English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper addresses an open problem in traffic modeling: the second-ordermacroscopic node problem. A second-order macroscopic traffic model, in contrastto a first-order model, allows for variation of driving behavior acrosssubpopulations of vehicles in the flow. The second-order models are thus moredescriptive (e.g., they have been used to model variable mixtures ofbehaviorally-different traffic, like car/truck traffic, autonomous/human-driventraffic, etc.), but are much more complex. The second-order node problem is aparticularly complex problem, as it requires the resolution of discontinuitiesin traffic density and mixture characteristics, and solving of throughflows forarbitrary numbers of input and output roads to a node (in other words, this isan arbitrary-dimensional Riemann problem with two conserved quantities). Inthis paper, we extend the well-known "Generic Class of Node Model" constraintsto the second order and present a simple solution algorithm to the second-ordernode problem. Our solution makes use of a recently-introduced dynamic systemcharacterization of the first-order node model problem, which gives insight andintuition as to the continuous-time dynamics implicit in node models. Wefurther argue that the common "supply and demand" construction of node modelsthat decouples them from link models is not suitable to the second-order nodeproblem. Our second-order node model and solution method have immediateapplications in allowing modeling of behaviorally-complex traffic flows ofcontemporary interest (like partially-autonomous-vehicle flows) in arbitraryroad networks.

Generic second-order macroscopic traffic node model for general multi-input multi-output road junctions via a dynamic system approach