(Created page with " == Abstract == We propose a new method to estimate benefits of road network improvements, which allows to include the induced demand without arbitrary assumptions. Instead o...") |
m (Scipediacontent moved page Draft Content 826774490 to Szarata et al 2020a) |
(No difference)
| |
Latest revision as of 13:53, 12 February 2021
Abstract
We propose a new method to estimate benefits of road network improvements, which allows to include the induced demand without arbitrary assumptions. Instead of estimating induced demand (which is nontrivial and hardly possible in practice), we search for demand induction where initial benefits are mitigated to zero. Such approach allows to formulate a dual measure of benefit, covering both the potential benefits and the likelihood of consuming them by the induced traffic. We first estimate benefits of road network improvement assuming that traffic demand is fixed. Consequently, we find demand model configurations at which the benefits of the new investment become null, i.e., all the initial benefits are consumed by the traffic demand growth. We call such states of induced demand the Lewis–Mogridge points of the analysed improvement. We select the most probable of such points and use it to calculate the proposed novel indicator <jats:italic>μ</jats:italic>, for which the initial benefits (obtained under a fixed-demand assumption) are multiplied with a demand increase rate needed to consume them. We believe that such measure allows to include the critical phenomena of induced traffic and, at the same time, to overcome problems associated with reliable estimation of induced demand. As we illustrate with the case of two alternative road improvement schemes in Kraków, Poland, the proposed method allows to estimate maximal threshold of induced traffic and to select scenario more resilient to induced traffic.
Document type: Article
Full document
Original document
The different versions of the original document can be found in:
- http://downloads.hindawi.com/journals/jat/2020/3096260.pdf under the license https://creativecommons.org/licenses/by
- http://dx.doi.org/10.1155/2020/3096260 under the license cc-by
Document information
Published on 01/01/2020
Volume 2020, 2020
DOI: 10.1155/2020/3096260
Licence: Other
Share this document
Keywords
claim authorship
Are you one of the authors of this document?