A bidirectional pedestrian macroscopic speed model construction based on pedestrian microscopic simulation experiments.

Studies of macroscopic speed modeling of bidirectional pedestrian cross-flows have relied heavily on scenario experiments, but the data itself may be deficient because large-scale scenario experiments are not easy to organize and subjects may not be walking under normal conditions. In order to explore the possibility of using microscopic pedestrian flow simulations for macroscopic speed modeling of pedestrian flows, a series of two-way pedestrian cross-flow simulation experiments were designed. Bidirectional pedestrian flows are defined as Peds1 and Peds2. The crossing angle and pedestrian flow rate are used as variables, and a bidirectional pedestrian flows simulation is designed as an orthogonal experiment. The crossing angles range from 15 to 165 degrees, and bidirectional pedestrian flow rate range from 1 ped/s to 8 ped/s. A series of simulations are built and performed on the GIS agent-based modeling architecture (GAMA) platform. By analyzing the flow data of bidirectional flows in the crossing area, it is found that when the Peds1 density falls below a threshold, Peds1 speed is determined by pedestrians themselves and mainly remains in a free flow state; otherwise, the Peds1 speed decreases with density. The clear effects such as Peds2 density on the Peds1 speed cannot be determined. A piecewise function combined with a linear function and an exponential function is constructed as the Peds1 speed model considering the influence of the crossing angle. The calibration results show that the piecewise function should be better than the non-piecewise function. Compared to the results of established studies, the results in this paper have some differences. Therefore, the simulation method cannot completely replace the scene experiments. However, this approach can provide suggestions for subsequent refinement of the experimental program, as well as a feasible direction for the construction of a speed relationship for bidirectional pedestrian flows.

Simulating pedestrian avoidance: The human-zombie game.

This study introduces a simulated active matter system, applying the pedestrian collision avoidance paradigm, which involves dynamically adjusting the desired velocity. We present a human-zombie game set within a closed geometry, combining predator-prey behavior with a one-way contagion process that transforms prey into predators. The system demonstrates varied responses in our implemented model: with agents having the same maximum speeds, a single zombie always captures a human, whereas two zombies never capture a single human agent. As the number of human agents increases, observables such as the final fraction of zombie agents and total conversion times exhibit significant changes in the system's behavior at intermediate density values. Most notably, there is evidence of a first-order phase transition when analyzing the mean population speed as an order parameter.

The relationships between the campus built environment and walking activity.

Despite the gradual development of students' sedentary habits and associated health problems, only a few studies have extensively and systematically measured campus built environments (CBE) and their impact on street walking activity. This study explores the association between CBEs and pedestrian volume (PV). Comprehensive questionnaires, field audits, and GIS were used to measure the CBE variables and PV of 892 street segments on eight Chinese campuses in Tianjin. We used negative binomial regression models without spatial autocorrelations to investigate the relationship between the CBEs and PV. The findings indicated that campus Walk Score, facility and residential land ratio, campus design qualities, sidewalk conditions, street amenities, and other streetscape features were positively associated with PV. This study presents implications for campus research and planning practices in designing a pedestrian-friendly, sustainable, and healthy campus.

The association between passenger-vehicle front-end profiles and pedestrian injury severity in motor vehicle crashes.

INTRODUCTION: Vehicles play an important role in pedestrian injury risk in crashes. This study examined the association between vehicle front-end geometry and the risk of fatal pedestrian injuries in motor vehicle crashes. METHOD: A total of 17,897 police-reported crashes involving a single passenger vehicle and a single pedestrian in seven states were used in the analysis. Front-end profile parameters of vehicles (2,958 vehicle makes, series, and model years) involved in these crashes were measured from vehicle profile photos, including hood leading edge height, bumper lead angle, hood length, hood angle, and windshield angle. We defined a front-end-shape indicator based on the hood leading edge height and bumper lead angle. Logistic regression analysis evaluated the effects of these parameters on the risk that a pedestrian was fatally injured in a single-vehicle crash. RESULTS: Vehicles with tall and blunt, tall and sloped, and medium-height and blunt front ends were associated with significant increases of 43.6%, 45.4%, and 25.6% in pedestrian fatality risk, respectively, when compared with low and sloped front ends. There was a significant 25.1% increase in the risk if a hood was relatively flat as defined in this study. A relatively long hood and a relatively large windshield angle were associated with 5.9% and 10.7% increases in the risk, respectively, but the increases were not significant. CONCLUSIONS: Vehicle front-end profiles that were significantly associated with increased pedestrian fatal injury risk were identified. PRACTICAL APPLICATIONS: Automakers can make vehicles more pedestrian friendly by designing vehicle front ends that are lower and more sloped. The National Highway Traffic Safety Administration (NHTSA) can consider evaluations that account for the growing hood heights and blunt front ends of the vehicle fleet in the New Car Assessment Program or regulation.

How state mindfulness affects mobile phones usage while walking: A daily diary study in China.

INTRODUCTION: Pedestrians are a particularly vulnerable group of road users. Mobile phone usage while walking (MPUWW) is a significant contributor to pedestrians' involvement in road crashes and associated injuries. The current study aims to explore the effect of state mindfulness on daily MPUWW via phone dependence (at the within-person level), and the moderating role of risk perception (at the between-person level) in the phone dependence-MPUWW relationship. METHOD: We utilized a fine-grained method, the daily diary methodology (DDM) to explore the aforementioned model. A total of 88 Chinese college students participated in a consecutive 12-day study, yielding 632 daily data. Unconflated multilevel modeling was used to analyze the data. RESULTS: After trait mindfulness being controlled, state mindfulness has a negative impact on MPUWW via phone dependence at the daily level. Furthermore, risk perception as an individual difference variable moderates the relationship between phone dependence and MPUWW, in which a weaker effect observed in individuals with higher levels of risk perception. CONCLUSIONS: State mindfulness can decrease the frequency of daily MPUWW by reducing phone dependence, and risk perception is a crucial factor in mitigating the negative effects of phone dependence on MPUWW. PRACTICAL APPLICATIONS: To lower MPUWW and thereby minimize the risk of road crashes and associated injuries, it is beneficial to foster present-moment awareness of individuals, encourage individuals to use mobile phones in a balanced and sensible manner, and integrate the enhancement of risk perception into road safety education.

Children's ability to estimate approaching vehicle time-to-arrival following training in a virtual pedestrian environment.

OBJECTIVES: Child pedestrian injuries represent a significant public health challenge. Understanding the most complex cognitive skills required to cross streets helps us understand, improve, and protect children in traffic, as underdeveloped cognitive skill likely impacts children's pedestrian safety. One complex component of street-crossing is the cognitive-perceptual task of judging time-to-arrival of oncoming traffic. We examined capacity of 7- and 8-year-olds to judge time-to-arrival for vehicles approaching from varying distances and speeds, as well as improvement in those judgments following intensive street-crossing training in a virtual reality (VR) pedestrian simulator. METHODS: 500 seven- and eight-year-olds participated in a randomized trial evaluating use of a large kiosk VR versus smartphone-based VR headset to teach street-crossing skills. Prior to randomization into VR training condition and also prior to initiation of any training, children engaged in a video-based vehicle approach estimation task to assess ability to judge traffic time-to-arrival. They then engaged in multiple VR-based pedestrian safety training sessions in their randomly assigned condition until achieving adult functioning. Soon after training and again 6 months later, children repeated the vehicle estimation task. RESULTS: Prior to randomization or training, children were more accurate judging time to arrival for closer versus farther traffic, and rapidly-moving versus slower-moving traffic, but those results were subsumed by a speed x distance interaction. The interaction suggested distance cues were used more prominently than speed cues, and speed had varying effects at different distances. Training group had minimal effect on learning and all children became significantly better at judging vehicle arrival times following training. CONCLUSIONS: Children tend to underestimate vehicle arrival times. Distance cues are more impactful on time-to-arrival judgments than speed cues, but children's estimations based both on manipulations of vehicle speed and manipulations of vehicle distance improved post-training. Improvements were retained six months later. This finding is consistent with psychophysics research suggesting vehicle approach judgments rely on optical size and looming, which are impacted both by vehicle speeds and distances. Implementation of VR-based training for child pedestrian safety is recommended, as it may improve children's judgment of vehicle time-to-arrival, but it must be conducted cautiously to avoid iatrogenic effects.

Risk of pedestrian collision for persons with peripheral field loss: A computational analysis.

SIGNIFICANCE: People with peripheral field loss report colliding with other pedestrians on their blind side(s). We show that, in dyadic collision scenarios between persons, one with field loss, such as homonymous hemianopia, and the other normally sighted pedestrian, collisions occur only if the persons with homonymous hemianopia are overtaking the pedestrians, and the collision risk is concentrated at farther bearing angles than previously suggested. PURPOSE: Prior work computed the risk of collision while simulating both pedestrians as points and did not consider the ability of the other pedestrian's normal vision to avoid the collision. We extended the model to better characterize the open space collision risk posed for persons with homonymous hemianopia by normally sighted pedestrians where both have volume. METHODS: We computed the risk of collision with approaching pedestrians using a model that simulates approaching pedestrians as volumetric entities without vision, volumetric entities with vision, and as points for comparison with the prior work. Collision risk of approaching pedestrians is characterized for all three conditions through spatial collision risk maps and collision risk densities as a function of bearing and radial distances. RESULTS: The collision risk for volumetric pedestrians is slightly different from that of point pedestrians. For volumetric pedestrians simulated with normal vision, the risk of collision was reduced substantially, as the other pedestrians could detect and avoid most impending collisions. The remaining collision risk is from pedestrians approaching at higher bearing angles (>50°) and from shorter radial distances (<2 m). Thus, collisions occurred when the pedestrians started in front of the person with homonymous hemianopia that was overtaking the pedestrian. CONCLUSIONS: The probability of collisions between pedestrians and the person with peripheral field loss is low and occurs only when the person with peripheral field loss is walking from behind the pedestrian at faster speed, thereby overtaking them. Such collisions occur with pedestrians at higher bearing angles, which should be monitored by assistive aids to avoid collisions. The same collision risk applies not only in homonymous hemianopia but also in other peripheral field loss such as monocular vision loss or concentric field loss, as common in retinitis pigmentosa and glaucoma.

The Governance of Traffic Noise Impacting Pedestrian Amenities in Melbourne Australia: A Critical Policy Review.

By identifying a unified aim of Federal, State, and Local government authorities to deliver healthier, more liveable urban spaces and enable walkable neighbourhoods in Melbourne, Australia, questions emerge regarding noise data collection methods and the policies that aim to protect pedestrian areas from potential increases in urban traffic noise. It highlights a missed opportunity to develop strategies that provide explicit guidance for designing more compact urban forms without diminishing pedestrian amenities. This study investigates the governance of traffic-induced noise pollution and its impact on pedestrian amenities in Melbourne, Australia. It aims to identify the government bodies best positioned to protect pedestrians from noise pollution and evaluate the strategic justification for reducing traffic noise to enhance urban walkability. This research employs a semi-systematic policy selection method and a hybrid critique and review method to evaluate the multidisciplinary governance frameworks engaged in the management and mitigation of traffic noise in Melbourne. Key findings reveal that while traffic noise poses significant health risks, current policies overlook its impact on pedestrian amenities in urban areas. This study emphasises the benefits of qualitative and subjective noise data collection to inform policy-makers of the pedestrian aural experience and impacts. Discussion points include noise management strategies and the value of implementing metropolitan-scale noise-mapping to illustrate the impact of noise rather than quantities of sound. The conclusions demonstrate that there is strategic justification for managing traffic-induced noise pollution to protect pedestrian areas within international, federal, and state government policies and implicit rationale at a local level.

Investigating Implicit and Explicit Communication of Highly Automated Vehicles in Japan: How do Light-band eHMIs affect Pedestrians' Willingness to Cross, Trust and Perceived Safety?

In the near future, pedestrians will face highly automated vehicles on the roads. Highly automated vehicles (HAVs) should have safety-enhancing communication tools to guarantee traffic safety, e.g., vehicle kinematics and external human-machine interfaces (eHMIs). Pedestrians, as highly vulnerable road users, depend on communication with HAVs. Miscommunication between pedestrians and HAVs could quickly result in accidents, and this, in turn, could cause severe impairments for pedestrians. Light-band eHMIs have the potential to enhance traffic safety. However, eHMIs have been less explored in Japan so far. As a first-time approach, this experimental online study shed light on the effect of a light-band eHMI on Japanese pedestrians (N=99). In short video sequences, the participants interacted with two differently sized HAVs equipped with light-band eHMI. We investigated the effect of vehicle size (small vs. large), eHMI status (no eHMI vs. static eHMI vs. dynamic eHMI), and vehicle kinematics (yielding vs. non-yielding) on pedestrians' willingness to cross, trust, and perceived safety. To investigate possible side effects of eHMIs, we also included experimental conditions in which the eHMI mismatched the vehicle's kinematics. Results revealed that Japanese were more willing to cross the street and indicated higher trust- and safety ratings when they received information about the vehicle's intention and automation status (dynamic eHMI) compared to when they received no information (no eHMI) or only about the vehicle automation status (static eHMI). Surprisingly, Japanese participants tended to rely on the eHMI when there was mismatching information between eHMI and vehicle kinematics. Overall, we concluded that light-band eHMIs could contribute to a safe future interaction between pedestrians and HAVs in Japan under the requirement that the eHMI is in accordance with vehicle kinematics.

Identifying factors related to pedestrian and cyclist crashes in ACT, Australia with an extended crash dataset.

As vulnerable road users, pedestrians and cyclists are facing a growing number of injuries and fatalities, which has raised increasing safety concerns globally. Based on the crash records collected in the Australian Capital Territory (ACT) in Australia from 2012 to 2021, this research firstly establishes an extended crash dataset by integrating road network features, land use features, and other features. With the extended dataset, we further explore pedestrian and cyclist crashes at macro- and micro-levels. At the macro-level, random parameters negative binomial (RPNB) model is applied to evaluate the effects of Suburbs and Localities Zones (SLZs) based variables on the frequency of pedestrian and cyclist crashes. At the micro-level, binary logit model is adopted to evaluate the effects of event-based variables on the severity of pedestrian and cyclist crashes. The research findings show that multiple factors are associated with high frequency of pedestrian total crashes and fatal/injury crashes, including high population density, high percentage of urban arterial road, low on-road cycleway density, high number of traffic signals and high number of schools. Meanwhile, many factors have positive relations with high frequency of cyclist total crashes and fatal/injury crashes, including high population density, high percentage of residents cycling to work, high median household income, high percentage of households with no motor vehicle, high percentage of urban arterial road and rural road, high number of bus stops and high number of schools. Additionally, it is found that more severe pedestrian crashes occur: (i) at non-signal intersections, (ii) in suburb areas, (iii) in early morning, and (iv) on weekdays. More severe cyclist crashes are observed when the crash type is overturned or struck object/pedestrian/animal; when more than one cyclist is involved; and when crash occurs at park/green space/nature reserve areas.

The efficacy of training to improve road safety in elderly pedestrians: A systematic review.

Elderly pedestrians are involved in disproportionately more vehicle-pedestrian crashes than younger age groups. Training programs have been found to be effective in training children in pedestrian behaviours that improve their safety, however there is no consensus on whether older adults benefit from training. This systematic review aimed to identify whether training is effective for older adult pedestrians through analysis of training type, modalities, and the lasting effects of training. A systematic search of Medline, PsycINFO, and Scopus was conducted in March 2022 and updated in September 2023. Eight studies met the criteria all of which were high quality. Four distinct training types were found: physical (e.g., training physical strength or balance), behavioural (e.g., training specific pedestrian safety behaviours), cognitive (e.g., training reaction time and executive functioning), and educational (training knowledge about pedestrian safety behaviours). Physical training types were found to be most effective, followed by behavioural, cognitive, and educational respectively. Twelve pedestrian behaviours were measured across the eight studies. Reaction time was the most effectively trained outcome, followed by missed crossing opportunities. Errors of stimuli, median accepted time gap, initiation time and crossing were not effectively trained. The effects of training were maintained at follow-up for missed crossing opportunities only. There was preliminary evidence of potential efficacy of training for specific pedestrian safety behaviours, however, the long-term efficacy of training was not promising. Theory-driven research is needed to better understand why some behaviours are more trainable than others. More research is also needed to determine the real-world generalisability if training is to be recommended for older adult pedestrians.

Investigating vehicle-vehicle and vehicle-pedestrian crash severity at street intersections with the latent class parameterized correlation bivariate generalized ordered probit.

Street intersection crashes often involve two parties: either two vehicles hitting each other (i.e., a vehicle-vehicle crash) or a vehicle colliding with a pedestrian (i.e., a vehicle-pedestrian crash). In such crashes, the severity of injuries can vary considerably between the parties involved. It is necessary to understand the injuries of both parties simultaneously to identify the causality of a vehicle-pedestrian or two-vehicle crash. While the latent class ordinal model has been used in crash severity studies to capture heterogeneity in crash propensity, most of these studies are univariate, which is inappropriate for crashes involving two parties. This study proposes a latent class parameterized correlation bivariate generalized ordered probit (LCp-BGOP) model to examine 32,308 vehicle-vehicle and vehicle-pedestrian crashes at intersections in Taipei City, Taiwan. The model parameterizes thresholds and within-crash correlations of crash severity involving two parties and classifies these crashes into two distinct risk groups: the "Ordinary Crash Severity" (OCS) group and the "High Crash Severity" (HCS) group. The OCS group is mainly two-vehicle crashes involving motorcycles. The HCS group comprises vulnerable road users such as pedestrians and cyclists, mainly in mixed traffic with heavy volumes. The results also show that the effects of party-specific factors contributing to injury severity are greater than those of generic factors. Our study provides invaluable insight into intersection crashes, helping to reduce the severity of injuries in vehicle-vehicle and vehicle-pedestrian crashes.

A novel framework for crash frequency prediction: Geographic support vector regression based on agent-based activity models in Greater Melbourne.

The field of spatial analysis in traffic crash studies can often enhance predictive performance by addressing the inherent spatial dependence and heterogeneity in crash data. This research introduces the Geographical Support Vector Regression (GSVR) framework, which incorporates generated distance matrices, to assess spatial variations and evaluate the influence of a wide range of factors, including traffic, infrastructure, socio-demographic, travel demand, and land use, on the incidence of total and fatal-or-serious injury (FSI) crashes across Greater Melbourne's zones. Utilizing data from the Melbourne Activity-Based Model (MABM), the study examines 50 indicators related to peak hour traffic and various commuting modes, offering a detailed analysis of the multifaceted factors affecting road safety. The study shows that active transportation modes such as walking and cycling emerge as significant indicators, reflecting a disparity in safety that heightens the vulnerability of these road users. In contrast, car commuting, while a consistent factor in crash risks, has a comparatively lower impact, pointing to an inherent imbalance in the road environment. This could be interpreted as an unequal distribution of risk and safety measures among different types of road users, where the infrastructure and policies may not adequately address the needs and vulnerabilities of pedestrians and cyclists compared to those of car drivers. Public transportation generally offers safer travel, yet associated risks near train stations and tram stops in city center areas cannot be overlooked. Tram stops profoundly affect total crashes in these areas, while intersection counts more significantly impact FSI crashes in the broader metropolitan area. The study also uncovers the contrasting roles of land use mix in influencing FSI versus total crashes. The proposed framework presents an approach for dynamically extracting distance matrices of varying sizes tailored to the specific dataset, providing a fresh method to incorporate spatial impacts into the development of machine learning models. Additionally, the framework extends a feature selection technique to enhance machine learning models that typically lack comprehensive feature selection capabilities.

Camera-in-the-loop based test scenario generation method for pedestrian collision avoidance system.

The Pedestrian Collision Avoidance System (PCAS) of Intelligent Vehicle (IV) can be effective in preventing the occurrence of traffic accidents. However, the complicated operation environments introduce great challenges to the camera used by the PCAS. Therefore, the camera based PCAS should be fully tested and evaluated before deployment. The traditional simulation test for the camera based PCAS attempted to use geometric or physical simulation models, which have low reality and are suitable for the primary stage of the PCAS development. Camera-in-the-Loop (CIL) test is one of Hardware-in-the-Loop methods that embeds the real camera hardware into the virtual simulation system to test the camera. CIL can utilize the real hardware response while overcoming the common simulation weakness of fidelity. In this paper, we construct a CIL test platform, and propose the CIL based test scenarios generation and scenario parameter impact evaluation method for PCAS. First, we construct the CIL test platform whose image quality and functional confidence are both validated to prove CIL credibility. Second, the PCAS under the test is analyzed and the corresponding test scenario parameters are designed. In order to accelerate the test scenario generation, a Greedy Based Combination test method (GBC) based on the CIL is proposed. The Chi-square analysis and two-factor of variance analysis verification methods are used to analyze the influence of individual and multiple scenario parameters on the PCAS performance. The experiment results show that the GBC improves the test speed by 12 times compared to the traversal test, and the frequency ratio of each scenario parameter is no more than 3% different from that of the traversal test. Also, GBC has an equivalent ability to find the PCAS collision scenarios parameter combination to the traversal test.

Developing equity-aware safety performance functions for identifying hotspots of pedestrian-involved crashes.

Crashes are frequently disproportionally observed in disadvantaged areas. Despite the evident disparities in transportation safety, there has been limited exploration of quantitative approaches to incorporating equity considerations into road safety management. This study proposes a novel concept of equity-aware safety performance functions (SPFs), enabling a distinct treatment of equity-related variables such as race and income. Equity-aware SPFs introduce a fairness distance and integrate it into the log-likelihood function of the negative binomial regression as a form of partial lasso regularization. A parameter λ is used to control the importance of the regularization term. Equity-aware SPFs are developed for pedestrian-involved crashes at the census tract level in Virginia, USA, and then employed to compute the potential for safety improvement (PSI), a prevalent metric used in hotspot identification. Results show that equity-aware SPFs can diminish the effects of equity-related variables, including poverty ratio, black ratio, Asian ratio, and the ratio of households without vehicles, on the expected crash frequencies, generating higher PSIs for disadvantaged areas. Based on the results of Wilcoxon signed-rank tests, it is evident that there are significant differences in the rankings of PSIs when equity awareness is considered, especially for disadvantaged areas. This study adds to the literature a new quantitative approach to harmonize equity and effectiveness considerations, empowering more equitable decision-making in safety management, such as allocating resources for safety enhancement.

Investigating the impact of temporal instability in smart roadway retrofitting on terrain-related crash injury severity.

The advancement of intelligent road systems in developing countries poses unique challenges in identifying risk factors and implementing safety strategies. The variability of factors affecting crash injury severity leads to different risks across levels of roadway smartness, especially in hazardous terrains, complicating the adaptation of smart technologies. Therefore, this study investigates the temporal instability of factors affecting injury severities in crashes across various terrains, with a focus on the evolution of road smartness. Crash data from selected complex terrain regions in Shaanxi Province during smart road adaptation were used, and categorized into periods before, during, and after smart road implementations. A series of mixed logit models were employed to account for unobserved heterogeneity in mean and variance, and likelihood ratio tests were conducted to assess the spatio-temporal instability of model parameters across different topographic settings and smart processes. Moreover, a comparison between partially constrained and unconstrained temporal modeling approaches was made. The findings reveal significant differences in injury severity determinants across terrain conditions as roadway intelligence progressed. On the other hand, certain factors like pavement damage, truck and pedestrian involvement were identified that had relatively stable effects on crash injury severities. Out-of-sample predictions further emphasize the need for modeling across terrain and roadway development stages. These insights are crucial for developing tailored safety measures for smart road retrofitting in different terrain conditions, thereby supporting the transition towards smarter road systems in developing regions.

Pedestrian flow-environmental pollutants interactions and health risks to residents in high-occupancy public areas of apartment buildings.

The current interaction of pedestrian flow and environmental pollutants in high-occupancy public areas of apartment and the risks of residents being exposed to environmental pollutants are issues that are often overlooked but urgently need to be addressed. In this study, we provide a comprehensive of pedestrian flow-environmental pollutants interactions and health risks to residents in first-floor public areas of apartment with high-occupancy. The main findings indicate that under closed management conditions, there is a significant increase in TVOC and noise levels during the peak periods of nighttime pedestrian flow. In the correlation analysis, the significant impact of time granularity selection in clarifying the correlation between pedestrian flow and environmental pollutants has been highlighted, with larger time granularities generally showing stronger correlations, while finer time granularities may help identify specific risks in areas directly connected to the external environment. There is a significant correlation exists between pedestrian flow and environmental pollutants (TVOC, ozone, and noise), with higher concentrations of these pollutants observed during peak pedestrian flow periods, thereby increasing the risk of residents being exposed to adverse environmental conditions. To mitigate the risks associated with TVOC pollution and noise exposure, it is crucial to maintain proper ventilation, avoid conducting cleaning or maintenance activities during peak hours, and implement noise-reducing measures, such as distancing noise sources from residential areas or installing soundproofing barriers. Additionally, the study identifies total volatile organic compounds originating from property maintenance activities and clarifies their dispersion patterns, emphasizing the importance of developing robust, standardized maintenance protocols for indoor environmental quality assurance. This research can improve the environmental sustainability of apartment buildings and provide a theoretical basis for the development of environmental health strategies for high-occupancy public areas of apartment buildings.

A comparison of factors influencing the safety of pedestrians accessing bus stops in countries of differing income levels.

Pedestrian fatalities comprise a quarter of all traffic deaths in Low-and-Middle-Income Countries (LMICs). The use of safer modes of transport such as buses can reduce road trauma as well as air pollution and traffic congestion. Although travelling by bus is safer than most other modes, accessing bus stops can be risky for pedestrians. This paper systematically reviews factors contributing to the safety of pedestrians near bus stops in countries of differing income levels. The review included forty-one studies from high (20), upper-middle (13) and lower-middle income countries (8) during the last two decades. The earliest research was conducted in high-income countries (HICs), but research has spread in the last decade. The factors influencing pedestrian safety fell into three groups: (a) characteristics of road users, (b) characteristics of bus stops and (c) characteristics of the road traffic environment. Pedestrians near bus stops are frequently exposed to a high risk of collisions and fatalities due to factors such as unsafe pedestrian behaviours (e.g., hurrying to cross the road), lack of bus stop amenities such as safe footpaths, high traffic speeds and traffic volumes, multiple lanes, and roadside hazards (e.g., parked cars obscuring pedestrians). Road crash statistics are commonly used to identify unsafe bus stops in HICs but the unavailability and unreliability of data have prevented more widespread use in LMICs. Future research is recommended to focus on surrogate safety measures to identify hazardous bus stops for pedestrians.

Sustainable repurpose of end-of-life fiber reinforced polymer composites: A new circular pedestrian bridge concept.

In response to global challenges in resource supply, many industries are adopting the principles of the Circular Economy (CE) to improve their resource acquisition strategies. This paper introduces an innovative approach to address the environmental impact of waste Glass Fiber Reinforced-Polymer (GFRP) pipes and panels by repurposing them to manufacture structural components for new bicycle and pedestrian bridges. The study covers the entire process, including conceptualization, analysis, design, and testing of a deck system, with a focus on the manufacturing process for a 7-m-long prototype bridge. The study shows promising results in the concept of a sandwich structure utilizing discarded GFRP pipes and panels, which has the flexibility to account for variabilities in dimensions of incoming products while still meeting mechanical requirements. The LCA analysis shows that the transportation of materials is the governing contributing factor. It was concluded that further development of this concept should be accompanied by a business model that considers the importance of the contributions from the whole value chain.

Meteorological gaps in audits of pedestrian environments: a scoping review.

BACKGROUND: Weather and season are determinants of physical activity. Therefore, it is important to ensure built environments are designed to mitigate negative impacts of weather and season on pedestrians to prevent these losses. This scoping review aims to identify built environment audits of pedestrian environments developed for use during a specific weather condition or season. Secondly, this review aims to investigate gaps in the inclusion of relevant weather mitigating built environment features in pedestrian environment audit tools. METHODS: Following a standard protocol, a systematic search was executed in CINAHL, Medline and Web of Science to identify built environment audit tools of pedestrian spaces. These databases were chosen since they are well-known to comprehensively cover health as well as multi-disciplinary research publications relevant to health. Studies were screened, and data were extracted from selected documents by two independent reviewers (e.g., psychometric properties and audit items included). Audit items were screened for the inclusion of weather mitigating built environment features, and the tool's capacity to measure temperature, precipitation, seasonal and sustainability impacts on pedestrians was calculated. RESULTS: The search returned 2823 documents. After screening and full text review, 27 articles were included. No tool was found that was developed specifically for use during a specific weather condition or season. Additionally, gaps in the inclusion of weather mitigating items were found for all review dimensions (thermal comfort, precipitation, seasonal, and sustainability items). Poorly covered items were: (1) thermal comfort related (arctic entry presence, materials, textures, and colours of buildings, roads, sidewalk and furniture, and green design features); (2) precipitation related (drain presence, ditch presence, hazards, and snow removal features); (3) seasonal features (amenities, pedestrian scale lighting, and winter destinations and aesthetics); and (4) sustainability features (electric vehicle charging stations, renewable energy, car share, and bike share facilities). CONCLUSIONS: Current built environment audit tools do not adequately include weather / season mitigating items. This is a limitation as it is important to investigate if the inclusion of these items in pedestrian spaces can promote physical activity during adverse weather conditions. Because climate change is causing increased extreme weather events, a need exists for the development of a new built environment audit tool that includes relevant weather mitigating features.