A variable speed limit control approach for freeway tunnels based on the model-based reinforcement learning framework with safety perception.

To improve the traffic safety and efficiency of freeway tunnels, this study proposes a novel variable speed limit (VSL) control strategy based on the model-based reinforcement learning framework (MBRL) with safety perception. The MBRL framework is designed by developing a multi-lane cell transmission model for freeway tunnels as an environment model, which is built so that agents can interact with the environment model while interacting with the real environment to improve the sampling efficiency of reinforcement learning. Based on a real-time crash risk prediction model for freeway tunnels that uses random deep and cross networks, the safety perception function inside the MBRL framework is developed. The reinforcement learning components fully account for most current tunnels' application conditions, and the VSL control agent is trained using a deep dyna-Q method. The control process uses a safety trigger mechanism to reduce the likelihood of crashes caused by frequent changes in speed. The efficacy of the proposed VSL strategies is validated through simulation experiments. The results show that the proposed VSL strategies significantly increase traffic safety performance by between 16.00% and 20.00% and traffic efficiency by between 3.00% and 6.50% compared to a fixed speed limit approach. Notably, the proposed strategies outperform traditional VSL strategy based on the traffic flow prediction model in terms of traffic safety and efficiency improvement, and they also outperform the VSL strategy based on model-free reinforcement learning framework when sampling efficiency is considered together. In addition, the proposed strategies with safety triggers are safer than those without safety triggers. These findings demonstrate the potential for MBRL-based VSL strategies to improve traffic safety and efficiency within freeway tunnels.

Identifying multilevel predictors of behavioral outcomes like park use: A comparison of conditional and marginal modeling approaches.

This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in 128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance.

Association between area-level walkability and glycated haemoglobin: a Portuguese population-based study.

Diabetes poses a substantial disease burden, prompting preventive interventions. Physical inactivity, a major risk factor for type 2 diabetes, can potentially be mitigated by enhancing area-level walkability. Despite this, limited population-based studies have investigated the link between walkability and objective diabetes measures. Our study aims to estimate the association between area-level walkability and individual glycated haemoglobin levels in the Portuguese adult population without the diagnosis of diabetes. Data from the 2011 census and an updated street map were obtained to construct a walkability index based on residential density, land-use mix, and street connectivity. Individual health data were sourced from The National Health Examination Survey (INSEF) 2015, a representative survey of the Portuguese adult population. Gamma regression was employed for estimation of the main associations, revealing that residing in moderately walkable areas significantly reduced average glycated haemoglobin levels (Exp(ß) = 0.906; 95% CI: 0.821, 0.999) compared to the least walkable areas. The association was less pronounced and not statistically significant for the third tertile of walkability (Exp(ß) = 0.919; 95% CI: 0.822, 1.028). Our findings highlight a nonlinear protective association between walkability and glycated haemoglobin, emphasizing the potential policy implications for urban planning, diabetes prevention, and health promotion.

An assessment of the perceptual elements of urban streets based on the context of urban tourism - The case of Sheffield.

Background: After COVID-19, more and more travelers are more inclined to walk in cities, and the sensory elements of streets can have a significant impact on urban tourism. Local residents and travelers have different perceptions of the street and preferences for its use. The purpose of this study is to evaluate and analyse the streets from the perspective of locals and travelers. Method: In this study, a questionnaire was designed to obtain local residents' and travelers' evaluations of the sensory elements of the street and a quadrant analysis of the street's sensory elements was carried out using the IPA-Kano model. Results: The results of the study show that travelers are particularly concerned about maps and signage guidance, while local residents are more concerned about the green environment of the surroundings and how well it is maintained. Conclusion: There is a difference in the indicators chosen by the two groups in the results of the comparison between locals and travelers, and this study is hoped to provide some data support for future urban managers and designers to learn from and refer to for street improvements and renewal.

Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a need for more understanding of its potential safety impact. Unfortunately, many advanced real-time crash prediction models encounter an important challenge in their applicability due to their demand for a substantial volume of data for direct modeling. To tackle this challenge, we proposed a simple yet effective approach - anomaly detection learning, which formulates model as an anomaly detection problem, solves it through normality feature recognition, and predicts crashes by identifying deviations from the normal state. The proposed approach demonstrates significant improvement in the Area Under the Curve (AUC), sensitivity, and False Alarm Rate (FAR). When juxtaposed with the prevalent direct classification paradigm, our proposed anomaly detection learning (ADL) consistently outperforms in AUC (with an increase of up to 45%), sensitivity (experiencing up to a 45% increase), and FAR (reducing by up to 0.53). The most performance gain is attained through the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) in an ensemble, resulting in a 0.78 AUC, 0.79 sensitivity, and a 0.22 false alarm rate. Furthermore, we analyzed model features with a game-theoretic approach illustrating the most correlated features for accurate prediction, revealing the attention of advanced convolution neural networks to occupancy features. This provided crucial insights into improving crash precaution, the findings from which not only benefit private stakeholders but also extend a promising opportunity for governmental intervention on the express lane. This work could promote express lane with more efficient resource allocation, real-time traffic management optimization, and high-risk area prioritization.

Investigating built environment and traffic flow impact on crash frequency in urban road networks.

While numerous studies have examined the factors that influence crash occurrence, there remains a gap in understanding the intricate relationship between built environment, traffic flow, and crash occurrences across different spatial units. This study explores how built environment attributes, and dynamic traffic flow characteristics affect crash frequency by focusing on proposed traffic density-based zones (TDZs). Utilizing a comprehensive dataset from Greater Melbourne, Australia, this research emphasizes on the dynamic traffic flow variables and insights from the Macroscopic Fundamental Diagram model, considering parameters such as shockwave velocity and congestion index. The association between the potential influencing factors and crash frequency is examined using a random parameter negative binomial regression model. Results indicate that the data segmentation based on TDZs is instrumental in establishing a more refined crash model compared to traditional planning-based zones, as demonstrated by improved goodness-of-fit measures. Factors including density (e.g., employment density), network design (e.g., road density and highway density), land use diversity (e.g., job-housing balance and land use mixture), and public transit accessibility (e.g., bus route density) are significantly associated with crash occurrence. Furthermore, the unobserved heterogeneity effects of the shockwave velocity and congestion index on crashes are revealed. The study highlights the significance of incorporating dynamic traffic flow variables in understanding crash frequency variations across different spatial units. These findings can inform optimal real-time traffic monitoring, environmental design, and road safety management strategies to mitigate crash risks.

Redefining Age-Friendly Neighbourhoods: Translating the Promises of Blue Zones for Contemporary Urban Environments.

The longevity and healthy ageing observed in Blue Zones offer valuable insights for contemporary urban neighbourhood planning and design. This paper reviews the age-friendly features of the built environment in Blue Zones, aiming to translate these insights into actionable strategies for urban neighbourhood development. Employing a systematic literature review and Convolutional Neural Networks (CNNs) analysis of Google Street View imagery, this study assesses the built environments in Blue Zones, including housing, public spaces, and transportation systems. Key findings highlight the presence of adaptable housing, building designs that foster a connection with nature, and semi-public spaces that encourage social interaction and physical activity. A notable emphasis on walkability and limited public transport access was observed. The CNN analysis corroborated these findings, providing a quantitative view of age-friendly features. This research contributes to the academic discourse in urban planning and design by providing practical insights for developing age-friendly neighbourhoods, inspired by Blue Zones. It concludes by offering policy advice and future research directions for creating sustainable and inclusive urban environments conducive to ageing populations.

Enhancing intersection safety in autonomous traffic: A grid-based approach with risk quantification.

Existing studies on autonomous intersection management (AIM) primarily focus on traffic efficiency, often overlooking the overall intersection safety, where conflict separation is simplified and traffic conflicts are inadequately assessed. In this paper, we introduce a calculation method for the grid-based Post Encroachment Time (PET) and the total kinetic energy change before and after collisions. The improved grid-based PET metric provides a more accurate estimation of collision probability, and the total kinetic energy change serves as a precise measure of collision severity. Consequently, we establish the Grid-Based Conflict Index (GBCI) to systematically quantify collision risks between vehicles at an autonomous intersection. Then, we propose a traffic-safety-based AIM model aimed at minimizing the weighted sum of total delay and conflict risk at the intersection. This entails the optimization of entry time and trajectory for each vehicle within the intersection, achieving traffic control that prioritizes overall intersection safety. Our results demonstrate that GBCI effectively assesses conflict risks within the intersection, and the proposed AIM model significantly reduces conflict risks between vehicles and enhances traffic safety while ensuring intersection efficiency.

Investigating safety and cost-effectiveness of cable median barriers in Louisiana.

OBJECTIVES: Cable median barriers (CMBs) are installed on freeway medians to prevent cross-median crashes and reduce the severity of median-related crashes. Though CMBs are effective in preventing cross-median crashes, they are also known to increase the number of property damage-only (PDO) crashes. The higher frequency of PDO crashes could result in increased CMB maintenance and repair expenses. The aim of this study is to evaluate the safety impact and economic justification of CMBs in Louisiana. METHODS: Initially, a flowchart was developed using Louisiana crash data to identify targeted crashes, such as median-related and cross-median crashes. This was followed by a 3-year observational before-and-after crash analysis with an emphasis on head-on collisions and crashes involving large trucks. Using a 4-step improved prediction method, crash modification factors were then developed to quantitatively assess the impact of CMBs on crash outcomes, accounting for and adjusting to changes in the annual average daily traffic (AADT) and relevant crash frequencies before and after CMB implementation. Finally, an exhaustive benefit-cost analysis was conducted to determine the cost-effectiveness of CMBs. RESULTS: The results revealed that CMBs significantly reduced cross-median crashes of all severities. However, an increase in PDO crashes was observed in both total and median-related crashes. Large truck cross-median crashes and head-on collisions also decreased significantly after CMB implementation. Testing Level 4 (TL-4) CMBs were found to be more effective in preventing vehicles from crossing the median and in reducing crashes of higher severity levels. The benefit-cost ratios, calculated using economic crash unit costs for both total and targeted crashes, were greater than 1. Notably, the estimated benefit-cost ratios were considerably higher, demonstrating that CMBs are cost-effective countermeasures for enhancing traffic safety. CONCLUSION: This study contributes to the understanding of CMB performance from both traffic safety and economic perspectives. The findings may assist transportation agencies in making decisions regarding the management of CMB systems. Based on the comprehensive analysis of CMBs on Louisiana freeways, this project has revealed that CMBs are an effective and economically justified crash countermeasure. Thus, further implementation of CMBs is recommended until better alternatives are available.

Built environment and physical activity in adolescents: Use of the kernel density estimation and the walkability index.

The availability of places for physical activity (PA) and the walkability of the neighborhood can impact the level of PA of adolescents. However, studies of this nature are still limited in Latin America. This study had two objectives: 1- using kernel density estimative, it investigated whether individuals living near PA places that are more intensely distributed than dispersed are more likely to be sufficiently active; 2-checked whether adolescents who live in neighborhoods with better walkability have a greater chance of being sufficiently active. Were evaluated 292 adolescents and PA was measured by accelerometry. Were measured five environmental variables for composing the walkability index. 98 PA points (places) were identified and destinations within these areas were geocoded and kernel density estimates (KDE) of places intensity were created using kernels (radius) of 400m (meters), 800, 1200 and 1600m. Using Logistic Regression, the association between the intensity of PA places (classified into quartiles Q1(smallest)-Q4(largest)) and the probability of being "Sufficient PA"; and the association between walkability (quartiles Q1(least)-Q4(highest)) and the probability of being "PA Sufficient " were estimated (p≤0.05). There were associations only for the intensities of places with the largest radius. Among adolescents who lived in places with higher intensity compared with lower intensity places: 1200m (Q3, OR 2.18 95% CI 1.12-4.22; Q4, OR 2.77 95% CI 1.41-5.43) and 1600m (Q3, OR 3.68 95%CI 1.86-7.30; Q4, OR 3.69 95%CI 1.86-7.30) were more likely to be "Sufficient PA". There were also associations for walkability, where those living in places with better walkability (Q4, OR 2.58 95% CI 1.33-5.02) had greater chances of being "Sufficient PA" compared to Q1. In conclusion, living in places with bigger densities and better walkability increases adolescent's chances of being "Sufficient PA".

Walkability and socio-economic status in relation to walking, playing and sports practice in a representative Spanish sample of youth: The PASOS study.

PURPOSE: Physical activity (PA) provides multiple health-related benefits in children and adolescents, however, at present, the majority of young people are insufficiently physically active. The aim of this study was to evaluate if neighborhood walkability and/or socio-economic status (SES) could affect the practice of walking, play outdoors and sports practice in a representative sample of Spanish children and adolescents. METHODS: A sample of 4092 youth (aged 8-16 years old) from 245 primary and secondary schools in 121 localities from each of the 17 Spanish autonomous communities participated in the study. Walk Score was used to evaluate walkability of the neighborhood and household income was used as an indicator of SES. A 7-item self-reported validated questionnaire, was used to assess PA levels, and in a subsample of 10% of the participants, randomly selected from the entire sample, PA was objectively measured by accelerometers. RESULTS: Youth from more walkable areas reported more minutes walking per day compared with those from less walkable neighborhoods (51.4 vs 48.8 minutes, respectively). The lowest average minutes spent in playing outdoors was found among participants from low-SES and low-walkable neighborhoods. Neighborhood SES influenced on the participation in team sports during the weekend, being this participation higher in high SES neighborhoods. CONCLUSION: Providing high walkable environments seems a good strategy to promote PA regardless SES levels. It seems that improving the walkability is a key component to partially overcome the SES inequalities, especially in urban areas with low SES. High-SES environments can offer better sports facilities and more organized physical activities than low-SES ones.

Crash risk estimation of Heavy Commercial vehicles on horizontal curves in mountainous terrain using proactive safety method.

Heavy commercial vehicles (HCVs) face elevated crash risks in mountainous terrains due to the challenging topography and intricate geometry, posing a significant challenge for transportation agencies in mitigating these risks. While safety studies in such terrains traditionally rely on historical crash data, the inherent issues associated with crash data have led to a shift towards proactive safety studies using surrogate safety measures (SSM) in recent years. However, the scarcity of accurate microscopic data related to HCV drivers has limited the application of proactive safety studies in mountainous terrains. This study addresses this gap by employing an SSM known as anticipated collision time (ACT) to explore the impact of horizontal curves on the crash risk of HCVs in mountainous terrain. To perform the crash risk analysis, a collection of videos was gathered from horizontal curves in the mountainous terrain along the Guwahati-Shillong bypass in the Northeastern region of India. Subsequently, trajectories were extracted from these videos using semi-automated image processing software. Traffic conflicts were identified using ACT, and the crash risk was estimated through the Peak-Over Threshold (POT) approach of the Extreme Value Theory (EVT). The findings indicate that Run-Off-Road (ROR) traffic events happen more frequently on or near the horizontal curves falling in mountainous terrain. However, the frequency of severe ROR traffic events is lower, indicating the lower propensity for such collisions on the selected curves. The threshold for the safety margin of ROR traffic events involving HCVs was 2 s. The study revealed that stationary models exhibit an overestimation of crash frequency (0, 6) compared to the observed crash frequency (0, 2). Consequently, non-stationary crash risk models were developed, incorporating road geometry and the braking and yaw rates of HCVs as covariates. The results demonstrate that the estimated confidence bounds (1, 2) align with the observed crash frequency (0, 2), emphasizing the applicability of POT models for safety analysis in mountainous terrains in India. The study identified curve radius, length of the approach tangent, and the distance between the center points of horizontal and vertical curves as influential factors affecting the Run-Off-Road (ROR) crash risk of HCVs. Notably, sharp curves with radii less than 200 m or more are associated with a significantly higher crash risk. Additionally, an increased distance between the midpoints of horizontal and vertical curves beyond 1 m was found to escalate the ROR crash risk of HCVs. To mitigate these risks, it is recommended to reduce the length of the approach tangent to prevent high-speed travel on sharp curves. Furthermore, proper signage should be strategically placed to warn drivers and avert potential hazards.

Crash modification factors for high friction surface treatment on horizontal curves of two-lane highways: A combined propensity scores matching and empirical Bayes before-after approach.

Horizontal curves are locations that, as a result of the changing alignment, may be a contributing factor in roadway departure crashes. One low-cost countermeasure to mitigate crashes at these locations is the installation of the high friction surface treatment (HFST), which increases roadway friction and is intended to help keep drivers on the roadway when traversing a horizontal curve. This treatment has been implemented at numerous curves in Pennsylvania, but the overall safety effectiveness is not known. The purpose of this study is to estimate a suite of Crash Modification Factors (CMFs) for HFST applied to curve sections of undivided two-lane roadways. A novel combination of the empirical Bayes observational before-after study design and propensity score matching was used to estimate CMFs for multiple crash types, crash severities, and roadway settings (urban and rural). Propensity score matching was implemented to identify the most appropriate reference group to use within the empirical Bayes methodology. The results indicate that the installation of HFST is associated with a statistically significant decrease in all crash types and severities considered.

Quantifying Area-Level Physical Activity Offerings in Social Context: A Novel Concept That Goes Beyond Walkability and Access to Open Spaces.

BACKGROUND: Social support is a crucial factor influencing the sustainability of physical activity (PA). This proof-of-concept study presents the development of a Social Physical Activity Index for Area (SPAIFA) an indicator reflecting opportunities for individuals to actively participate as part of a group within which opportunities for social interaction can be developed. METHODS: Six government councils in the state of New South Wales, Australia, were selected encompassing 174 suburbs. Using 2 search engines' map tools, we identified PA venues for each suburb (eg, park, studios, etc). To enumerate activities per suburb, we used (1) venue websites, (2) New South Wales Office of Sport website, (3) national websites of grassroots PA for nonorganized activity (eg, parkrun, meetup, etc), and (4) social media. The database was linked to the suburb demographic profile, the area disadvantage score, walkability and open space scores, and the proportion of insufficiently active residents. Spatial analysis techniques were used to identify SPAIFA clusters. RESULTS: SPAIFA councils' average was 9.9 activities per 10,000 people (ranging from 6.6/10,000 to 16.2/10,000). SPAIFA-Old (ie, activities specific to older adults) varied significantly (ranging from 11.7/10,000 to 0.8/10,000 seniors). Disadvantaged areas and a high proportion of insufficiently active residents were associated with being classified as low SPAIFA (P < .01). Three clusters of low SPAIFA were identified, and 17 high-risk areas where low SPAIFA was compounded by poor environmental support. CONCLUSIONS: SPAIFA can be used by councils and policymakers as an indicator for monitoring and intervening in areas where natural and/or urban design is not conducive for PA.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

Research on traffic accident prediction of expressway tunnel based on B-NB model.

OBJECTIVE: The study investigates the relationship between traffic accidents in expressway tunnels and their influencing factors, with the aim of predicting traffic accidents within tunnels and presenting reasonable recommendations to improve tunnel safety. METHODS: The study utilizes a dataset of 586 traffic accidents occurring exclusively within 8 tunnels along a Guangdong Province expressway from 2017 to 2021. It applies the geometric alignment consistency principle to segment road sections, defines tunnel boundaries based on driving behavior, and employs a Bayesian-modified negative binomial regression model (B-NB model) to identify 6 significant variables from a pool of 17 factors. RESULTS: The predictive performance of the B-NB model demonstrated similarities to that of the fixed parametric model. This outcome might be attributed to the chosen prior distribution settings and the limited amount of data. Nonetheless, the model effectively captures relationships among variables, leading to improved accuracy in accident prediction and the predictive model achieves a 76.1% accuracy rate. CONCLUSIONS: Drawing from the estimation results, practical measures are suggested across three dimensions: road geometric alignment design, tunnel traffic safety facilities, and traffic emergency management. These proposals aim to ameliorate the severe consequences of tunnel accidents. Future research will explore an in-depth comparison of estimation results, considering the impact of time and variable correlation on the prediction model by expanding the existing data. This will guide the direction of subsequent research endeavors.

The built environment and cancer survivorship: A scoping review.

BACKGROUND: There are more than 32 million cancer survivors worldwide. The built environment is one of the contextual factors that may influence cancer survivorship. However, studies investigating the interdisciplinary field of the built environment and cancer survivorship are lacking. OBJECTIVE: To conduct a systematic review of the existing literature regarding the relationship between the built environment and cancer survivorship, identify any knowledge gaps, and recommend future research directions. METHODS: A systematic literature search was performed by searching OVID Medline, Embase, CINAHL, and Web of Science Core Collection. RESULTS: Of 4235 unique records identified, 26 studies met eligibility criteria. Neighborhood walkability and greenness were the most examined built environment characteristics among the included studies. Walkability was found to be associated with various cancer survivorship experience, including increased levels of physical activity, lowered body mass index, and improved quality of life. The association between greenness and cancer survivorship outcomes were inconsistent across the included studies. Additionally, studies have reported the relationship between light and noise pollution and sleep among cancer survivors. Regarding blue space, in one qualitative study, breast cancer survivors brought up the healing properties of water. CONCLUSION: Our scoping review demonstrated a breadth of current cancer survivorship research in the field of neighborhood walkability and greenness, but fewer studies detailing other aspects of the built environment as defined by this review, such as light pollution, noise pollution, and blue space. We identified future research directions for those interested in this interdisciplinary field, which can provide insights for urban planners and policy makers on how to best leverage the built environment to promote the health and wellbeing of cancer survivors.

Short-term Safety Performance Functions by Random Parameters Negative Binomial-Lindley model for Part-time Shoulder Use.

Part-time Shoulder Use (PTSU) is a traffic management and operation strategy that allows the use of the left or right shoulder as a travel lane, typically during the peak hours of the day. Though PTSU is an effective strategy for increasing roadway capacity in congested traffic conditions, there is very limited quantitative information about PTSU design elements and operational strategy in the existing literature, which could impact the occurrence of crashes on freeways. This study contributes to the safety literature by analyzing various potential crash contributing factors related to PTSU operation and design elements through the development of short-term Safety Performance Functions (SPFs). A comparison of the estimated models demonstrated that by utilizing the mixed distribution and allowing the posterior parameter estimates of explanatory variables to vary from one observation to another, the Random Parameters Negative Binomial-Lindley (RPNB-L) model outperformed the traditional NB and fixed coefficient NB-L models. The results of the proposed RPNB-L model indicated that the PTSU implemented sections experienced a lower number of traffic crashes compared to the non-PTSU freeway sections. Among the attributes related to PTSU operation and design elements, the usage of the leftmost shoulder lane as PTSU, the presence of emergency rest areas for damaged vehicles, and adequate shoulder width would significantly reduce crash frequency for the PTSU implemented freeways. Moreover, investigation of the identified hotspots revealed that the transition areas (start/end locations of PTSU) are the most critical sections. The findings from this research could assist transportation agencies to take appropriate countermeasures for preventing and reducing crash occurrences on PTSU implemented freeways.

Impacto de la arquitectura del hospital en la experiencia de parto: un estudio fenomenológico con madres expertas en su diseño / Impact of hospital architecture on the birthing experience: a phenomenological study with mothers-to-be who are design experts

Fundamento. El lugar donde paren las madres condiciona su proceso de parto y nivel de satisfacción. El objetivo de este estudio es identificar las experiencias y percepciones acerca de los elementos de diseño del entorno del parto hasta el alta hospitalaria, que influyen en la experiencia de las madres a largo plazo. Metodología. Investigación fenomenológica de tipo método biográfico, a través del análisis temático inductivo de veinticinco testimonios de parto en el hospital, escritos por madres arquitectas, ingenieras, paisajistas o diseñadoras de interiores. Resultados. Los resultados se organizaron en cuatro temas y siete subtemas. El primer tema es la “Impresión a primera vista y largo plazo” que se subdivide en los subtemas “Itinerario despersonalizado en accesos y pasillos” y “Búsqueda instintiva de conexión con la naturaleza”. El segundo tema trata sobre el “Acompañamiento y arropamiento durante el proceso de parto” y se subdivide en “Como en un hotel: espacio para el movimiento y adaptación personalizada” y “Desamparo, frío e incertidumbre: espacios donde estar contra su voluntad”. El tercer tema son los “Daños (en espacios) colaterales”, que engloba “La integración de los aseos en el proceso de parto”, los “Quirófanos inmutables ante el parto por cesárea” y las “Salas de neonatos que no integran a las familias”. El cuarto tema incluye “Propuestas de mejora para nuevos diseños”. Conclusiones. Esta investigación permite profundizar en aspectos de diseño identificados en literatura reciente y mostrar que son necesarios más estudios que incorporen la experiencia de la mujer en el proceso del parto para promocionar políticas de diseño basadas en evidencias. (AU)

Background. The birthplace has a crucial role in shaping the childbirth experience and mothers’ satisfaction levels. This study aimed to identify the experiences and perceptions that may have an impact in the long-term on mothers’ birthing experience, considering hospital design features in the birthing environment until discharge. Methods. Inductive thematic analysis of twenty-five hospital labor testimonies employing a phenomenological research approach and utilizing a biographical method. Participants were women with a professional background in architecture, landscape architecture, engineering, or interior design. Results. The results are organized into four themes and seven subthemes. The first theme is “First sight and long term impression” which is subdivided into the subthemes “Depersonalized itinerary in entrances and corridors” and “Instinctive search for connection with nature”. The second theme deals with “Accompaniment and tucking in during the birthing process”, subdivided into “Hotel-like: space for movement and personalized adaptation” and “Helplessness, cold and uncertainty: spaces to be against one’s will”. The third theme is “Damage in collateral rooms”, which includes “The integration of toilets in the birthing process”, “Operating rooms unchangeable in the face of cesarean delivery” and “Neonatal units that do not integrate families”. Finally, the fourth theme includes “Improvement proposals for new designs”. Conclusions. This study contributes to the existing literature by deepening the understanding of the design features identified in hospitals in recent studies. Further research incorporating the experiences of women in the birthing process is needed to facilitate evidence-based design policies. (AU)