Data

The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is therefore limited in addressing the complexities created by the interrelated impacts of the pandemic. Such research generally makes use of only one of either 1) actively collected data such as surveys, or 2) passively collected data. While a few studies make use of both actively and passively collected data, only one other study collects it longitudinally...

While transport modelers in developed countries are accustomed to working with relatively rich datasets including transport networks and land use data, such databases are rarely available in developing countries. However, developing countries such as China with its immense rate of economic growth are, arguably, most in need of demand models. The research addressed in this paper is how to develop mode choice models for planning and policy analysis when level of service data are not available and resources are limited. The research makes use of a 1,001 household travel and activity survey...

PeMS 6 is the latest of six task orders devoted to research, development, and maintenance of the PeMS system. PeMS collects, processes, stores, and makes available online data from eight Caltrans districts (D3, 4, 5, 6, 7, 8, 11, 12). The data are obtained from 22,067 loops1, grouped into 8,649 vehicle detector stations (VDS). These loops cover 3,154 out of 30,572 directional-miles of interstate and state highways in California. PeMS began as a research project. As the research system evolved, Caltrans determined that the information it provided was very valuable, and additional resources...

Traffic signals play an important role in transportation by enabling traffic flow management, and ensuring safety at intersections. In addition, knowing the traffic signal phase and timing data can allow optimal vehicle routing for time and energy efficiency, eco-driving, and the accurate simulation of signalized road networks. In this paper, we present a machine learning (ML) method for estimating traffic signal timing information from vehicle probe data. To the authors best knowledge, very few works have presented ML techniques for determining traffic signal timing parameters from...