AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The proposed framework for estimating travel times at both the link and route levels using sparse GPS data is implemented using Python scripting within the ArcGIS environment and validated against high-frequency GPS records, demonstrating that the approach yields accurate and reliable results despite the data sparsity.
Smart cities increasingly rely on interconnected data infrastructures, yet emergency management systems—particularly for wildfire evacuation—remain disconnected from these capabilities. This paper proposes a four-layer GPS-based smart city mobility data framework that integrates crowd-sourced location data as a permane...
This study presents an analysis of GPS data obtained from the Danish truck tolling system, covering a one-week period with more than 800 million observations across over 60,000 trucks. The analysis extracts mobility patterns from high-resolution data by segmenting raw GPS sequences into trips. These trips are subsequen...
Conventional traffic volume surveys used to identify peak hours require extensive data collection periods, often taking up to 84 days. Although Narendra (2022) proposed leveraging the Google Maps "Popular Times" feature as a rapid alternative, empirical validation regarding its reliability on urban secondary collector...
Travel time reliability (TTR) is a key mobility performance measure for roadway systems. Intelligent Transportation Systems have enabled transportation agencies and researchers to use large-scale travel time data for evaluating TTR. The United States Congress has directed federal, state, and metropolitan transportation...
Urban flyover construction projects aim to improve mobility and reduce congestion but often trigger short-term disruptions in traffic and socio-economic activities. This study assesses the impacts of the ongoing flyover construction in Ile-Ife, Nigeria, using geospatial analysis and socio-economic surveys. Travel time...
Accurate information on intra-urban population distribution is essential for urban planning, infrastructure management, exposure assessment, and evidence-based decision-making. However, census data are usually available only for predefined administrative units and often lack the spatial detail required for fine-scale u...
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