Road network design in a developing country using mobile phone data: An application to Senegal
article
This study uses mobile phone data to understand
mobility patterns in a country, with limited mobility data, in
order to give advice about decisions on how to design the national
and regional road network. Our method consists of three parts:
(1) filtering mobile phone traces to derive mobility patterns, (2)
building an adapted formulation of the gravity-based trip
distribution model, which considers telecommunication intensity
(i.e., aggregate number of calls and text messages) and travel
time as input to forecast the influence of road improvements on
country-wide mobility, and (3) optimizing the road network
investment based on the adapted trip distribution model by using
a local search algorithm. The method was applied to the case
study country of Senegal. The mobile phone data was
transformed to support informed decisions on road network
development in that country given different objectives, namely
accessibility and equity. We believe that the methodology is
valuable and reproducible to other countries where traditional
mobility data is scarce but mobile phone data is available to
transport planners
mobility patterns in a country, with limited mobility data, in
order to give advice about decisions on how to design the national
and regional road network. Our method consists of three parts:
(1) filtering mobile phone traces to derive mobility patterns, (2)
building an adapted formulation of the gravity-based trip
distribution model, which considers telecommunication intensity
(i.e., aggregate number of calls and text messages) and travel
time as input to forecast the influence of road improvements on
country-wide mobility, and (3) optimizing the road network
investment based on the adapted trip distribution model by using
a local search algorithm. The method was applied to the case
study country of Senegal. The mobile phone data was
transformed to support informed decisions on road network
development in that country given different objectives, namely
accessibility and equity. We believe that the methodology is
valuable and reproducible to other countries where traditional
mobility data is scarce but mobile phone data is available to
transport planners
TNO Identifier
843336
Source
IEEE Intelligent Transportation Systems Magazine, pp. 1-11.
Pages
1-11
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