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Kentaro Iio

Publications and source records attributed to Kentaro Iio.

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On the Distribution of Probe Traffic Volume Estimated without Trajectory Reconstruction

In recent years, passively recorded probe traffic volumes have increasingly been used to estimate traffic volumes. However, it is not always possible to count probe traffic volume in a spatial dataset when probe trajectories cannot be fully reconstructed from raw probe point location data due to sparse recording intervals, lack of pseudonyms or timestamps. As a result, the application of such probe point location data has been limited in traffic volume estimation. To relax these constraints, we present the exact distribution of the estimated probe traffic volume in a road segment based on probe point location data without trajectory reconstruction. The distribution of the estimated probe traffic volume can exhibit multimodality, without necessarily being line-symmetric with respect to the true probe traffic volume. As more probes are present, the distribution approaches a normal distribution. The conformity of the distribution was visualised through numerical simulations. Sometimes, there exists a local optimal cordon length that maximises estimation precision. The theoretical variance of estimated probe traffic volume can address heteroscedasticity in the modelling of traffic volume estimates.

cs.CY

COVID-19 and Social Distancing: Disparities in Mobility Adaptation between Income Groups

In response to the coronavirus disease 2019 (COVID-19) pandemic, governments have encouraged and ordered citizens to practice social distancing, particularly by working and studying at home. Intuitively, only a subset of people have the ability to practice remote work. However, there has been little research on the disparity of mobility adaptation across different income groups in US cities during the pandemic. The authors worked to fill this gap by quantifying the impacts of the pandemic on human mobility by income in Greater Houston, Texas. In this paper, we determined human mobility using pseudonymized, spatially disaggregated cell phone location data. A longitudinal study across estimated income groups was conducted by measuring the total travel distance, radius of gyration, number of visited locations, and per-trip distance in April 2020 compared to the data in a baseline. An apparent disparity in mobility was found across estimated income groups. In particular, there was a strong negative correlation ($ρ$ = -0.90) between a traveler's estimated income and travel distance in April. Disparities in mobility adaptability were further shown since those in higher income brackets experienced larger percentage drops in the radius of gyration and the number of distinct visited locations than did those in lower income brackets. The findings of this study suggest a need to understand the reasons behind the mobility inflexibility among low-income populations during the pandemic. The study illuminates an equity issue which may be of interest to policy makers and researchers alike in the wake of an epidemic.

cs.CY