The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major
source of atmospheric pollution in the parts of cities where people live, commute and work …

Accurate traffic speed prediction is critical to modern internet of things-based intelligent
transportation systems. It serves as the foundation of advanced traffic management systems …

The role of spillover effect of transportation endowment on regional economic development
is analyzed in this paper. We adopt the reduced form from the Solow growth model to …

Congestion pricing of a large-scale network is characterized by expensive-to-evaluate
objective functions without closed forms. This paper further enhances a computationally …

The determination of the pricing for tolled facilities always involves consideration of multiple
objectives, eg, efficiency, safety, pollution, reliability, and economy. Simulations are widely …

As road congestion is exacerbated in most metropolitan areas, many transportation policies
and planning strategies try to nudge travelers to switch to other more sustainable modes of …

This paper focuses on modeling agents' en-route diversion behavior under information
provision. The behavior model is estimated based on naïve Bayes rules and re-calibrated …

The availability, accuracy and relevance of real world input data are essential for developing
a reliable traffic simulation model. Large-scale traffic simulation models, in particular, require …

Travel time variability in a network is an important measure of the transportation system
performance and a major factor influencing the decision-making of system management …