title: Encapsulating urban traffic rhythms into road networks.
abstract: Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.
authors.affiliation: 1] School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410000, P.R. China [2].
authors.forename: Junjie
authors.initials: J
authors.lastname: Wang
authors.affiliation: 1] School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410000, P.R. China [2].
authors.forename: Dong
authors.initials: D
authors.lastname: Wei
authors.affiliation: School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410000, P.R. China.
authors.forename: Kun
authors.initials: K
authors.lastname: He
authors.affiliation: School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410000, P.R. China.
authors.forename: Hang
authors.initials: H
authors.lastname: Gong
authors.affiliation: School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, 410000, P.R. China.
authors.forename: Pu
authors.initials: P
authors.lastname: Wang