Anatomy and efficiency of urban multimodal mobility
| Autor: | Aleksandr Zolotov, Yeldos Mukhametov, Riccardo Gallotti, Mikolaj P. Karpinski, Aigul Shaikhanova |
|---|---|
| Přispěvatelé: | Institut de Physique Théorique - UMR CNRS 3681 (IPHT), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre d'Analyse et de Mathématique sociales (CAMS), École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
[PHYS]Physics [physics]
Physics - Physics and Society Service (systems architecture) Multidisciplinary Operations research business.industry Computer science Population size Mode (statistics) FOS: Physical sciences Anatomy Physics and Society (physics.soc-ph) Article Public transport 11. Sustainability Path (graph theory) Synchronization (computer science) Key (cryptography) business |
| Zdroj: | Scientific Reports Scientific Reports, 2015, 4, pp.6911. ⟨10.1038/srep06911⟩ Scientific Reports, Nature Publishing Group, 2015, 4, pp.6911. ⟨10.1038/srep06911⟩ |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/srep06911⟩ |
| Popis: | The growth of transportation networks and their increasing interconnections, although positive, has the downside effect of an increasing complexity which make them difficult to use, to assess, and limits their efficiency. On average in the UK, 23% of travel time is lost in connections for trips with more than one mode, and the lack of synchronization decreases very slowly with population size. This lack of synchronization between modes induces differences between the theoretical quickest trip and the `time-respecting' path, which takes into account waiting times at interconnection nodes. We analyse here the statistics of these paths on the multilayer, temporal network of the entire, multimodal british public transportation system. We propose a statistical decomposition -- the `anatomy' -- of trips in urban areas, in terms of riding, waiting and walking times, and which shows how the temporal structure of trips varies with distance and allows us to compare different cities. Weaknesses in systems can be either insufficient transportation speed or service frequency, but the key parameter controlling their global efficiency is the total number of stop events per hour for all modes. This analysis suggests the need for better optimization strategies, adapted to short, long unimodal or multimodal trips. Comment: 9 pages, 7 figures +supplementary information (9 pages and 9 figures) |
| Databáze: | OpenAIRE |
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