How drivers perform under different scenarios: Ability-related driving style extraction for large-scale dataset.

The extraction and analysis of driving style are essential for a comprehensive understanding of human driving behaviours. Most existing studies rely on subjective questionnaires and specific experiments, posing challenges in accurately capturing authentic characteristics of group drivers in naturalistic driving scenarios. As scenario-oriented naturalistic driving data collected by advanced sensors becomes increasingly available, the application of data-driven methods allows for a exhaustive analysis of driving styles across multiple drivers.

How containment policy and medical service impact COVID-19 transmission: A cross-national comparison among China, the USA, and Sweden.

As COVID-19 shows a heterogeneous spreading process globally, investigating factors associated with COVID-19 spreading among different countries will provide information for containment strategy and medical service decisions. A significant challenge for analyzing how these factors impact COVID-19 transmission is assessing key epidemiological parameters and how they change under different containment strategies across different nations. This paper builds a COVID-19 spread simulation model to estimate the core COVID-19 epidemiological parameters.

COVID-19, traffic demand, and activity restriction in China: A national assessment.

The global COVID pandemic of 2020, affected travel patterns across the world. The level of impact was influenced not only by the virus itself, but also by the nature, extent, and duration of governmental restriction on commerce and personal activity to limit its spread. This paper focuses on the interaction between COVID-19 transmission and traffic volume and further explores the impact of traffic control policies on the interaction.