Intersection Density Research Articles

The Criteria for Transition of Fluid to Nonlinear Flow for Fractured Rocks: The Role of Fracture Intersection and Aperture

Understanding the fluid pattern is of special significance for estimating the hydraulic conductivity of fractured rock masses. The nonlinearity of fluid flow in discrete fracture networks (DFNs) originates from inertial effects and is enhanced by complex geometric topologies, which produces additional viscous friction and is subject to inertia effects, consequently transitioning the fluid to the nonlinear flow regime. Therefore, it is important to obtain the critical conditions for the transition of a fluid from laminar to turbulent flow. To investigate the role of fracture aperture and fracture intersection on the onset of the transition of a fluid to nonlinear flow in fractured rocks, the fluid dynamic computation was performed by solving Navier–Stokes (N–S) equations in DFN models. The results show that the flow flux initially linearly correlates with the hydraulic gradient (J) and the permeability of DFNs initially remains constant. As the hydraulic gradient increases, the flow flux presents a strong nonlinear relationship with the hydraulic gradient, and the permeability decreases dramatically. In particular, significant inertial effects appear earlier with a large fracture aperture or a dense fracture intersection. A critical hydraulic gradient (Jc) is proposed to judge the onset of nonlinear flow. The mathematical expression of Jc and Forchheimer coefficients A and B involving the fracture aperture and fracture intersection density is established through a multiple regression algorithm. Finally, the reliability of the predictive model was verified by comparing the results of the prediction and fluid dynamic computation of a series of DFN models with well-known geometric distributions. The consistency of the fitted equations and a correlation coefficient greater than 0.9 between them indicate that the predictive model proposed in this study is reliable.

Characterization of the genesis and spatial variability in tectonic fractures in the Gaosong ore field (South China).

This study examines fractures in the Gaosong ore field to determine the main factors affecting the spatial variability in the fracture structure. The attributes of fractures, including the fracture orientation, intensity and intersection density, in the Wuzishan anticline and near the Lotus mountain fault in the Gaosong ore field in the GeJiu ore district were extracted by using a modified circular scanning line method. The fracture intensity and intersection density were analyzed based on the semivariance geostatistics function by using the volume of variation and the amount of relative variability. These parameters quantitatively describe the spatial variability in the fracture structure. The mean and standard variance of fracture intensity and intersection density in the ore field decrease with distance from the Lotus mountain fault, while the coefficient of variation increases. The spatial anisotropy is closely related to the axial direction of the Wuzishan anticline and the orientation of the Lotus mountain fault. The main factors affecting the spatial variability in the fault structure can be determined with the semivariance geostatistics function, and the results are useful for studying the geology of the mining area and can help to construct an accurate structural model to serve the needs of mine production.

How Does the Built Environment Affect Drunk-Driving Crashes? A Spatial Heterogeneity Analysis

In this research, 3356 alcohol-related traffic crashes were obtained from blood-alcohol test reports in Tianjin, China. Population density, intersection density, road density, and alcohol outlet densities, including retail density, entertainment density, restaurant density, company density, hotel density, and residential density, were extracted from 2114 traffic analysis zones (TAZs). After a spatial autocorrelation test, the multiple linear regression model (MLR), geographically weighted Poisson regression model (GWPR), and semi-parametric geographically weighted Poisson regression model (SGWPR) were utilized to explore the spatial effects of the aforementioned variables on drunk-driving crash density. The result shows that the SGWPR model based on the adaptive Gaussian function had the smallest AICc value and the best-fitting accuracy. The residential density and the intersection density are global variables, and the others are local variables that have different influences in different regions. Furthermore, we found that the influence of local variables in the economic–technological development area shows significantly different characteristics compared with other districts. Thus, a comprehensive consideration of spatial heterogeneity would be able to improve the effectiveness of the programs formulated to decrease drunk driving crashes.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BackgroundMost studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours. MethodsWe used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations. ResultsNeighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure. ConclusionsWithin a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents’ cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

Nonlinear impact analysis of built environment on urban road traffic safety risk

With the rapid development of economy, the increasing number of motor vehicles and the total road mileage, which leads to the increasingly prominent traffic safety problems. In order to explore the quantitative relationship between the built environment and the risk of urban road traffic safety, this paper reconstructs the built environment system based on the ‘5D' element model of the built environment combined with the factors influencing traffic safety risks, and describes the built environment from multiple aspects such as density, diversity &traffic design etc, and then build the gradient lift decision tree model to explore the importance and dependency of variables. The empirical analysis selects a district in Chongqing as the research unit, and the results show that: the RMSE the model was 0.0036, the MAPE was 1.9%, and the determination coefficient R2 was 0.84. GBDT algorithm results shows: the cumulative importance of population density, road facilities, intersection density, secondary road and branch road density, average intersection distance, land use mix, and economic density reaches 77.87%. Some variables show obvious nonlinearity and threshold effect.

One approach does not fit all settings: Exploring the effects of natural and built environments on running pleasantness across places

Running is one of the most frequently practiced exercises worldwide. Perceived pleasantness of running contributes to exercise motivation and thereby can promote running behaviours. However, the associations between environmental factors and running experience have been largely overlooked. This study adopts a public participation GIS approach to collect the mapped point features (N = 941) and assess running pleasantness from 222 runners who resided in the Helsinki Metropolitan Area, Finland. The results of a global regression model indicated that nature exposure (including eye-level greenness, top-down greenness, and blue space availability) and housing price were positively related to running pleasantness. Intersection density, traffic noise, and population density were negatively associated with running pleasantness. The spatial heterogeneity of these associations across the study area was revealed by adopting a local regression (MGWR) approach. Positive environmental attributes (e.g. blue space availability) increase running pleasantness more effectively when such attributes are more abundant, while negative attributes (e.g. traffic noise) strongly affect running pleasantness in settings where such environmental features are relatively rare. Given that the spatially-varying and scale-varying relationships between running pleasantness and environmental variables were observed across the study area, our findings provide evidence-based knowledge for planners and related policymakers, which suggests that utilizing a single approach without targeting specific settings is unwise to promote running exercise. Activity-based locations tend to have various environmental characteristics, the exposure of which needs to be adjusted uniquely and separately. Therefore, location-targeted interventions would be more effective in promoting running exercise and other physical activities than blanket approaches.

The relationship of single-family detached house prices with neighborhood walkability and disaster risk.

People's preferences regarding their neighborhood environment can vary depending on their socioeconomic status and the cities where they live. This study aims to discern the relationship between neighborhood environment factors and single-family detached house sales by sale price and by central and noncentral cities. We analyzed sale prices in the Tokyo Metropolitan Area from 2015 to 2020. The neighborhood environment was assessed using flood/sediment risk and neighborhood walkability measured by net residential density, intersection density, and facility density (walking opportunity). Flood and sediment risk is a major concern that restricts the available land and is included as a negative aspect of the neighborhood environment, taking the topographic features into consideration. A comparison of the results showed that the preference for neighborhood walkability varies by socioeconomic status as well as by target cities. For most facility types, the number of walking opportunities within walking distance from houses was found to be positively related to the sale price of single-family detached houses in all quantiles. The relationship of house price with population and intersection density was found to vary depending on the price level, with a negative relationship with the sale price of relatively more expensive houses being exhibited. People who considered buying houses with relatively higher sale prices were found to devalue houses located in flood/sediment-hazardous areas more. However, it was also found that the negative relationship was slightly mitigated in the highest quantile of sale prices for houses in areas with a moderate flood risk (maximum flooding depth: 3-5 m). Plains near rivers with amenities offer high walkability but pose a flood risk, resulting in a trade-off between flood risk and neighborhood walkability. The findings suggest the use of indices representing diverse preferences in accordance with the target socioeconomic status when policymakers assess the neighborhood environment.

Social and built neighborhood environments and sleep health: The Hispanic Community Health Study/Study of Latinos Community and Surrounding Areas and Sueño Ancillary Studies.

To test associations between neighborhood social, built, and ambient environment characteristics and multidimensional sleep health in Hispanic/Latino adults. Data were from San Diego-based Hispanic/Latino adults mostly of Mexican heritage enrolled in the Hispanic Community Health Study/Study of Latinos (N = 342). Home addresses were geocoded to ascertain neighborhood characteristics of greenness, walkability (density of intersections, retail spaces, and residences), socioeconomic deprivation (e.g. lower income, lower education), social disorder (e.g. vacant buildings, crime), traffic density, and air pollution (PM 2.5) in the Study of Latinos Communities and Surrounding Areas Study. Sleep dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration were measured by self-report or actigraphy approximately 2 years later. Multivariable regression models accounting for study design (stratification and clustering) were used to examine associations of neighborhood variables with individual sleep dimensions and a multidimensional sleep health composite score. Neighborhood characteristics were not significantly associated with the multidimensional sleep health composite, and there were few significant associations with individual sleep dimensions. Greater levels of air pollution (B = 9.03, 95% CI: 1.16, 16.91) were associated with later sleep midpoint, while greater social disorder (B = -6.90, 95% CI: -13.12, -0.67) was associated with earlier sleep midpoint. Lower walkability was associated with more wake after sleep onset (B = -3.58, 95% CI: -7.07, -0.09). Living in neighborhoods with lower walkability and greater air pollution was associated with worse sleep health, but otherwise findings were largely null. Future research should test these hypotheses in settings with greater variability and investigate mechanisms of these associations.

How do density, employment and transit affect the prevalence of COVID-19 pandemic? A study of 3,141 counties across the United States

Previous research has explored the effect of the built environment on the spread of the coronavirus disease (COVID-19) pandemic. This study extends the existing literature by examining the relationship between pandemic prevalence and density, employment, and transit factors at the county level. Using multilinear spatial-lag regressions and time series clustering analyses on the Smart Location Database encompassing 3141 counties in the United States, our findings reveal the following: (1) Density, employment, and transit variables yield heterogeneous effects to infection rate, death rate, and mortality rate. (2) Pedestrian-oriented road density is positively correlated to the prevalence of COVID-19, every 0.011 miles/acre increase is associated with 1% increase in the infection rate. (3) A consistent negative correlation is observed between jobs per household and infection rate, while a decrease in unemployment rate leads to an increase in the death rate. (4) The results from time series analysis suggest that areas characterized by low auto-oriented intersection density but high pedestrian-oriented road density are more susceptible to the impacts of pandemics. This highlights the need to prioritize pandemic prevention efforts in the suburban and rural areas with low population density, as emphasized in existing literature emphasized.

Do built environment factors have different effects on ridesourcing usage before and after the COVID-19 pandemic?

Ridesourcing has undergone a magnificent development pre pandemic and has had a transformative impact on travel behavior and urban mobility. While an individual's travel behavior has been found to be inevitably influenced by the pandemic, how COVID-19 influences the utilization of ridesourcing has rarely been discussed in previous studies. Understanding how COVID-19 has reshaped people's ridesourcing usage may also be helpful for providing updated policy implications in the post-pandemic era. The objective of this research is to investigate the extent to which the impact of the built environment on the utilization of ridesourcing has changed post pandemic, as compared to pre-pandemic period. This study analyzes the spatiotemporal difference in ridesourcing usage before and after the pandemic, and the differential impacts of built environment factors on ridesourcing usage using real-world trip data in Chicago. Generalized additive mixed models (GAMMs) are applied to analyze the nonlinear built environment effects on ridesourcing usage. Results show average ridesourcing usage in the post-pandemic period failed to recover to pre-pandemic trip volumes by June 2022. There are significant differences in the effects of population density, intersection density, land use mix, population employment balance index, and bus accessibility on ridesourcing pick-up usage between the post-pandemic and pre-pandemic periods. For example, population density had an overall positive effect pre pandemic. However, a significant negative effect was observed in areas with extremely high population density post pandemic. The positive effect of land use mix before the pandemic also turns into a negative effect after the pandemic. It seems that COVID-19 is having long-term effects on ridesourcing usage, at least in Chicago. Relevant policies and tailored land-use interventions should be updated regarding the differentiated built environment effects in the post-pandemic era.

Moving vision zero programs forward: What pedestrian-focused countermeasure combinations work best and where? A dynamic copula-based time-series approach

Vision Zero stands out as one of the most promising systemic safety action plans. A crucial step to ensure the successful implementation of Vision Zero is to continuously assess the efficiency of the implemented treatments. Traditionally, this is achieved using before-and-after analyses or cross-sectional studies. However, the applicability of these approaches can be limited in assessing Vision Zero initiatives, which usually involve installing multiple treatments at a location, leading to a significant interdependency between treatments. This study proposes a dynamic R-vine copula-based time series model to evaluate the efficiency of treatments implemented as a part of Vision Zero. The proposed approach enables the accurate assessment of the treatments, understanding of their long-term impacts, and identifying the most effective combination of treatments at a location. The study also investigated the association between location characteristics and the performance of treatments. The proposed framework was applied to the City of Toronto at the macro-level (neighbourhood level) and focused on pedestrian-related treatments. Collision data and the implemented countermeasures were obtained from Toronto’s Vision Zero Mapping Tool. The results show that the combination of speed limit reduction, leading pedestrian intervals (LPI), and community safety zones was the most frequent combination in terms of efficiency. Enforcement and speed limit reduction were the most effective combination in neighbourhoods with high school density, while LPI was effective in neighbourhoods with high densities of subway stations, and office density, especially when integrated with speed limit reduction and community zones. Driver feedback signs were effective in neighbourhoods with a high density of intersections, but only when combined with automated enforcement, community safety zones, and speed limit reduction. The results of the study would assist decision-makers in selecting the most effective treatment in a neighbourhood based on the neighbourhood characteristics and the countermeasures that are already installed.

Association between built environment on transport and recreational walking in Japan: the case of Kitakyushu

Walking is a popular form of transportation with a wide range of health, economic, environmental and social benefits. Previous studies have shown that walking is easily influenced by the surrounding built environment. In order to explore the relationship between objective built environment and perceived built environment factors in Japan and transport walking and recreational walking, this study selected Kitakyushu as a sample through questionnaire survey and geographic information data, and evaluated walking activity level through IPAQ and perceive the built environment through ANEWS, and then measured the objective measurement characteristics of the built environment through GIS. Multivariate linear regression model and multivariate logistic model were also used to evaluate the relationship between different built environment factors and pedestrian walking behavior in Japan. The results show that: (1) Age and residential period promoted transport walking. (2) Land mix use, dense bus stops, accessible commercial facilities, and a safe environment can all promote transport walking. (3) High building density and intersection density, more transit stops, more accessible commercial facilities and public service facilities can also promote recreational walking. (4) Having excellent walking facilities increased the time spent on leisure walks.

Pathways from street network design to symptoms of depression among emerging adults in China

Streets comprise over 80% of all urban public space, while previous studies associated street network attributes with traffic and transport model choice, they did not examine network design in conjunction with symptoms of depression. This paper developed a path analysis model to examine the direct and indirect effects of street network designs on symptoms of depression among undergraduates. Road network density, road intersection density and public transit density were measured within 1 km buffers centered on university campuses. A survey that included the 9-item patient health questionnaire (PHQ9) addressed these effects and measured the incidence of symptoms of depression among a random sample of 22,060 Chinese undergraduates. After controlling for individual- and campus-level covariates, the results revealed that exposure to PM2.5, poor sleep quality and unhealthy dietary pattern (excluding transport-related physical activity) mediated the relationship between specific street network attributes and symptoms of depression. Higher road density was found to alleviate symptoms of depression by increasing exposure to PM2.5. Greater road connectivity tended to alleviate symptoms of depression by reducing exposure to PM2.5 but to exacerbate symptoms of depression by worsening sleep quality and increasing the incidence of unhealthy dietary patterns. Better access to public transit inclined to ameliorate symptoms of depression by improving sleep quality but to exacerbate symptoms by increasing PM2.5 exposure. These findings emphasize the need for strategies aimed at improving street network designs to include assessments of the aggregate effects on campus environs and the associated impacts on undergraduate mental health.

The contributions of neighbourhood design in promoting metabolic health

The design and quality of the neighbourhood built environment can encourage health-supportive behaviours and support cardiometabolic health. However, despite the relationships between demographic and behavioural risk factors of metabolic syndrome being investigated by many studies, only some studies have directly estimated the associations between the built environment and metabolic syndrome. Using data from Canada, we examined the associations between the neighbourhood built environment and metabolic syndrome. Data from Alberta’s Tomorrow Project participants, conducted in Alberta, Canada, was used (n = 6718). Metabolic syndrome was defined as the presence of at least three clinical risk factors among lipid levels, blood pressure, and waist circumference. The normalised difference vegetation index was used to quantify the greenness of each participant’s neighbourhood. Built attributes of participants’ neighbourhoods associated with supporting physical activity, including dwelling density, intersection density, and the number of points of interest, were obtained via the Canadian Urban Environmental Health Research Consortium. Increases in the number of points of interest and total active living environment-friendliness of the neighbourhood were associated with having fewer metabolic syndrome risk factors (b = −0.11, 95% CI −0.16, −0.07 and b = −0.03, 95% CI −0.05, −0.01, respectively) and lower odds of metabolic syndrome (OR = 0.89, 95% CI 0.84, 0.094 and OR = 0.97, 95% CI 0.95, 0.99, respectively). Furthermore, higher dwelling density was associated with having fewer metabolic syndrome risk factors (b = −0.05, 95% CI −0.09, −0.01). Our findings highlight the importance of urban design to prevent and potentially manage metabolic syndrome and improve population health.

Impact of corridor highway system on communities: Built environment and travel mode choices

Conventional corridor management has focused on travel speed and efficiency while ignoring interactions between highway corridors and surrounding areas. This study investigates the interaction between the corridor highway system and the built environment around highways by estimating sustainable mode choices with respect to the land use characteristics of surrounding corridor highways throughout 29 regions in the U.S. The results indicate that the D variables at the corridor level matter. D variables at the corridor level, such as activity density, job-population balance, percentage of accessible jobs within 10 min by car, intersection density, percentage of 4-way intersections, and transit stop density, were highly associated with internal capture, walking trips, and transit use. The neighborhoods with higher activity density, job-population balance, intersection density, and better employment accessibility by transit experienced reduced VMT. The likelihood of internal trips, walking trips, and transit use decreased with household size and income; the opposite signs were found with VMT. The regional gasoline price had significant effects on all trips. In conclusion, this study provides planning and transportation researchers and practitioners with new evidence on the importance of built environmental characteristics (D variables) to encourage sustainable mode choices in the proximate neighborhoods of corridor highways.

The effects of the urban built environment on public transport ridership: similarities and differences

Understanding the relationship between public transport ridership and the built environment is crucial for the development of sustainable transportation systems. However, few studies have uncovered how the impact of built environment factors differs depending on the mode of public transportation, and there is insufficient evidence regarding the role of built environment factors in different types of ridership and their threshold effects. This paper presents a modeling framework that utilizes multi-source travel data to explore public transport ridership across multiple modes, including bus, transit (bus and metro), taxi, and shared bike ridership. A study conducted in Shenzhen, China found that common factors influence ridership across multiple transportation modes, and their effects vary by public transport mode. The joint contribution of variables related to the transportation network or points of interest to public transport ridership is substantial, but the effect of transportation network variables on different types of ridership varies significantly. Factors such as population density, distance to metro station, intersection density, shopping, and entertainment have similar associations with different types of ridership. The analysis of the active ranges and thresholds of built environment factors provides specific references for enhancing public transportation services or adjusting land use. The findings carry implications for policymakers to promote public transport use.

Street and activity centre characteristics associated with the use of different transport modes

Streets play a vital role in cities, yet there is little understanding of how their characteristics influence the use of different transport modes, particularly in activity centres. Using measurements of people concentration (people/km) from 57 activity centre locations across Melbourne, Australia, this research significantly contributes to understanding how street and activity centre characteristics are associated with the use of each of the following: walking, cycling, buses, trams, cars, car parking, trucks and motorbikes. Fractional logit regression models including the estimation of marginal effects were developed. Street-related characteristics that were significant included: presence of bicycle lanes, exclusive general traffic lanes, clearways, car parking charges, public transport services, in addition to footpath width, public transport service frequency, and movement and place classifications. Activity centre-related characteristics found to be significant included: size of the activity centre, network distance to various facilities and the CBD, intersection density, employment density and car ownership. The findings from this research can be used to support activity centre planning to achieve broader transport and land use objectives, particularly those related to local living such as 20-minute neighbourhoods.

“Green transit-oriented development”: Exploring the association between TOD and visible green space provision using street view data

Environmental inequalities generated by transit—oriented development (TOD) are of planning and policy relevance in developing countries. Existing literature has pointed out that TOD has the effect of ‘place making’, which means the newly developed transit systems may be able to change the environment and amenities of a certain area. While previous studies have largely focused on environment hazards such as noise and pollution induced by transit systems, scant attention has been paid to visible green space provision at station areas. This study develops a new and systematic framework to assess potential disparities in quality and quantity aspects of visible green space provision around subway stations. We explore the effects of TOD on visible green space provision around subway stations using spatial regression models. The results show that there are disparities in visible green space provision around subway stations, but such disparities tend to fade with distance away from stations. We also find that population density, land use mix, intersection density and bus stop density are significantly associated with quantity and quality aspects of visible green space provision around subway stations.

Neighborhood walkability, neighborhood social health, and self-selection among U.S. adults

Neighborhood walkability is favorably related to multiple physical health outcomes, but associations with social health are less clear. Present analyses examined how neighborhood walkability was related to neighborhood social health and explored the potential confounding role of neighborhood self-selection. Cross-sectional data were analyzed for 1745 adults, ages 20-66, recruited from two US regions. We created a walkability index around each participant's home (1km street network buffer) based on residential density, street intersection density, mixed land use, and retail floor area ratio. Neighborhood social health outcomes included reported social interactions with neighbors and sense of community. Two mixed model regressions were conducted for each outcome, with and without adjusting for walkability-related reasons for moving to the neighborhood (self-selection). Covariates included sex, age, socioeconomic status, white/nonwhite race/ethnicity, marital status, and time living in the neighborhood. Neighborhood walkability was positively related to social interactions with neighbors, both without (b=0.13, p<.001) and with adjustment for self-selection (b=0.09, p=.008). Neighborhood walkability was positively associated with sense of community, but only before adjusting for self-selection (b=0.02, p=.009). Neighborhood walkability may promote specific aspects of neighborhood social health, which together are beneficial for physical and mental health. These findings provide additional impetus for enhancing walkability of US communities.

Coupling shared E-scooters and public transit: a spatial and temporal analysis

ABSTRACT The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.