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Traffic Estimation
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Emission estimation based on traffic models and measurements
Traffic congestion increases travel times, but also results in higher energy usage and vehicular emissions. To evaluate the impact of traffic emissions on environment and human health, the accurate estimation of their rates and location is required. Traffic emission models can be used for estimating emissions, providing emission factors in grams per vehicle and kilometre. Emission factors are defined for specific traffic situations, and traffic data is necessary in order to determine these traffic situations along a traffic network. The required traffic data, which consists of average speed and flow, can be obtained either from traffic models or sensor measurements. In large urban areas, the...
Traffic Information Estimation Methods Based on Cellular Network Data
Traffic Information Estimation Methods Based on Cellular Network Data is an in-depth discussion of the estimation methods used in traffic information systems. Covering essential topics such as research background, data limitations and sources, as well as a literature review, this comprehensive title also discusses methods for Intelligent Transportation Systems and proposes three traffic information estimation methods: HO (Handover)-based, Fingerprint Positioning Algorithm (FPA)-based, and Cell Probe (CP)-based methods.
Mobility Data-Driven Urban Traffic Monitoring
This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory t...
Traffic Simulation and Data
A single source of information for researchers and professionals, Traffic Simulation and Data: Validation Methods and Applications offers a complete overview of traffic data collection, state estimation, calibration and validation for traffic modelling and simulation. It derives from the Multitude Project—a European Cost Action project that incorporates work packages defining traffic simulation practice and research; highway and network modeling; and synthesis, dissemination, and training. This book addresses the calibration and validation of traffic models, and introduces necessary frameworks and techniques. It also includes viable methods for sensitivity analyses, and incorporates releva...
Traffic Measurement on the Internet
Traffic Measurement on the Internet presents several novel online measurement methods that are compact and fast. Traffic measurement provides critical real-world data for service providers and network administrations to perform capacity planning, accounting and billing, anomaly detection, and service provision. Statistical methods play important roles in many measurement functions including: system designing, model building, formula deriving, and error analyzing. One of the greatest challenges in designing an online measurement function is to minimize the per-packet processing time in order to keep up with the line speed of the modern routers. This book also introduces a challenging problem – the measurement of per-flow information in high-speed networks, as well as, the solution. The last chapter discusses origin-destination flow measurement.
Traffic Measurement for Big Network Data
This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems. The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flo...
