The estimation of the network traffic state, its likely short-term evolution and the prediction of the expected travel times in a network are key steps of traffic management and information systems, especially in urban areas and in real-time applications. To perform such functions, most systems have at their core engine specific dynamic traffic models whose main input is a dynamic OD-matrix describing the time dependency of travel patterns in urban scenarios. This chapter provides an overview of the main concepts supporting these dynamic traffic models and their practical implementations in some software platforms, as well as an outline on the main approaches for the estimation of dynamic OD-matrices. Additionally, this chapter provides a basic discussion on one of the main emerging trends: strategies aimed at using the unprecedented amount of new traffic data made available by “new” mobile technologies.
Data Analytics and Models for Understanding and Predicting Travel Patterns in Urban Scenarios
Springer Tracts on Transportation, Traffic
2022-01-21
77 pages
Article/Chapter (Book)
Electronic Resource
English
Predicting TCM Responses with Urban Travel-Demand Models
British Library Conference Proceedings | 1994
|Changing patterns of urban travel
SLUB | 1985
|Travel patterns of urban residents
Engineering Index Backfile | 1967
|Changing patterns of urban travel
Taylor & Francis Verlag | 1986
|Understanding Taxi Travel Demand Patterns Through Floating Car Data
Springer Verlag | 2018
|