Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Quantifying the impact of urban road networks on the efficiency of local trips
https://orcid.org/0000-0003-1822-083X
Abstract City-level circuity factors have been introduced to quantify and compare the directness of vehicular travel across different cities. While these city-level factors help to improve the quality of distance approximation functions for city-wide vehicle movements, more granular factors are needed to obtain accurate shortest path distance approximations for last-mile transportation systems that are typically characterized by local trips. More importantly, local circuity factors encode valuable information about the efficiency and complexity of the urban road network, which can be leveraged to inform policy and practice. In this paper, we quantify and analyze local network circuity leveraging contemporary traffic datasets. Using the city of São Paulo as our primary case study and a combination of supervised and un-supervised machine learning methods, we observe significant heterogeneities in local network circuity, explained by dimensional and topological properties of the road network. Locally, real trip distances are about twice as long as distances predicted by the norm. Results from São Paulo are compared to seven additional urban areas in Latin America and the United States. At a coarse-grained level of analysis, we observe similar correlations between road network properties and local circuity across these cities.
Quantifying the impact of urban road networks on the efficiency of local trips
https://orcid.org/0000-0003-1822-083X
Abstract City-level circuity factors have been introduced to quantify and compare the directness of vehicular travel across different cities. While these city-level factors help to improve the quality of distance approximation functions for city-wide vehicle movements, more granular factors are needed to obtain accurate shortest path distance approximations for last-mile transportation systems that are typically characterized by local trips. More importantly, local circuity factors encode valuable information about the efficiency and complexity of the urban road network, which can be leveraged to inform policy and practice. In this paper, we quantify and analyze local network circuity leveraging contemporary traffic datasets. Using the city of São Paulo as our primary case study and a combination of supervised and un-supervised machine learning methods, we observe significant heterogeneities in local network circuity, explained by dimensional and topological properties of the road network. Locally, real trip distances are about twice as long as distances predicted by the norm. Results from São Paulo are compared to seven additional urban areas in Latin America and the United States. At a coarse-grained level of analysis, we observe similar correlations between road network properties and local circuity across these cities.
Quantifying the impact of urban road networks on the efficiency of local trips
https://orcid.org/0000-0003-1822-083X
Abstract City-level circuity factors have been introduced to quantify and compare the directness of vehicular travel across different cities. While these city-level factors help to improve the quality of distance approximation functions for city-wide vehicle movements, more granular factors are needed to obtain accurate shortest path distance approximations for last-mile transportation systems that are typically characterized by local trips. More importantly, local circuity factors encode valuable information about the efficiency and complexity of the urban road network, which can be leveraged to inform policy and practice. In this paper, we quantify and analyze local network circuity leveraging contemporary traffic datasets. Using the city of São Paulo as our primary case study and a combination of supervised and un-supervised machine learning methods, we observe significant heterogeneities in local network circuity, explained by dimensional and topological properties of the road network. Locally, real trip distances are about twice as long as distances predicted by the norm. Results from São Paulo are compared to seven additional urban areas in Latin America and the United States. At a coarse-grained level of analysis, we observe similar correlations between road network properties and local circuity across these cities.
Quantifying the impact of urban road networks on the efficiency of local trips
Merchán, Daniel (Autor:in) / Winkenbach, Matthias (Autor:in) / Snoeck, André (Autor:in)
Transportation Research Part A: Policy and Practice ; 135 ; 38-62
19.02.2020
25 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Movies, the mother road and road trips
British Library Online Contents | 2010
| DOAJ | 2019
Urban passenger model - trips by gender and distance
| TIBKAT | 2000