<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Most of the major modern cities of the world face problems due to traffic conditions. However, in the last decade the degree of motorization combined with increased urbanization and population density causes excess traffic capacity during peak hours on the main streets of already congested cities. In these circumstances, public transport should provide a reliable and alternative choice for daily travel. The article is focused on the development of models to quantify the environment in which public transport operates and the quality of services. Also, the use of artificial neural network as a tool for assisted analysis of all traffic components can help local authorities to improve the performance of public transport service. In addition, improvements in the reliability of public transport service can reduce travel costs and change the modal split.</p>
</abstract>

Most of the major modern cities of the world face problems due to traffic conditions. However, in the last decade the degree of motorization combined with increased urbanization and population density causes excess traffic capacity during peak hours on the main streets of already congested cities. In these circumstances, public transport should provide a reliable and alternative choice for daily travel. The article is focused on the development of models to quantify the environment in which public transport operates and the quality of services. Also, the use of artificial neural network as a tool for assisted analysis of all traffic components can help local authorities to improve the performance of public transport service. In addition, improvements in the reliability of public transport service can reduce travel costs and change the modal split.

The Use of Multimodal Service Level and Artificial Neural Networks for the Improvement of Public Transport

Department of Roads, Railway and Construction Materials

Technical University of Civil Engineering of Bucharest

Romanian Journal of Transport Infrastructure

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Most of the major modern cities of the world face problems due to traffic conditions. However, in the last decade the degree of motorization combined with...

The Use of Multimodal Service Level and Artificial Neural Networks for the Improvement of Public Transport

Publié en ligne: 09 août 2024

Pages: 1 - 10

DOI: https://doi.org/10.2478/rjti-2024-0005

Mots clés
level of service, public transport analysis, artificial neural networks

© 2024 Mihai Maleanu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The Use of Multimodal Service Level and Artificial Neural Networks for the Improvement of Public Transport

Publié en ligne: 09 août 2024

Pages: 1 - 10

DOI: https://doi.org/10.2478/rjti-2024-0005

Mots cléslevel of service, public transport analysis, artificial neural networks

© 2024 Mihai Maleanu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
level of service, public transport analysis, artificial neural networks