traffic crash rates from the perspective of access management techniques in urban areas. The target areas are located in the Las Vegas metropolitan area in the USA and 19 arterial routes were selected. To address the interdependency between crash rates and travel speeds and left-censored issue, simultaneous equation Tobit models are presented. The structure of the model addresses the left-censored issue for the segments while the simultaneous equation models treat the endogeneity issue between crash rates and travel speeds. The results indicate that there is a strong interdependency between crash rates and travel speeds. Segment length, driveway density, median (central reservation) opening density, posted speed limit and annual average daily traffic per lane were found to be statistically significant factors that influence both crash rates and travel speeds on segments. Moreover, crash rates are significantly influenced by two-directional median opening density.

Safety performance functions (SPFs) were developed for rural two-lane county roadway segments in Michigan. Five years of crash data (2011 to 2015) were analyzed for greater than 6,500 mi of rural county roadways, covering 29 of Michigan’s 83 counties and representing all regions of the state. Three separate models were developed to estimate annual deer-excluded total and injury crashes on rural county roadways: 1) paved federal-aid segments, 2) paved non-federal-aid segments, and 3) paved and gravel non-federal-aid segments with fewer than 400 vpd. To account for the unobserved heterogeneity associated with differing county design standards, mixed effects negative binomial models with a county-specific random effect were utilized. Not surprisingly, the county segment SPFs generally differed from traditional models generated using data from state-maintained roadways. County federal-aid roadways general showed greater crash occurrence than county non-federal-aid roadways, the Highway Safety Manual (HSM) two-lane rural roadways model, and rural state highways in Michigan. County non-federal-aid paved roadways showed crash occurrence rates that were remarkably similar to the HSM base rural two-lane roadway model, whereas gravel roadways showed greater crash occurrence rates. The presence of horizontal curves with design speeds below 55 mph had a strong association with the occurrence of total and injury crashes across all county road classes. Increasing driveway density was also found to be associated with increased crash occurrence. However, lane width, roadway surface width, and paved shoulder width had little to no impact on total or injury crashes.

Crash data in Kentucky show that the fatal crash rate on two-lane rural roads is substantially higher than on any other type of road. Improvements have been proposed at some locations on this type of road which involve either upgrading the existing two-lane road or adding lanes resulting in a four-lane road. As part of the public information process, highway officials have been asked to document the previous results of this type of construction. The objectives of this study were to: 1) identify sections of two-lane rural roadways where either the two-lane road had been realigned and reconstructed or additional lanes had been added and 2) conduct a before-and-after analysis to determine how these changes affected traffic crashes. Of the 49 locations included in the study, 25 involved adding lanes and converting to a four-lane road while the two-lane road was upgraded (realignment with wider lanes and shoulders) at 24 locations. Before the construction, the average traffic volume was almost three times higher on the roads where additional lanes were added than where the two-lane road was upgraded. The average daily traffic increased dramatically after the construction was completed with a slightly higher increase for roads where lanes were added. When all the locations are considered, there was a 51% reduction in the crash rate when the road was upgraded and a 56% reduction in the crash rate when lanes were added. The rate was reduced from 250 to 122 crashes/100 million vehicle miles (MVM) when the road was upgraded and from 258 to 114 crashes/100 MVM when lanes were added. When only the number of crashes is considered, the number of crashes per mile decreased by 39% when the road was upgraded and by 45% when lanes were added. The rate of injury or fatal crashes was reduced by 54% for upgrading the road and 55% by adding lanes, while the number of crashes per mile decreased by 43% both when the road was upgraded and when lanes were added. The overall conclusion of the study is that both upgrading two-lane rural roads and converting the road to four lanes are effective methods of reducing total crashes and injury or fatal crashes. The traffic volume would determine the appropriate alternative.