Urban infrastructure design principles for connected and autonomous vehicles: a case study of Oxford, UK
Huazhen Liu , Miao Yang , ChengHe Guan , Yi Samuel Chen , Michael Keith , Meizi You , Monica Menendez
Computational Urban Science ›› 2023, Vol. 3 ›› Issue (1) : 34
Urban infrastructure design principles for connected and autonomous vehicles: a case study of Oxford, UK
Connected and Autonomous Vehicles (CAVs) are reshaping urban systems, demanding substantial computational support. While existing research emphasizes the significance of establishing physical and virtual infrastructure to facilitate CAV integration, a comprehensive framework for designing CAV-related infrastructure principles remains largely absent. This paper introduces a holistic framework that addresses gaps in current literature by presenting principles for the design of CAV-related infrastructure. We identify diverse urban infrastructure types crucial for CAVs, each characterized by intricate considerations. Deriving from existing literature, we introduce five principles to guide investments in physical infrastructure, complemented by four principles specific to virtual infrastructure. These principles are expected to evolve with CAV development and associated technology advancements. Furthermore, we exemplify the application of these principles through a case study in Oxford, UK. In doing so, we assess urban conditions, identify representative streets, and craft CAV-related urban infrastructure tailored to distinct street characteristics. This framework stands as a valuable reference for cities worldwide as they prepare for the increasing adoption of CAVs.
Shanghai Nature and Health Foundation,(Grant No. 20230701 SNHF CH_Guan)
NYU Shanghai,(Grant No. 2022CHGuan_MGSF)
NYUAD Center for Interacting Urban Networks,(NYUAD Research Institute Award CG001)
PEAK Urban Programme at University of Oxford,(Grant Ref: ES/P011055/1)
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