On the public citation graph
Estimating Pedestrian and Vehicle Volumes with Microscopic Built Environment Attributes with Bayesian Poisson Spatial Modeling Approach
0 signed · 106 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-snapshot
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/bf00116466openalex-snapshot
Bayesian image restoration, with two applications in spatial statistics
inferredcites →https://doi.org/10.1016/j.aap.2004.07.005openalex-snapshot
The association of rainfall and other weather variables with road traffic volume in Melbourne, Australia
inferredcites →https://doi.org/10.1016/j.aap.2008.03.009openalex-snapshot
Modelling area-wide count outcomes with spatial correlation and heterogeneity: An analysis of London crash data
inferredcites →https://doi.org/10.1016/j.aap.2008.10.001openalex-snapshot
An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning
inferredcites →https://doi.org/10.1016/j.aap.2009.11.002openalex-snapshot
Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis
inferredcites →https://doi.org/10.1016/j.aap.2011.02.005openalex-snapshot
The link between built environment, pedestrian activity and pedestrian–vehicle collision occurrence at signalized intersections
inferredcites →https://doi.org/10.1016/j.aap.2011.08.003openalex-snapshot
Macroscopic spatial analysis of pedestrian and bicycle crashes
inferredcites →https://doi.org/10.1016/j.aap.2012.06.016openalex-snapshot
Traffic analysis zone level crash estimation models based on land use characteristics
inferredcites →https://doi.org/10.1016/j.aap.2012.08.004openalex-snapshot
Application of finite mixture of negative binomial regression models with varying weight parameters for vehicle crash data analysis
inferredcites →https://doi.org/10.1016/j.aap.2015.03.003openalex-snapshot
Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level
inferredcites →https://doi.org/10.1016/j.aap.2016.04.018openalex-snapshot
Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models
inferredcites →https://doi.org/10.1016/j.aap.2016.07.028openalex-snapshot
Macro-level safety analysis of pedestrian crashes in Shanghai, China
inferredcites →https://doi.org/10.1016/j.aap.2016.11.002openalex-snapshot
The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach
inferredcites →https://doi.org/10.1016/j.aap.2017.03.009openalex-snapshot
Intersection crash prediction modeling with macro-level data from various geographic units
inferredcites →https://doi.org/10.1016/j.aap.2017.08.032openalex-snapshot
Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models
inferredcites →https://doi.org/10.1016/j.aap.2017.12.026openalex-snapshot
Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach
inferredcites →https://doi.org/10.1016/j.aap.2019.03.017openalex-snapshot
Exposure to pedestrian crash based on household survey data: Effect of trip purpose
inferredcites →https://doi.org/10.1016/j.aap.2019.07.020openalex-snapshot
Crash risk, crash exposure, and the built environment: A conceptual review
inferredcites →https://doi.org/10.1016/j.aap.2020.105652openalex-snapshot
Roles of infrastructure and land use in bicycle crash exposure and frequency: A case study using Greater London bike sharing data
inferredcites →https://doi.org/10.1016/j.aap.2020.105777openalex-snapshot
Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashes
inferredcites →https://doi.org/10.1016/j.aap.2020.105958openalex-snapshot
Propensities of red light running of pedestrians at the two-stage crossings with split pedestrian signal phases
inferredcites →https://doi.org/10.1016/j.aap.2021.106294openalex-snapshot
Vulnerable road users’ crash hotspot identification on multi-lane arterial roads using estimated exposure and considering context classification
inferredcites →https://doi.org/10.1016/j.aap.2022.106818openalex-snapshot
Effect of urban street trees on pedestrian safety: A micro-level pedestrian casualty model using multivariate Bayesian spatial approach
inferredcites →https://doi.org/10.1016/j.aap.2023.107400openalex-snapshot
Towards safer streets: A framework for unveiling pedestrians’ perceived road safety using street view imagery
inferredcites →https://doi.org/10.1016/j.aap.2024.107479openalex-snapshot
Exploring the influence of drivers’ visual surroundings on speeding behavior
inferredcites →https://doi.org/10.1016/j.aap.2024.107552openalex-snapshot
Modeling temporal correlation and heterogeneity in real-time conflict rates using Bayesian Tobit models for signalized intersections
inferredcites →https://doi.org/10.1016/j.aap.2024.107682openalex-snapshot
How does street environment affect pedestrian crash risks? A link-level analysis using street view image-based pedestrian exposure measurement
inferredcites →https://doi.org/10.1016/j.amar.2019.100090openalex-snapshot
A statistical assessment of temporal instability in the factors determining motorcyclist injury severities
inferredcites →https://doi.org/10.1016/j.amar.2022.100243openalex-snapshot
Addressing unobserved heterogeneity at road user level for the analysis of conflict risk at tunnel toll plaza: A correlated grouped random parameters logit approach with heterogeneity in means
inferredcites →https://doi.org/10.1016/j.atmosenv.2004.09.059openalex-snapshot
Inhalation of motor vehicle emissions: effects of urban population and land area
inferredcites →https://doi.org/10.1016/j.cities.2017.05.005openalex-snapshot
Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips
inferredcites →https://doi.org/10.1016/j.cities.2025.105890openalex-snapshot
Do protected cycle lanes make cities more bike-friendly? Integrating street view images with deep learning techniques
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2011.05.006openalex-snapshot
An empirical analysis of the influence of urban form on household travel and energy consumption
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2017.01.007openalex-snapshot
Using space syntax and agent-based approaches for modeling pedestrian volume at the urban scale
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2020.101481openalex-snapshot
Estimating pedestrian volume using Street View images: A large-scale validation test
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2023.102057openalex-snapshot
Advances in estimating pedestrian measures through artificial intelligence: From data sources, computer vision, video analytics to the prediction of crash frequency
inferredcites →https://doi.org/10.1016/j.jsr.2017.02.018openalex-snapshot
Comparative analysis of zonal systems for macro-level crash modeling
inferredcites →https://doi.org/10.1016/j.jsr.2022.09.004openalex-snapshot
Existence of the safety-in-numbers effect in the aspect of injury severity: A macroscopic analysis for bicyclists and pedestrians
inferredcites →https://doi.org/10.1016/j.jtrangeo.2007.12.003openalex-snapshot
Impact of cold and snow on temporal and spatial variations of highway traffic volumes
inferredcites →https://doi.org/10.1016/j.jtrangeo.2015.05.008openalex-snapshot
Understanding the effects of complex seasonality on suburban daily transit ridership
inferredcites →https://doi.org/10.1016/j.jtrangeo.2016.06.012openalex-snapshot
Macro and micro models for zonal crash prediction with application in hot zones identification
inferredcites →https://doi.org/10.1016/j.jtrangeo.2021.103067openalex-snapshot
Varying influences of the built environment on daily and hourly pedestrian crossing volumes at signalized intersections estimated from traffic signal controller event data
inferredcites →https://doi.org/10.1016/j.jtrangeo.2024.103954openalex-snapshot
Toward pedestrian-friendly cities: Nonlinear and interaction effects of building density on pedestrian volume
inferredcites →https://doi.org/10.1016/j.jtrangeo.2024.103989openalex-snapshot
Re-examining the role of street network configuration on bicycle commuting using crowdsourced data
inferredcites →https://doi.org/10.1016/j.jtrangeo.2024.104032openalex-snapshot
Bayesian multivariate spatiotemporal statistical modeling of bus and taxi ridership
inferredcites →https://doi.org/10.1016/j.jtrangeo.2025.104179openalex-snapshot
Deciphering urban cycling: Analyzing the nonlinear impact of street environments on cycling volume using crowdsourced tracker data and machine learning
inferredcites →https://doi.org/10.1016/j.landurbplan.2016.07.002openalex-snapshot
Measuring walkability for distinct pedestrian groups with a participatory assessment method: A case study in Lisbon
inferredcites →https://doi.org/10.1016/j.landurbplan.2023.104756openalex-snapshot
Assessing impacts of objective features and subjective perceptions of street environment on running amount: A case study of Boston
inferredcites →https://doi.org/10.1016/j.scs.2022.103755openalex-snapshot
Investigating pedestrian-level greenery in urban forms in a high-density city for urban planning
inferredcites →https://doi.org/10.1016/j.scs.2023.104454openalex-snapshot
Interactive impacts of walkability, social vulnerability, & travel behavior on COVID-19 mortality: A hierarchical Bayesian spatial random parameter approach
inferredcites →https://doi.org/10.1016/j.ssci.2011.09.012openalex-snapshot
The role of built environment on pedestrian crash frequency
inferredcites →https://doi.org/10.1016/j.ssci.2014.02.019openalex-snapshot
Analysis of residence characteristics of at-fault drivers in traffic crashes
inferredcites →https://doi.org/10.1016/j.ssci.2015.07.017openalex-snapshot
Safety-in-numbers: A systematic review and meta-analysis of evidence
inferredcites →https://doi.org/10.1016/j.tbs.2013.10.004openalex-snapshot
Pedestrian exposure measures: A time-space framework
inferredcites →https://doi.org/10.1016/j.tbs.2021.05.010openalex-snapshot
A big data approach to understanding pedestrian route choice preferences: Evidence from San Francisco
inferredcites →https://doi.org/10.1016/j.tbs.2022.05.002openalex-snapshot
Mixed-methods approach to studying multiuser perceptions of an interim Complete Streets project in Norway
inferredcites →https://doi.org/10.1016/j.tbs.2023.100573openalex-snapshot
Investigating pedestrian crossing route choice at mid-blocks without crossing facilities: The role of roadside environment
inferredcites →https://doi.org/10.1016/j.tbs.2023.100673openalex-snapshot
Exploring non-linear and synergistic effects of green spaces on active travel using crowdsourced data and interpretable machine learning
inferredcites →https://doi.org/10.1016/j.tra.2006.05.005openalex-snapshot
Goods transport in large European cities: Difficult to organize, difficult to modernize
inferredcites →https://doi.org/10.1016/j.tra.2018.04.005openalex-snapshot
A conceptual framework to formulate transportation network design problem considering social equity criteria
inferredcites →https://doi.org/10.1016/j.tra.2019.07.010openalex-snapshot
Applying a deep learning approach for transportation safety planning by using high-resolution transportation and land use data
inferredcites →https://doi.org/10.1016/j.tra.2021.11.017openalex-snapshot
Examining non-linear associations between built environments around workplace and adults’ walking behaviour in Shanghai, China
inferredcites →https://doi.org/10.1016/j.tra.2023.103946openalex-snapshot
Using mobile phone big data and street view images to explore the mismatch between walkability and walking behavior
inferredcites →https://doi.org/10.1016/j.tra.2024.103968openalex-snapshot
Redefining walkability to capture safety: Investing in pedestrian, bike, and street level design features to make it safe to walk and bike
inferredcites →https://doi.org/10.1016/j.tra.2025.104437openalex-snapshot
Exploring pedestrian route choice preferences by demographic groups: Analysis of street attributes in Chicago
inferredcites →https://doi.org/10.1016/j.tranpol.2010.01.012openalex-snapshot
Regional traffic impacts of logistics-related land use
inferredcites →https://doi.org/10.1016/j.tranpol.2023.04.020openalex-snapshot
Waiting for signalized crossing or walking to footbridge/underpass? Examining the effect of weather using stated choice experiment with panel mixed random regret minimization approach
inferredcites →https://doi.org/10.1016/j.trb.2005.01.003openalex-snapshot
Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model
inferredcites →https://doi.org/10.1016/j.trc.2019.11.023openalex-snapshot
On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment
inferredcites →https://doi.org/10.1016/j.trc.2020.102739openalex-snapshot
A tensor decomposition method for cycle-based traffic volume estimation using sampled vehicle trajectories
inferredcites →https://doi.org/10.1016/j.trd.2020.102651openalex-snapshot
Predicting bicycling and walking traffic using street view imagery and destination data
inferredcites →https://doi.org/10.1016/j.trd.2022.103590openalex-snapshot
The impact of perceived injury risk and psychosocial factors on walking equity
inferredcites →https://doi.org/10.1016/j.trf.2003.06.001openalex-snapshot
Pedestrian behaviors at and perceptions towards various pedestrian facilities: an examination based on observation and survey data
inferredcites →https://doi.org/10.1016/j.trf.2023.06.016openalex-snapshot
Detection of Driver Distraction in the Australian Naturalistic Driving Study Videos Using Pre-Trained Models and Transfer Learning
inferredcites →https://doi.org/10.1016/j.trpro.2016.05.386openalex-snapshot
Why are Trees Still Such a Major Hazard to Drivers in Poland?
inferredcites →https://doi.org/10.1016/s0001-4575(98)00055-4openalex-snapshot
An inter-regional comparison: fatal crashes in the southeastern and non-southeastern United States: preliminary findings
inferredcites →https://doi.org/10.1016/s0749-3797(02)00475-0openalex-snapshot
How the built environment affects physical activity
inferredcites →https://doi.org/10.1061/(asce)0733-9488(2006)132:2(76)openalex-snapshot
Sustainable Urban Transportation: Concepts, Policies, and Methodologies
inferredcites →https://doi.org/10.1068/a38106openalex-snapshot
District Variations in Road Curvature in England and Wales and their Association with Road-Traffic Crashes
inferredcites →https://doi.org/10.1080/01944361003766766openalex-snapshot
Travel and the Built Environment
inferredcites →https://doi.org/10.1080/13574800802451155openalex-snapshot
Measuring the Unmeasurable: Urban Design Qualities Related to Walkability
inferredcites →https://doi.org/10.1080/17421772.2015.1062285openalex-snapshot
“Theory and Practice of Spatial Econometrics”
inferredcites →https://doi.org/10.1080/23249935.2021.1922536openalex-snapshot
Revisiting spatial correlation in crash injury severity: a Bayesian generalized ordered probit model with Leroux conditional autoregressive prior
inferredcites →https://doi.org/10.1093/acprof:oso/9780198515326.003.0007openalex-snapshot
Bayesian approaches to disease mapping
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00721openalex-snapshot
YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors
inferredcites →https://doi.org/10.1109/icce-berlin53567.2021.9720012openalex-snapshot
A Rethinking of Real-Time Computer Vision-Based Lane Detection
inferredcites →https://doi.org/10.1109/ijcnn.2016.7727480openalex-snapshot
Vision-based vehicle detecting and counting for traffic flow analysis
inferredcites →https://doi.org/10.1109/te.2013.2239997openalex-snapshot
Traffic Sign Recognition for Computer Vision Project-Based Learning
inferredcites →https://doi.org/10.1109/tits.2017.2658664openalex-snapshot
Real-Time Traffic State Estimation With Connected Vehicles
inferredcites →https://doi.org/10.1109/tits.2018.2797697openalex-snapshot
Real-Time Traffic Flow Parameter Estimation From UAV Video Based on Ensemble Classifier and Optical Flow
inferredcites →https://doi.org/10.1109/tits.2020.2984197openalex-snapshot
A Smart, Efficient, and Reliable Parking Surveillance System With Edge Artificial Intelligence on IoT Devices
inferredcites →https://doi.org/10.1109/tits.2020.2993926openalex-snapshot
Deep Neural Network Based Vehicle and Pedestrian Detection for Autonomous Driving: A Survey
inferredcites →https://doi.org/10.1111/1467-9868.00353openalex-snapshot
Bayesian Measures of Model Complexity and Fit
inferredcites →https://doi.org/10.1136/bmj.324.7346.1129openalex-snapshot
Safety education of pedestrians for injury prevention: a systematic review of randomised controlled trials
inferredcites →https://doi.org/10.1177/00139165211014609openalex-snapshot
How are Neighborhood and Street-Level Walkability Factors Associated with Walking Behaviors? A Big Data Approach Using Street View Images
inferredcites →https://doi.org/10.1177/0361198118758652openalex-snapshot
Using Open Source Data to Measure Street Walkability and Bikeability in China: A Case of Four Cities
inferredcites →https://doi.org/10.1177/0361198120946016openalex-snapshot
Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data
inferredcites →https://doi.org/10.1177/0361198120953795openalex-snapshot
Investigation of Safety-in-Numbers for Pedestrians and Bicyclists at a Macroscopic Level with Various Exposure Variables
inferredcites →https://doi.org/10.1177/0885412209335553openalex-snapshot
The Built Environment and Traffic Safety
inferredcites →https://doi.org/10.2105/ajph.2011.300528openalex-snapshot
Neighborhood Social Inequalities in Road Traffic Injuries: The Influence of Traffic Volume and Road Design
inferredcites →https://doi.org/10.3141/2148-04openalex-snapshot
County-Level Crash Risk Analysis in Florida: Bayesian Spatial Modeling
inferredcites →https://doi.org/10.3141/2213-04openalex-snapshot
Integrating Trip and Roadway Characteristics to Manage Safety in Traffic Analysis Zones
inferredcites →https://doi.org/10.3141/2264-09openalex-snapshot
Modeling of Pedestrian Activity at Signalized Intersections: Land Use, Urban Form, Weather, and Spatiotemporal Patterns
inferredcites →https://doi.org/10.3141/2661-10openalex-snapshot
Estimating Pedestrian Exposure for Small Urban and Rural Areas
inferredcites →https://doi.org/10.3390/ijgi11100504openalex-snapshot
How Are Macro-Scale and Micro-Scale Built Environments Associated with Running Activity? The Application of Strava Data and Deep Learning in Inner London
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.