The Effectiveness of eHMI Displays on Pedestrian-Autonomous Vehicle Interaction in Mixed-Traffic Environments.

External human-machine interfaces (eHMIs) serve as communication bridges between autonomous vehicles (AVs) and road users, ensuring that vehicles convey information clearly to those around them. While their potential has been explored in one-to-one contexts, the effectiveness of eHMIs in complex, real-world scenarios with multiple pedestrians remains relatively unexplored. Addressing this gap, our study provides an in-depth evaluation of how various eHMI displays affect pedestrian behavior. The research aimed to identify eHMI configurations that most effectively convey an AV's information, thereby enhancing pedestrian safety. Incorporating a mixed-methods approach, our study combined controlled outdoor experiments, involving 31 participants initially and 14 in a follow-up session, supplemented by an intercept survey involving 171 additional individuals. The participants were exposed to various eHMI displays in crossing scenarios to measure their impact on pedestrian perception and crossing behavior. Our findings reveal that the integration of a flashing green LED, robotic sign, and countdown timer constitutes the most effective eHMI display. This configuration notably increased pedestrians' willingness to cross and decreased their response times, indicating a strong preference and enhanced concept understanding. These findings lay the groundwork for future developments in AV technology and traffic safety, potentially guiding policymakers and manufacturers in creating safer urban environments.

Discovering latent themes in traffic fatal crash narratives using text mining analytics and network topology.

The proliferation of digital textual archives in the transportation safety domain makes it imperative for the inventions of efficient ways of extracting information from the textual data sources. The present study aims at utilizing crash narratives complemented by crash metadata to discern the prevalence and co-occurrence of themes that contribute to crash incidents. Ten years (2009-2018) of Michigan traffic fatal crash narratives were used as a case study. The structural topic modeling (STM) and network topology analysis were used to generate and examine the prevalence and interaction of themes from the crash narratives that were mainly categorized into pre-crash events, crash locations and involved parties in the traffic crashes. The main advantage of the STM over the other topic modeling approaches is that it allows the researchers to discover themes from documents and estimate how the topic relates to the document metadata. Topics with the highest prevalence for the angle, head-on, rear-end, sideswipe and single motor vehicle crashes were crash at stop-sign, crossing the centerline, unable to stop, lane change maneuver and run-off-road crash, respectively. Eigenvector centrality measure in network topology showed that event-related topics were consistently central in articulating the crash occurrence. The centrality and association between topics varied across crash types. The efficacy of generated topics in classifying crashes by type was tested using a machine learning algorithm, Random Forest. The classification accuracy in the held-out sample ranged between 89.3 % for sideswipe crashes to 99.2 % for single motor vehicle crashes. High classification accuracy suggests that automation of crash typing and consistency checks can be accomplished effectively by using extracted latent themes from the crash narratives.

Development of systemwide pedestrian safety performance function using stratified random sampling and a proxy measure of pedestrian exposure.

The lack of pedestrian counts at a systemwide level prompts the need to find other innovative ways of assessing pedestrian traffic crash risks using proxy measures of exposure. This study aims to formulate the methodology for developing pedestrian safety performance functions (SPF) using the proxy measure of pedestrian exposure and stratified random sampling. The case study was all urban intersections in Michigan State that comprise of collector and arterial roads. The stratified random sampling strategy was deployed to select the sample which is representative of all urban intersections in the state of Michigan. Factor analysis was used to develop a proxy measure of pedestrian exposure at urban intersections using a walkability measure (walk score), among other factors. The performances of various count models were compared using the goodness of fit measures based on the Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and Vuong test. The final pedestrian SPFs was formulated using the Zero-Inflated Poisson (ZIP) model with AADT at a major approach, AADT at the minor approach, and a proxy measure of pedestrian exposure. The proposed methodology in this study can benefit transportation agencies that have embarked on systemwide planning of pedestrian facilities to improve the safety of pedestrians but lack systemwide analytical tools and pedestrian counts to make data-driven decisions.

Assessing the safety impacts of raising the speed limit on Michigan freeways using the multilevel mixed-effects negative binomial model.

Objectives: The main objective of this study was to assess the change in crash patterns associated with speed limit changes from 55 mph to 70 mph that occurred on some of Michigan freeway segments between year 2005 and year 2010.Method: Many of the statistical methods used in the past to evaluate the safety impacts of raising the speed limit on freeways lack the ability to address one or more critical issues inherent in count data, such as omitted-sample bias, over-dispersion and regression-to-the-mean bias. This study used multilevel mixed-effects negative binomial regression to address these limitations, with an additional advantage of controlling for intra-cluster correlation of crashes on each freeway corridor and segments nested in the same corridor. Changes in the crash patterns between the year 2000 and year 2015 were investigated on test sites that had a change of speed limit from 55 mph to 70 mph, relative to control sites where the speed limit was maintained at 55 mph.Results: The inclusion of random effects improved the model's ability in explaining observed crash variations on the selected freeway segments, as indicated by test statistics such as the log-likelihood ratio test, the Akaike information criterion and Bayesian information criterion (BIC)values. Further, random effects improved the significant speed limit change fixed effects during model calibration. The final mixed-effects model indicated a significant increase in fatal and injury crashes (FI), total crashes (KABCO) and road departure crashes by 11.9 percent, 21.0 percent and 23.3 percent, respectively, on freeway segments where the speed limit was raised from 55 mph to 70 mph. The increase in road departure crashes was more pronounced on curved freeway segments with the raised speed limit compared to straight segments with no speed limit changes.Conclusions: The 15 mph increase in the speed limit on Michigan freeways had a significant association with the increase in fatal and injury crashes, total crashes and road departure crashes. The elevated crash risks associated with the speed limit increase suggest that further studies are needed to understand changes in drivers' behaviors following a speed limit increase.

How does an increased freeway speed limit influence the frequency of crashes on adjacent roads?

Urban arterial roads carry the most traffic on urban road networks and experience the highest percentage of crashes in urban areas. Safety on urban arterials that are adjacent to a higher speed freeway may be impacted by speed spillover or adaptation. The objective of this study was to determine the effects of raising freeway speed limits on the frequency of crashes on urban arterial roads adjacent to freeways (spillover effects). Crash data within Michigan were collected on 1393 urban arterial road segments before and after freeway speed limits were altered. Before-and-after data was collected simultaneously on 1470 comparison segments of urban arterial where speed limits did not change to control for the regression-to-the-mean bias. The mixed effects negative binomial (MENB) regression model was developed to analyze crash frequency on urban arterials. The results indicate that raising speed limits of freeways by as little as five miles per hour had a likelihood of increasing crash frequency on adjacent arterial roads by as much as 13.9 percent. To investigate if the safety impact of speed spillover changes with the distance from the freeway, influence areas (0-1 mile, 1-2 mile, and 2-3 mile) were used. The findings of this study provide insights into the effects of speed spillover on crash occurrences, and it demonstrates that increasing freeway speed limit has a negative influence on driver compliance with the speed limit on adjacent arterial roads. Correspondingly, the influence of freeway speed on drivers' speeding behavior on adjacent urban arterials fades away with the distance from the freeway.

A comparison of safety benefits of pedestrian countdown signals with and without pushbuttons in Michigan.

OBJECTIVE: This study evaluated the safety impacts of pedestrian countdown signals (PCSs) with and without pushbuttons based on pedestrian crashes and pedestrian injuries in Michigan. METHODOLOGY: This study used 10 years of intersection data-5 years before PCSs were installed and 5 years after they were installed-along with a comparison group, to evaluate the crash impacts of PCSs; at 107 intersections the PCS had a pushbutton and at 96 it did not. At these intersections, and at their comparison sites (where no PCS was installed), crash data (from 2004 to 2016) were examined, along with traffic and geometric characteristics, population, education, and poverty level data. RESULTS: Intersections where PCSs with pushbuttons have been installed showed a 29% reduction in total pedestrian crashes and a 30% reduction in fatal/injury pedestrian crashes. Further, when considering only pedestrians age 65 and below, these respective reductions are 33 and 35%. Intersections with PCSs but without pushbuttons did not show any significant change in any type of pedestrian crash. CONCLUSIONS: Although the Manual on Uniform Traffic Control Devices (Federal Highway Administration [FHWA] 2009 ) requires the use of PCSs at new traffic signal installations, this study suggests a safety benefit of installing PCSs with pushbutton at signals where a PCS without a pushbutton is present.

Quantifying the impact of adaptive traffic control systems on crash frequency and severity: Evidence from Oakland County, Michigan.

INTRODUCTION: Despite seeing widespread usage worldwide, adaptive traffic control systems have experienced relatively little use in the United States. Of the systems used, the Sydney Coordinated Adaptive Traffic System (SCATS) is the most popular in America. Safety benefits of these systems are not as well understood nor as commonly documented. METHOD: This study investigates the safety benefits of adaptive traffic control systems by using the large SCATS-based system in Oakland County, MI known as FAST-TRAC. This study uses data from FAST-TRAC-controlled intersections in Oakland County and compares a wide variety of geometric, traffic, and crash characteristics to similar intersections in metropolitan areas elsewhere in Michigan. Data from 498 signalized intersections are used to conduct a cross-sectional analysis. Negative binomial models are used to estimate models for three dependent crash variables. Multinomial logit models are used to estimate an injury severity model. A variable tracking the presence of FAST-TRAC controllers at intersections is used in all models to determine if a SCATS-based system has an impact on crash occurrences or crash severity. RESULTS: Estimates show that the presence of SCATS-based controllers at intersections is likely to reduce angle crashes by up to 19.3%. Severity results show a statistically significant increase in non-serious injuries, but not a significant reduction in incapacitating injuries or fatal accidents.

Identifying access management factors associated with safety of urban arterials mid-blocks: a panel data simultaneous equation models approach.

OBJECTIVE: The objective of this study was to evaluate the safety impact of selected access management techniques in urban areas because access management techniques play an important role in urban roadway safety on the roadway network. METHODS: In order to correct the interdependency between safety and mobility for heterogeneous mid-block segments, simultaneous equation models were adopted. The panel data structure of the model was used to address the heterogeneity issue for mid-block segments along a corridor. The integrated random coefficient simultaneous equation models were proposed to interpret both issues. RESULTS: The models developed were used to identify influential factors. The length of mid-block segments, driveway density, and median opening density were among the significant factors found to be associated with crash rate on mid-block segments. CONCLUSIONS: From the results it can be concluded that the access management techniques, mid-block segment length, driveway density, and median opening density are significant factors that influence safety on mid-block segments. The longer the distance between signals, driveways, and median openings, the fewer the potential crashes are. In addition to these access management techniques, land use, especially the commercial land type, influences the safety on mid-block segments.

Effect of bus size and operation to crash occurrences.

This paper evaluates roadway and operational factors considered to influence crashes involving buses. Factors evaluated included those related to bus sizes and operation services. Negative binomial (NB) and multinomial logit (MNL) models were used in linearizing and quantifying these factors with respect to crash frequency and injury severities, respectively. The results showed that position of the bus travel lane, presence or absence of on-street shoulder parking, posted speed limit, lane width, median width, number of lanes per direction and number of vehicles per lane has a higher influence on bus crashes compared to other roadway and traffic factors. Wider lanes and medians were found to reduce probability of bus crashes while more lanes and higher volume per lane were found to increase the likelihood of occurrences of bus-related crashes. Roadways with higher posted speed limits excluding freeways were found to have high probability of crashes compared to low speed limit roadways. Buses traveling on the inner lanes and making left turns were found to have higher probability of crashes compared to those traveling on the right most lanes. The same factors were found to influence injury severity though with varying magnitudes compared to crash frequency.

Investigation of the AP-42 sampling method.

The AP-42 method has been recommended by the U.S. Environment Protection Agency to collect dust emission data. According to this method, the number of sampling sites needs to be determined first. At these sites, the dust will be collected based on plots drawn on the road surface. Apparently, there has been no systematic rule to follow to determine the number of sampling sites. In addition, it is not known whether the required number of plots and their sizes are validated based on real data. Mobile sampling technology can collect dust emission data at very close space intervals, which to some extent can be viewed as being close to actual dust emission data continuously distributed over roadway segments. With such data available, this study investigated the number of sampling sites and the number of plots and their sizes based on the optimal allocation sampling method and the Monte Carlo simulation method. The results from the optimal allocation method indicated that most of the sampling sites should be drawn from the local roads because the variance of emission and proportion of road segments of this roadway classification are significantly bigger than other roadway classifications. This observation may lead to the application of other cost-effective sampling approaches. The results from the Monte Carlo simulation method imply that clear patterns of improved estimation of emission factors versus plot number and size can be observed only for three roadway classifications, not for other classifications. This result indicates that the AP-42 method may not be applicable to some roadway classifications, and thus different data collection methods such as the mobile sampling technology may be necessary.

Identifying influencing factors on paved roads silt loading.

The factors that influence the increase or decrease of silt loadings on paved roadways have not been fully quantitatively investigated. They were identified in this study based on the quarterly silt loading sampling data collected from 20 sites by the Clark County Department of Air Quality and Environmental Management in Southern Nevada for the period from 2000 to 2003. The silt loading and associated data collected over these years at one sampling site may inherently possess site-specific characteristics that can be better incorporated by using panel data models. The factors that are identified as significant are the presence of curbs and gutters, shoulder type, pavement conditions, and the presence of construction activities in the vicinity of roadways. The presence of curbs and gutters, stabilized shoulders, and good pavement conditions would result in decreased silt loadings. Conversely, the presence of construction activities within the immediate vicinity of sampled areas would result in increases of silt loadings on the roadway surfaces. Based on the analysis of the results, it was recommended that constructing curbs, gutters and stabilized shoulders, preventing or reducing construction track-out from construction activity, and improving pavement conditions be the preferred control measures to reduce silt loading on paved roadways.