Crosswalking Four Pain Impact Measures in a Nationally Representative Sample of Adults with Back Pain.

OBJECTIVE: To generate crosswalk equations and tables for four pain impact measures: the Impact Stratification Score (ISS), Oswestry Disability Index (ODI), Roland-Morris Disability Questionnaire (RMDQ), and the Pain, Enjoyment of Life and General Activity Scale (PEG). DESIGN: Cross-sectional survey assessing demographics and pain impact. Crosswalks were developed using item response theory (IRT) co-calibrations and linear regressions between the ISS, ODI, RMDQ, and PEG. SETTING: Online panel. PARTICIPANTS: Population-based sample of U.S. adults aged 18 and older. Eligibility criteria were reporting currentback pain, not reporting two fake health conditions, and having data for two or more pain measures (N = 1,530; 37% of sample). Crosswalks were developed (n = 1,030) and cross-validated in a sub-sample of 500 participants (n = 125 randomly sampled from each ISS quartile). INTERVENTIONS: Not Applicable. MAIN OUTCOME MEASURES: ISS, ODI, RMDQ, and the PEG. RESULTS: Associations of the ISS with the PEG and ODI met the criteria for IRT co-calibration. Other measure pairs were cross-walked using regression. Associations were strongest between the PEG and the ISS (r = 0.87, Normalized Mean Absolute Error [NMAE] = 0.38) and between the ODI and the ISS (r = 0.85, NMAE = 0.39). Associations were weakest between the PEG and the RMDQ (r = 0.69, R2 = 0.48, NMAE: 0.55-0.58). Regression equations and IRT accounted for between 48% to 64% of the variance (NMAE: 0.38-0.58) in corresponding pain measures in the cross-validation sample. CONCLUSION: The crosswalks between the ISS and common legacy pain measures created in this study of a nationally representative sample of U.S. adults with back pain can be used to estimate one pain impact measure from another. Further evaluation in clinical samples is recommended.

Measuring psychological distress using the 12-item general health questionnaire and the six-item Kessler psychological distress scale. Psychometric comparison and equipercentile equating of the two scales.

OBJECTIVES: This study aimed to examine if the General Health Questionnaire (GHQ)-12 and Kessler 6 (K6) assess the same underlying construct and to develop a score conversion table for the two scales. METHODS: A random sample of 4303 people who completed both the GHQ-12 and K6 in 2021 were analyzed. Exploratory bifactor analysis evaluated if both scales measured the same construct, and Rasch analysis assessed item severities. The scales were transformed using Equipercentile equivalence for comparability and score conversion. Agreement was estimated with Cohen's Kappa coefficient, along with raw positive and negative agreement. RESULTS: We found that the two scales measure the same phenomenon to the extent that they can be made equivalent. Conversion tables between GHQ-12 and K6 are presented. Applying the commonly used cut-off of ≥3 on the GHQ-12 bi-modal scoring, we found that the best corresponding cut-off on the K6 would be ≥8. The prevalence of psychological distress was then 22% with GHQ-12% and 21% with K6. CONCLUSIONS: The GHQ-12 and K6 measure the same construct and corresponding cut-off scores on one scale were found for the other scale. This is valuable for longitudinal studies or time series where one scale has replaced the other scale.

Program Infrastructure the Key to Success: A Pilot Crosswalk Installation to Promote Walkability, Pedestrian Safety, and Physical Activity in the U.S. Virgin Islands.

BACKGROUND & AIMS: While physical inactivity can contribute to chronic diseases, regular activity like walking can help prevent them. In 2010, one in three adults in the U.S. Virgin Islands (USVI) was physically inactive, higher than most U.S. states and territories. There are few walkable destinations and sidewalks along streets in the USVI. Since community- and street-scale design features can influence walking, we convened a 3-day walkability institute in the USVI to (1) learn about physical activity and best practices for design and (2) develop public health infrastructure that supports implementation. Island teams were formed to develop and implement a territory-wide action plan, focused on passing a Complete Streets policy, and demonstration projects on the islands of St. Croix, St. John, and St. Thomas to advance and pass this policy. An example of the demonstration projects and their significance is the completed one in St. Croix, which is the focus of this article. METHODS: Island teams applied critical components of functioning program infrastructure as described in the Component Model of Infrastructure (CMI) such as engaged data, multilevel leadership, responsive plans and planning, and networked partnerships. We evaluated whether a crosswalk installation in St. Croix could alter driver and pedestrian behavior and create a safer environment for pedestrians. Observers recorded pedestrian crossing time, driver speed, and other behaviors before and after crosswalk installation. RESULTS: Pedestrians took significantly fewer average seconds to cross the street in the postdemonstration period (9.83) compared with predemonstration (13.4) (p = .03). Average car speed declined between the predemonstration (24.3) and long-term demonstration periods (p < .01) and from the postdemonstration (24.7) to the long-term demonstration period (18.2) (p < .01). A greater percentage of pedestrians used the crosswalk to cross the street between the postdemonstration (12.5%) and long-term demonstration periods (53.7%) (p < .01). IMPLICATIONS: The demonstration project in St. Croix shows that improvements to built environment infrastructure can increase safety for pedestrians, thus improving walkability in the USVI. We discuss the importance of CMI elements observed in the success of the St. Croix demonstration and its effectiveness in promoting a Complete Streets policy and the lack of these elements on St. John hindering progress there. Public health practitioners can apply the CMI to future physical activity promotion projects in the USVI and other settings as having functioning program infrastructure helps overcome challenges including natural disasters and a global pandemic and can achieve progress toward sustained policy and systems change.

Safer pedestrian crossing facilities on low-speed roads: Comparison of innovative treatments.

Despite the international efforts to improve pedestrian safety in different regions of the world, pedestrian fatalities still account for around one-third of annual road traffic deaths. Residential areas are commonly characterized by high pedestrian flows, making pedestrian safety a highpriority public health issue. Different types of treatments such as ITS-based, road markings, and physical treatments have been implemented to improve pedestrian safety, however, their efficiency varies between different locations worldwide. Therefore, this study aims to compare different innovative crosswalk treatments and to investigate their impacts on driving behavior in residential areas using a driving simulator. In our study, we juxtapose five different types of treatments with the untreated control condition. The treatments included two ITS-based solutions [LED pavement lights (ITS_LED) and Variable Message Sign (ITS_VMS)]; two different road markings [yellow zigzag marking (Marking_zigzag) and white road narrowing marking with the word SLOW written in the middle (Marking_narrowing)] and a physical road narrowing treatment (Physical_narrowing). Each of the tested conditions (control condition and treatment conditions) was tested with a Yield/Stop-controlled marked crosswalk located in a residential area with a posted speed limit of 50 km/h for two different situations. In the first situation, there was no pedestrian at the crosswalk (Situation PA), while in the second situation, a pedestrian was present at the crosswalk (Situation PP). Sixty-one volunteers possessing a valid Qatari driving license participated in the experiment. The study results showed that compared to the control condition, Physical_narrowing, ITS_VMS, and Marking_narrowing conditions helped to improve the yielding rates by 12.7 %. In terms of drivers' speed behavior, even though a pedestrian was not present at the crosswalk in Situation PA, physical_narrowing performed best by lowering the mean travel speed by around 10.1 km/h at the conflict location compared to the control location. Finally, the participants rated the physical_narrowing condition highest among the tested conditions. Based on the findings of the study, we conclude that the physical_narrowing treatment outperform other studied treatments since it significantly limits the freedom of drivers to maneuver, forcing them to slow down and give priority to crossing pedestrians.

Can automated driving prevent crashes with distracted Pedestrians? An exploration of motion planning at unsignalized Mid-block crosswalks.

Pedestrian distraction may provoke severe difficulties in automated vehicle (AV) control, which may significantly affect the safety performance of AVs, especially at unsignalized mid-block crosswalks (UMCs). However, there is no available motion-planning model for AVs that considers the effect of pedestrian distraction on UMCs. This study aims to explore innovative approaches for safe and reasonable automated driving in response to distracted pedestrians with various speed profiles at UMCs. Based on two common model design concepts, two new models are established for AVs: a rule-based model that solves motion plans through a fixed calculation procedure incorporating several optimization models, and a learning-based model that replaces the deterministic optimization process with policy-gradient reinforcement learning. The developed models were assessed through simulation experiments in which pedestrian speed profiles were defined using empirical data from field surveys. The results reveal that the learning-based model has outstanding safety performance, whereas the rule-based model leads to remarkable safety problems. For distracted pedestrians with significant crossing-speed changes, rule-based AVs lead to a 5.1% probability of serious conflict and a 1.4% crash probability. The learning-based model is oversensitive to risk and always induces high braking rates, which results in unnecessary efficiency loss. To overcome this, a hybrid model based on the learning-based model was developed, which introduces a rule-based acceleration value to regularize the action space of the proposed learning-based model. The results indicate that the hybrid approach outperforms the other two models in preventing crash hazards from distracted pedestrians by employing appropriate braking behaviors. The high safety performance of the hybrid models can be attributed to the spontaneous slowing down of the vehicle that initiates before detecting pedestrians on UMCs. Although such a cautious driving pattern leads to extra delay, the time cost of the hybrid model is acceptable considering the significant improvements in ensuring pedestrian safety.

Crosswalks between the Oxford hip and knee scores and the HOOS-12 and KOOS-12 instruments.

OBJECTIVE: To develop and validate bi-directional crosswalks between the Oxford Hip Score (OHS) and HOOS-12 summary impact score, and between the Oxford Knee Score (OKS) and KOOS-12 summary impact score. METHODS: Data were sourced from the Australian Orthopaedic Association National Joint Replacement Registry Patient-Reported Outcome Measures Program. Patients undergoing primary joint replacement for osteoarthritis who completed the OHS and HOOS-12 or OKS and KOOS-12 instruments were included in the analysis. An equipercentile method was used to create four crosswalks, with the distribution of scores smoothed using log-linear models prior to equating. Crosswalk validity was assessed through comparison of actual vs derived scores, Pearson correlation coefficients, root mean square errors (RMSE) and Bland-Altman plots. RESULTS: Paired OHS/HOOS-12 data and paired OKS/KOOS-12 data were available for 4,513 patients undergoing total hip replacement and 5,942 patients undergoing total knee replacement, respectively. Minimal differences were observed between actual and crosswalk-derived mean scores (actual OHS 27.55 vs derived OHS 27.56; actual HOOS-12 53.28 vs derived HOOS-12 53.31; actual OKS 27.34 vs derived OKS 27.34; actual KOOS-12 50.51 vs derived KOOS-12 50.58). High correlation was observed between actual and derived scores (Pearson's r for hip-specific instruments: 0.943-0.946; Pearson's r for knee-specific instruments: 0.925-0.931). Plotted actual vs mean derived scores also indicated robust concordance across the breadth of the instrument scales. CONCLUSION: These crosswalks provide close approximations of actual OHS, OKS, HOOS-12 and KOOS-12 scores, as indicated by multiple validation metrics. They offer a resource for clinicians, researchers and arthroplasty registries to support PROMs score conversion and data harmonisation efforts.

Interactions between autonomous vehicles and pedestrians at unsignalized mid-block crosswalks considering occlusions by opposing vehicles.

Visibility can be identified as one of the critical determinants for the safety performance of autonomous vehicles (AVs) on unsignalized mid-block crosswalks (UMC), which may be significantly influenced by build-up environment and surrounding vehicles. This study investigates the safety performance when AVs interact with pedestrians approaching from far-side sidewalks to UMCs considering the visual occlusion of opposing vehicles. A mathematical model is proposed for judging the visibilities of objects from observers' location under the impact of visual obstacles and is embedded into an agent-based pedestrian-vehicle interaction framework. Two yielding decision modules is assumed for AVs: The normal decision module implements the pedestrian priority rule simply based on the current detectable information, whereas the memory aid decision module extends AVs' detection abilities by incorporating the memory data. Through simulation experiments, it is found that the percentages of short post encroachment time (%SPET) between AVs and far-side pedestrians reach peaks when the pedestrian flow rate is 300-400 ped/h. When opposing vehicles are in stationary queue conditions, %SPETs are only sensitive to the net distance between the last opposing vehicles in the queue and crosswalks (Dqueue). As the Dqueue decreases to lower than 15 m, %SPETs start to increase drastically. However, when opposing vehicles are in free flow conditions, %SPETs are influenced by multiple factors such as pedestrians' crossing decisions, sizes and flow rates of opposing vehicles. Furthermore, only when opposing vehicles are in free flow conditions, memory aid AVs can significantly eliminate the impacts of opposite vehicles. Finally, several countermeasures are developed to enhance the visibility and safety at UMCs based on the findings of this study.

A novel agent-based framework for evaluating pedestrian safety at unsignalized mid-block crosswalks.

A critical safety problem in road networks is the conflicts on unsignalized crosswalks. Thus, a proactive approach to assess pedestrian safety performance is required. Simulating the microscopic road user behavior in a virtual platform is one of the typical approaches. However, current simulation tools are not flexible enough to properly reproduce various behaviors of pedestrians and drivers considering their interactions with the road environment and other road users. Therefore, the objective of this paper is to propose a novel agent-based framework for evaluating pedestrian safety at unsignalized crosswalks. Unsignalized mid-block crosswalks with refuge islands (UMCR) are considered as an example facility to implement the proposed framework, where relevant behavioral elements such as the reaction time, visual field with obstacles, and minimum safety margin time are addressed. Not only the pedestrian-vehicle interaction is modeled but also the vehicle-vehicle interaction is considered. Empirical validation on a UMCR shows that the proposed framework can reproduce reliable distributions of the post encroachment time compared to the observed distributions within an acceptable error range. The sensitivity analysis reveals that the high reaction time of drivers, small safety margin time, and visual obstacles near crosswalks increase the probability of serious conflicts. The results also show that the framework can reproduce traffic crashes under assumed extreme road conditions.

Incorporating conflict risks in pedestrian-motorist interactions: A game theoretical approach.

At "semi-controlled" crosswalks with yield signs and markings, negotiations as to the right-of-way occur frequently between pedestrians and motorists, to determine who should proceed first. This kind of "negotiation" often leads to traffic delay and potential conflicts. To minimize misunderstandings between pedestrian and motorist that can have serious safety consequences, it is essential that we understand the decision-making process as the "players" interact in real street-crossing situations. This paper employs a game-theoretic approach to investigate the joint behaviors of pedestrians and motorists from the perspective of safety. Assuming bounded rationality for each player, the quantal response equilibrium is a special kind of game with incomplete information. Explanatory variables such as conflicting risks and time savings can be incorporated into the payoff functions of the "players" via expected utility functions. Finally, model parameters can be estimated using an expectation maximization algorithm. The game-theoretic framework is applied to model pedestrian-motorist interactions at a semi-controlled crosswalk on a university campus. The estimation results indicate that the likelihood of pedestrian-vehicle conflict can be quantified. The results can lead to control measures that facilitate the negotiation between pedestrian and motorist and reduce the conflict risk at semi-controlled crosswalks.

Factors affecting pedestrian behaviors at signalized crosswalks: An empirical study.

INTRODUCTION: Safety of pedestrians depends, among other factors, on their behavior while crossing the road. This study aims to assess behaviors of pedestrians at signalized crosswalks. METHOD: Following a literature review and a pilot study, 25 vital pedestrian crossing factors and behaviors were determined. Then data was randomly collected for 708 pedestrians at 10 lighted crossings in Sharjah (UAE), five at road intersections and five mid-block crossings. RESULTS: Results indicated that 17.4% of pedestrians observed crossed partly or fully on red and that crossing speed was 1.22 m/s, on the average, which is slightly faster than most speeds recorded in the literature. Moreover, female pedestrians were more likely to cross while chatting with others, less likely to cross on red, and more likely to walk slower than male pedestrians. Results also showed that pedestrians who crossed at road intersections walked slower than those who crossed at mid-block crossings. It was also found that longer red pedestrian times and narrower roads tended to encourage pedestrians to cross on red and that the majority of pedestrians did not look around before crossing. PRACTICAL IMPLICATIONS: Use of the Health Belief Model for pedestrian safety are discussed.

Observational-based study to explore pedestrian crossing behaviors at signalized and unsignalized crosswalks.

Despite many studies on exploring the behaviors of pedestrians crossing the road, there is a need for comprehensive studies that identify the factors that may influence pedestrians crossing behavior at signalized and unsignalized intersections. This study aims to comprehensively examine the influence of gender, age group, group-crossing, technological devices and carrying items on pedestrians crossing behaviors at signalized and unsignalized crosswalks simultaneously. Observational data of 552 pedestrians at two signalized and two unsignalized crosswalks in Tehran were collected. Temporal and spatial violations, conflict experience and collision avoidance, situational awareness, and pedestrians crossing speed were used as pedestrians crossing behaviors indicators. To model crossing behaviors, linear mixed models (LMMs) and Generalized linear mixed models (GLMMs) with fixed-effect approach were applied for the continuous outcome (pedestrians' crossing speed) and binary outcomes, respectively. Phi and Cramer's V coefficients were used to avoid multicollinearity. Results showed that traffic checks before and while crossing showed a high positive correlation with crossing at "don't walk" and flashing "don't walk" signals and conflict experience at signalized crosswalks. As compared to females, males started their crossing more on flashing "don't walk" signal and crossed the crosswalk faster. Older pedestrians exhibited more cautious behaviors at signalized intersections but less in unsignalized intersections. Alone pedestrians behaved more cautiously than groups and crossed the crosswalk more quickly. Using technological devices, regardless of their types, caused pedestrians to not exhibit one or more safe crossing indicators considered in this study. Pedestrians talking on their phones had the least cautious behaviors. Pedestrians listening to music mostly looked at the ground or straight direction rather than looking left-right for traffic. The findings from this study are a valuable resource to road authorities and policy makers to develop appropriate targeted strategies to prevent pedestrians' injuries and fatalities and improve crosswalks safety.

A protocol for chronic pain outcome measurement enhancement by linking PROMIS-29 scale to legacy measures and improving chronic pain stratification.

BACKGROUND: Substantial investment has gone into research on the efficacy and effectiveness of pharmaceutical and nonpharmacologic interventions for chronic pain. However, synthesizing this extensive literature is challenging because of differences in the outcome measures used in studies of similar or competing interventions. The absence of a common metric makes it difficult to replicate findings, pool data from multiple studies, resolve conflicting conclusions, or reach consensus when interpreting findings. METHODS: This study has a seven-member Advisory Council of chronic pain experts. Preliminary analyses will be performed on data from several large existing datasets; intermediate analyses will be performed using primary data collected from Amazon's Mechanical Turk (MTurk); and cross-validation will use primary data collected from a nationally-representative, probability-based panel. Target sample size for both primary datasets is 1500. The three study aims are as follows: Aim 1 will develop and evaluate links between the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS®-29) and legacy measures used for chronic pain such as the Roland-Morris Disability Questionnaire (RMDQ) and the Oswestry Disability Index (ODI). We will assess the best method of score linking and create crosswalk tables. Aim 2 will evaluate and refine the Impact Stratification Score (ISS) based on 9 PROMIS-29 items and proposed by the NIH Research Task Force on chronic low back pain. We will evaluate the ISS in terms of other indicators of condition severity and patient prognosis and outcomes and identify cut-points to stratify chronic pain patients into subgroups. Aim 3 will evaluate the strengths and limitations of MTurk as a data collection platform for estimating chronic pain by comparing its data to other data sources. DISCUSSION: The accomplishment of Aims 1 and 2 will allow direct comparison of results across past and future studies of chronic pain. These comparisons will help us to understand different results from seemingly similar studies, and to determine the relative effectiveness of all pharmaceutical and nonpharmacologic interventions for chronic pain across different trials. Aim 3 findings will provide valuable information to researchers about the pros and cons of using the MTurk platform for research-based data collection. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04426812 ; June 10, 2020.

An exploratory analysis of factors associated with traffic crashes severity in Cartagena, Colombia.

Traffic fatalities are the second cause of violent deaths in Colombia. However, due to the signing of the peace agreement and the growing number of fatalities in road crashes, it is possible that soon traffic fatalities will be the primary cause of violent deaths in the country, particularly in urban areas. This study is an exploratory analysis focused on identifying the main factors associated with the severity of traffic crashes in urban areas, using Cartagena as a case study. We analyzed three levels of crash severity, namely fatal, injury, and property-damage-only, considering factors in several different dimensions: victim, vehicle, road infrastructure, traffic and control, day and time, and environmental factors. A modeling approach based on multinomial ordered discrete models was used to properly identify the main factors associated with the severity levels. We found that the probability of fatal accidents is higher on streets with speed limits over 40 km/h, and that males and people aged 60 years or older are the victims with the most significant risk of fatal crashes. Motorcycles were also identified as vehicles with the highest probability of fatal crashes in the city. We showed that the probability of fatal crashes occurring is higher on streets where pedestrian bridges, traffic lights, and crosswalks are present. These findings are worthy because, in Colombia and other developing countries, the authorities normally expect to reduce the probability of fatal accidents through investments in pedestrian bridges, signaling devices, and crosswalk markings. However, according to our results, it possibly will not occur unless further countermeasures are taken. Based on these findings, reducing speed limits, operational improvements at signalized intersections, zero tolerance for traffic violations related to pedestrians, an awareness campaign on pedestrian safety focused on males and people aged 60 or older, and improving motorcycle safety are the countermeasures we proposed. Furthermore, as the authorities make significant efforts to investing in pedestrian bridges, we propose a further investigation into the traffic crashes in streets where there is this infrastructure since more severe events occur near them.

Investigating pedestrian waiting time at semi-controlled crossing locations: Application of multi-state models for recurrent events analysis.

"Semi-controlled" crosswalks are unsignalized, but clearly marked with "yield to pedestrian within crosswalk" signs. Ideally, pedestrians can cross the street immediately after they arrive at the curb. However, real world observations show that pedestrians and vehicles are often involved in non-verbal "negotiations" to decide who should proceed first. This kind of "negotiation" often causes delays for both parties and may lead to unsafe situations. The study in this paper was based on video recordings of the waiting behaviors of 2059 pedestrians interacting with 1003 motorists at selected semi-controlled crosswalks. One such location experienced a conversion from one-way operation to two-way operation, which provided a rare opportunity for a before-and-after study at that location. Multi-state Markov models were introduced as a novel approach to correlate the dynamic process between recurrent events. Time-varying covariates related to pedestrian characteristics, traffic condition, and vehicle dynamics (distance and speed) turned out to be significant. The analytical method developed in this study provides a tool to dynamically model pedestrian waiting decisions with uncertainties. Model results reveal that, after the conversion from one-way to two-way operation, the probability of a pedestrian accepting a lag decreases from 69.7% to just below 60% on the same street. In addition, pedestrians are more hesitant to cross a two-way street than a one-way street. Countermeasures that increase motorist yielding rate or reduce pedestrian confusion will enhance safety such crossing locations.

Gap acceptance probability model for pedestrians at unsignalized mid-block crosswalks based on logistic regression.

Gap acceptance represents a pedestrian's assessment of how safe it may be to use an available gap in traffic flow at a particular point in time. Though walking is a major component of urban mobility, the high rate of fatal interaction with motor vehicle traffic raises safety issues around how pedestrians decide to accept the available gap. This paper explored these interactions by modeling gap acceptance behavior at the midblock crosswalks. Unlike other pedestrian gap acceptance studies that focus on individual psychological and sociological factors that are difficult to control or manage, this study focused on six environmental factors that we considered important and as having the potential to affect the pedestrians' gap acceptance decision at the crosswalks, i.e. gap size, crossing distance, number of waiting pedestrians, waiting time, vehicle traffic volume and position of pedestrian (whether on street kerb or median). Video data was collected on pedestrian gap acceptance from 13 midblock crosswalk locations in Shanghai, China. A Logit model with 96% accuracy was developed to describe and predict the pedestrian gap acceptance behaviors. The results show that gap size and crossing distance have the highest effect on the pedestrian gap acceptance decision. Pedestrians waiting at the kerbside could confidently accept gaps (with a 95% probability) when the gap is longer than 2.2s, 5.9s, and 9.6s under the condition that the crossing distance is 4 m (one lane), 7.5 m (two lanes), and 11 m (three lanes), respectively while pedestrians waiting at the median could confidently accept gaps when the gap is longer than 1.6s, 5.3s, and 8.5s respectively under the same conditions. The recommendations on improving the crossing safety are proposed accordingly.

Exploring patterns of child pedestrian behaviors at urban intersections.

Children are more vulnerable as pedestrians due to their cognitive, physical and behavioral traits. However, walking is one of the main forms of travel for children, particularly during leisure hours. Child pedestrian injury primarily occurs in urban areas, with a significant share at crosswalks. This study observed child pedestrian behaviors at crosswalks of urban intersections aiming to characterize their behavior patterns and identify risk factors that may lead to injury. Crossing behaviors of children and adolescents up to age 18, during leisure hours, were video-recorded at 29 crosswalks, on signalized and un-signalized intersections situated on collector roads. Some children used pedestrian crosswalks while riding a bicycle or other non-motorized means; they were also included in the sample. Behaviors of 2930 young road users were encoded and compared by age groups. Multivariate logistic regression models were adjusted to identify factors associated with crossing on red and with non-checking vehicle traffic at un-signalized crosswalks. The findings pointed to different behavior patterns for the various child age groups. Risk-taking behaviors are higher for older children; adolescents aged 14-17 cross more on red, without checking traffic, outside crosswalk boundaries and while distracted. At all types of sites, a fifth of children over the age of 9 crossed by riding, the probability of crossing on red and of non-checking traffic prior to crossing at an un-signalized crosswalk was higher for children riding an electric bicycle or kick-scooter. The non-checking of traffic was also higher when a child is distracted by a mobile phone or other electronic gadget, or carries a big object. Children under age 9 were usually accompanied by adults but still exhibited risk-taking behaviors that apparently mirrored those of the adults. Risk-taking behaviors of young road users should be taken into account in the development of injury prevention programs focusing on child and parent education and training, and by adapting the urban environment to better meet their needs.

Bridge Processes: A Solution for LCI Datasets Independent of Background Databases.

INTRODUCTION: New platforms are emerging that enable more data providers to publish life cycle inventory data. BACKGROUND: Providing datasets that are not complete LCA models results in fragments that are difficult for practitioners to integrate and use for LCA modeling. Additionally, when proxies are used to provide a technosphere input to a process that was not originally intended by the process authors, in most LCA software this requires modifying the original process. RESULTS: The use of a bridge process, which is a process created to link two existing processes, is proposed as a solution. DISCUSSION: Benefits to bridge processes include increasing model transparency, facilitating dataset sharing and integration without compromising original dataset integrity and independence, providing a structure with which to make the data quality associated with process linkages explicit, and increasing model flexibility in the case that multiple bridges are provided. A drawback is that they add additional processes to existing LCA models which will increase their size. CONCLUSION: Bridge processes can be an enabler in allowing users to integrate new datasets without modifying them to link to background databases or other processes they have available. They may not be the ideal long-term solution, but provide a solution that works within the existing LCA data model.

Modeling pedestrian crossing speed profiles considering speed change behavior for the safety assessment of signalized intersections.

Pedestrian safety is one of the most challenging issues in road networks. Understanding how pedestrians maneuver across an intersection is the key to applying countermeasures against traffic crashes. It is known that the behaviors of pedestrians at signalized crosswalks are significantly different from those in ordinary walking spaces, and they are highly influenced by signal indication, potential conflicts with vehicles, and intersection geometries. One of the most important characteristics of pedestrian behavior at crosswalks is the possible sudden speed change while crossing. Such sudden behavioral change may not be expected by conflicting vehicles, which may lead to hazardous situations. This study aims to quantitatively model the sudden speed changes of pedestrians as they cross signalized crosswalks under uncongested conditions. Pedestrian speed profiles are collected from empirical data and speed change events are extracted assuming that the speed profiles are stepwise functions. The occurrence of speed change events is described by a discrete choice model as a function of the necessary walking speed to complete crossing before the red interval ends, current speed, and the presence of turning vehicles in the conflict area. The amount of speed change before and after the event is modeled using regression analysis. A Monte Carlo simulation is applied for the entire speed profile of the pedestrians. The results show that the model can represent the pedestrian travel time distribution more accurately than the constant speed model.

Webcams, Crowdsourcing, and Enhanced Crosswalks: Developing a Novel Method to Analyze Active Transportation.

INTRODUCTION: Active transportation opportunities and infrastructure are an important component of a community's design, livability, and health. Features of the built environment influence active transportation, but objective study of the natural experiment effects of built environment improvements on active transportation is challenging. The purpose of this study was to develop and present a novel method of active transportation research using webcams and crowdsourcing, and to determine if crosswalk enhancement was associated with changes in active transportation rates, including across a variety of weather conditions. METHODS: The 20,529 publicly available webcam images from two street intersections in Washington, DC, USA were used to examine the impact of an improved crosswalk on active transportation. A crowdsource, Amazon Mechanical Turk, annotated image data. Temperature data were collected from the National Oceanic and Atmospheric Administration, and precipitation data were annotated from images by trained research assistants. RESULTS: Summary analyses demonstrated slight, bi-directional differences in the percent of images with pedestrians and bicyclists captured before and after the enhancement of the crosswalks. Chi-square analyses revealed these changes were not significant. In general, pedestrian presence increased in images captured during moderate temperatures compared to images captured during hot or cold temperatures. Chi-square analyses indicated the crosswalk improvement may have encouraged walking and biking in uncomfortable outdoor conditions (P < 0.5). CONCLUSION: The methods employed provide an objective, cost-effective alternative to traditional means of examining the effects of built environment changes on active transportation. The use of webcams to collect active transportation data has applications for community policymakers, planners, and health professionals. Future research will work to validate this method in a variety of settings as well as across different built environment and community policy initiatives.

A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks.

At unsignalized crosswalks, interactions between pedestrians and vehicles often lead to traffic safety hazards due to absence of traffic control and unclear right-of-ways. To address this safety problem, there is a need to understand the interaction behaviors of pedestrians and vehicles that are complicated by a variety of traffic and roadway attributes. The prime objective of this study is to establish a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at unsignalized crosswalks in a realistic way. The model is calibrated with detailed behavioral data collected and extracted from field observations. The capability of the calibrated model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay are also tested and demonstrated. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the proposed model is capable to evaluate the pedestrian safety. Thereby, the simulation model has the potential to serve as a useful tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing.