A tailored machine learning approach for urban transport network flow estimation
This study deals with urban transport network flow estimation based on Cellphone Location
(CL) and License Plate Recognition (LPR) data. We first propose two methods to filter CL …
(CL) and License Plate Recognition (LPR) data. We first propose two methods to filter CL …
Evaluation of opportunities and challenges of using INRIX data for real-time performance monitoring and historical trend assessment
In recent years there has been a growing desire for the use of probe vehicle technology for
congestion detection and general infrastructure performance assessment. Unlike costly …
congestion detection and general infrastructure performance assessment. Unlike costly …
Inferencing hourly traffic volume using data-driven machine learning and graph theory
Traffic volume is a critical piece of information in many applications, such as transportation
long-range planning and traffic operation analysis. Effectively capturing traffic volumes on a …
long-range planning and traffic operation analysis. Effectively capturing traffic volumes on a …
Inferring intercity freeway truck volume from the perspective of the potential destination city attractiveness
Accurately inferring the spatiotemporal distribution of freeway traffic volume is one of the
bottleneck problems for intelligent management of ground transportation. Although the …
bottleneck problems for intelligent management of ground transportation. Although the …
Data-driven approaches for modeling train control models: Comparison and case studies
In railway systems, the train dynamics are usually affected by the external environment (eg,
snow and wind) and wear-out of on-board equipment, leading to the performance …
snow and wind) and wear-out of on-board equipment, leading to the performance …
A deep convolutional neural network based approach for vehicle classification using large-scale GPS trajectory data
Transportation agencies are starting to leverage increasingly-available GPS trajectory data
to support their analyses and decision making. While this type of mobility data adds …
to support their analyses and decision making. While this type of mobility data adds …
Quantitative analysis of probe data characteristics: Coverage, speed bias and congestion detection precision
V Ahsani, M Amin-Naseri, S Knickerbocker… - Journal of Intelligent …, 2019 - Taylor & Francis
In recent years, there has been a growing desire for the use of probe vehicle technology for
congestion detection and general infrastructure performance assessment. Unlike costly …
congestion detection and general infrastructure performance assessment. Unlike costly …
Investigation of Vehicular Pollutant Emissions at 4-Arm Intersections for the Improvement of Integrated Actions in the Sustainable Urban Mobility Plans (SUMPs)
Sustainable urban mobility planning is a strategic and integrated approach that aims to
effectively address the complexities of urban transportation. Additionally, vehicle emissions …
effectively address the complexities of urban transportation. Additionally, vehicle emissions …
Estimating traffic flow states with smart phone sensor data
This study proposes a framework to classify traffic flow states. The framework is capable of
processing massive, high-density, and noise-contaminated data sets generated from …
processing massive, high-density, and noise-contaminated data sets generated from …
Big-data driven framework to estimate vehicle volume based on mobile device location data
Vehicle volume serves as a critical metric and the fundamental basis for traffic signal control,
transportation project prioritization, road maintenance planning, and more. Traditional …
transportation project prioritization, road maintenance planning, and more. Traditional …