Unknown

Dataset Information

0

Critical factors for mitigating car traffic in cities.


ABSTRACT: Car traffic in urban systems has been studied intensely in past decades but models are either limited to a specific aspect of traffic or applied to a specific region. Despite the importance and urgency of the problem we have a poor theoretical understanding of the parameters controlling urban car use and congestion. Here, we combine economical and transport ingredients into a statistical physics approach and propose a generic model that predicts for different cities the share of car drivers, the CO2 emitted by cars and the average commuting time. We confirm these analytical predictions on 25 major urban areas in the world, and our results suggest that urban density is not the most relevant variable controlling car-related quantities but rather are the city's area size and the density of public transport. Mitigating the traffic (and its effect such as CO2 emissions) can then be obtained by reducing the urbanized area size or, more realistically, by improving either the public transport density or its access. In particular, increasing the population density is a good idea only if it also increases the fraction of individuals having access to public transport.

SUBMITTER: Verbavatz V 

PROVIDER: S-EPMC6629143 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

altmetric image

Publications

Critical factors for mitigating car traffic in cities.

Verbavatz Vincent V   Barthelemy Marc M  

PloS one 20190715 7


Car traffic in urban systems has been studied intensely in past decades but models are either limited to a specific aspect of traffic or applied to a specific region. Despite the importance and urgency of the problem we have a poor theoretical understanding of the parameters controlling urban car use and congestion. Here, we combine economical and transport ingredients into a statistical physics approach and propose a generic model that predicts for different cities the share of car drivers, the  ...[more]

Similar Datasets

| S-EPMC5956282 | biostudies-literature
| S-EPMC3989229 | biostudies-literature
| S-EPMC8358017 | biostudies-literature
| S-EPMC6309774 | biostudies-literature
| S-EPMC7447804 | biostudies-literature
| S-EPMC4413274 | biostudies-other
| S-EPMC7821595 | biostudies-literature
| S-EPMC6320510 | biostudies-literature
| S-EPMC6704179 | biostudies-literature
| S-EPMC4311803 | biostudies-other