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A Scalable Machine Learning Framework for Assessing Urban Infrastructure Readiness for Automated Vehicles

https://doi.org/10.2139/ssrn.5353584
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Enabling Transportation Networks with Automated Vehicles: From Individual Vehicle Motion Control to Networked Fleet Management
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Infrastructure for Automated and Connected Driving: State of the Art and Future Research Directions
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Who Belongs in the Family?
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Urban infrastructure design principles for connected and autonomous vehicles: a case study of Oxford, UK
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Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
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Control of connected and automated vehicles: State of the art and future challenges
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OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks
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Cluster-wise assessment of cluster stability
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A k-mean clustering algorithm for mixed numeric and categorical data
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A new initialization method for categorical data clustering
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The effects of infrastructure quality on the usefulness of automated vehicles: A case study for Leeds, UK
inferredcites →https://doi.org/10.1016/j.patrec.2015.04.009openalex-snapshot
What are the true clusters?
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A Clustering Method Based on K-Means Algorithm
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Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia
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Are current roads ready for highly automated driving? A conceptual model for road readiness for AVs applied to the UK city of Leeds
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Locating charging stations for electric vehicles
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City readiness for connected and autonomous vehicles: A multi-stakeholder and multi-criteria analysis through analytic hierarchy process
inferredcites →https://doi.org/10.1016/j.trc.2019.01.026openalex-snapshot
Urban traffic signal control with connected and automated vehicles: A survey
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Implications of automated vehicles for physical road environment: A comprehensive review
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Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
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Open HD map service model: an interoperable high-Definition map data model for autonomous driving
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How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
inferredcites →https://doi.org/10.1109/access.2019.2903568openalex-snapshot
Survey of State-of-the-Art Mixed Data Clustering Algorithms
inferredcites →https://doi.org/10.1109/tits.2021.3085297openalex-snapshot
A Survey on Cyber-Security of Connected and Autonomous Vehicles (CAVs)
inferredcites →https://doi.org/10.1111/mice.12643openalex-snapshot
Octree‐based point cloud simulation to assess the readiness of highway infrastructure for autonomous vehicles
inferredcites →https://doi.org/10.1145/3385958.3430481openalex-snapshot
Autonomous Vehicles: Data Protection and Ethical Considerations
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Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet
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The Effects of Race, Gender, and Marital Status on Giving and Volunteering in Indiana
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Statistical and Econometric Methods for Transportation Data Analysis
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The world’s user-generated road map is more than 80% complete
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Preparing Infrastructure for Automated Vehicles
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Algorithm AS 136: A K-Means Clustering Algorithm
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Who Cares? Toward an Integrated Theory of Volunteer Work
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Cluster Analysis in Marketing Research: Review and Suggestions for Application
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Hybrid cooperative intersection management for connected automated vehicles and pedestrians
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Assessing State Department of Transportation Readiness for Connected Vehicle–Cooperative Systems Deployment: Oregon Case Study
inferredcites →https://doi.org/10.3390/app12073477openalex-snapshot
Road Infrastructure Challenges Faced by Automated Driving: A Review
inferredcites →https://doi.org/10.3390/designs5030040openalex-snapshot
Impact of Autonomous Vehicles on the Physical Infrastructure: Changes and Challenges
inferredcites →https://doi.org/10.3390/e24070917openalex-snapshot
How the Outliers Influence the Quality of Clustering?
inferredcites →https://doi.org/10.3390/s22197315openalex-snapshot
Physical and Digital Infrastructure Readiness Index for Connected and Automated Vehicles
inferredcites →https://doi.org/10.4324/9781003348832openalex-snapshot
Connected and Autonomous Vehicles
inferredcites →https://doi.org/10.5281/zenodo.3827479openalex-snapshot
Road infrastructure support levels for automated driving
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Data mining: concepts and techniques
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Autonomous Vehicle Technology: A Guide for Policymakers
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