New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data
G Harrison, SM Grant-Muller, FC Hodgson - Transportation Research Part …, 2020 - Elsevier
High quality, reliable data and robust models are central to the development and appraisal
of transportation planning and policy. Although conventional data may offer good 'content', it …
of transportation planning and policy. Although conventional data may offer good 'content', it …
A comprehensive review of trip generation models based on land use characteristics
J Mukherjee, BR Kadali - Transportation Research Part D: Transport and …, 2022 - Elsevier
To assess the impact of any proposed development, it is necessary to estimate the trips that
are likely to be generated because of such development. In case of developing countries …
are likely to be generated because of such development. In case of developing countries …
Multi-scale urban passenger transportation CO2 emission calculation platform for smart mobility management
Passenger transportation is one of the primary sources of urban carbon emissions. Travel
data acquisition and appropriate emission inventory availability make estimating high …
data acquisition and appropriate emission inventory availability make estimating high …
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 …
High-resolution human mobility data reveal race and wealth disparities in disaster evacuation patterns
Major disasters such as extreme weather events can magnify and exacerbate pre-existing
social disparities, with disadvantaged populations bearing disproportionate costs. Despite …
social disparities, with disadvantaged populations bearing disproportionate costs. Despite …
A stepwise interpretable machine learning framework using linear regression (LR) and long short-term memory (LSTM): City-wide demand-side prediction of yellow …
As app-based ride-hailing services have been widely adopted within existing traditional taxi
markets, researchers have been devoted to understand the important factors that influence …
markets, researchers have been devoted to understand the important factors that influence …
[HTML][HTML] Passively generated big data for micro-mobility: State-of-the-art and future research directions
The sharp rise in popularity of micro-mobility poses significant challenges in terms of
ensuring its safety, addressing its social impacts, mitigating its environmental effects, and …
ensuring its safety, addressing its social impacts, mitigating its environmental effects, and …
Interpretable machine learning learns complex interactions of urban features to understand socio‐economic inequality
C Fan, J Xu, BY Natarajan… - Computer‐Aided Civil …, 2023 - Wiley Online Library
Inequality in cities is a phenomenon arising from the complex interactions among urban
systems and population activities. Conventional statistics and mathematical models like …
systems and population activities. Conventional statistics and mathematical models like …
[HTML][HTML] Assessing the socio-demographic representativeness of mobile phone application data
Emerging forms of mobile phone data generated from the use of mobile phone applications
have the potential to advance scientific research across a range of disciplines. However …
have the potential to advance scientific research across a range of disciplines. However …
Residency and worker status identification based on mobile device location data
Mobile device location data (MDLD) have been widely recognized for their rich human
mobility information and thus considered as a supplementary data source for the current …
mobility information and thus considered as a supplementary data source for the current …