Digital twins for intelligent transportation systems are currently attracting great interests, in
which generating realistic, diverse, and human-like traffic flow in simulations is a formidable …

Traffic simulation provides interactive data for the optimization of traffic policies. However,
existing traffic simulators are limited by their lack of scalability and shortage in input data …

Urban movement data as collected by location-based social networks provides valuable
information about routes and specific roads that people are likely to drive on. This allows us …

Traffic simulators are important tools in autonomous driving development. While continuous
progress has been made to provide developers more options for modeling various traffic …

The precise prediction of multi-scale traffic is a ubiquitous challenge in the urbanization
process for car owners, road administrators, and governments. In the case of complex road …

Traffic simulation provides interactive data for the optimization of traffic control policies.
However, existing traffic simulators are limited by their lack of scalability and shortage in …

In the traffic simulation system, the data quality and inference speed of traffic flow generation
have a direct impact on the correlation between analysis results and actual traffic conditions …

High-quality traffic flow generation is the core module in building simulators for autonomous
driving. However, the majority of available simulators are incapable of replicating traffic …

Simulators generate diverse and realistic traffic scenarios to boost the development of
autonomous driving systems. However, existing simulators often fall short in scenario …

High-quality traffic flow generation is the core module in building simulators for autonomous
driving. However, the majority of available simulators are incapable of replicating traffic …