The goal of biclar
is to store code and (in the releases) data for
estimating cycling potential and influencing policy.
biclar is a tool for the design and assessment of different scenarios of the cycling network models in the Lisbon metropolitan area (LMA).
The key datasets are as follows:
The baseline scenario makes use of the 2018 mobility survey data in
LMA.
We considered all trips between Freguesias.
See vignette baseline scenario to see how this was modeled.
The National targets for cycling uptake were set to:
Cycling trips should replace car trips directly.
See vignette ENMAC scenario to see how this was modeled.
See vignette Intermodal scenario to see how this was modeled.
See vignette E-bike scenario to see how this was modeled.
biclar
uses the methods developed in PCT.bike
(Lovelace et al. 2017) for cycling uptake estimation and data
visualization.
For the disagregation of OD pairs at Freguesias level, we use OD Jittering (Lovelace, Félix, and Carlino 2022) method, which better suits walking and cycling trips modelling (shorter distances), instead of relying on centroids that concentrate all the trips between areas.
The OD datasets, before and after jittering, are shown below.
Use of CyclingStreets.net (R package) for fast and quiet bike routes for baseline scenario.
For e-bike scenario, we developed a proper algorithm, considering the
topography, and using slopes
package.
We made use and developed a methodology that considers replacing long trips by bike + train or ferry trips.
Health Economic Assessment Tool (HEAT v5.0) for walking and cycling by WHO.
See here for full map.
See here for results for each Municipality.
Compare the modeled cycling networks (segments overlapping) with expansion plans, by municipality.
We can view it in an interactive map here.
This project is funded by TML - Transportes Metropolitanos de Lisboa.