Integrated urban regeneration policy and soft mobility planning for transport energy-saving

Integrated urban regeneration policy and soft mobility planning for transport energy-saving

Gattuso DomenicoCassone Gian Carla Malara Margherita 

Dep DIIES Mediterranea, University of Reggio Calabria, Reggio Calabria, Italy

Dep PAU Mediterranea University of Reggio Calabria, Reggio Calabria, Italy

Corresponding Author Email: 
domenico.gattuso@unirc.it
Page: 
527-547
|
DOI: 
https://doi.org/10.3166/I2M.17.527-547
Received: 
| |
Accepted: 
| | Citation

OPEN ACCESS

Abstract: 

The new generation of plans (Urban development plans, Sustainable Urban Transport Plans) in Italy, as well as in Europe and in other international contexts, tends to combine different actions such as urban regeneration, enhancement of areas of particular value, containing of negative traffic impacts, also through innovative technologies and measures, in particular in the ITS field (Intelligent Transportation Systems), soft mobility (pedestrian and cycle mobility, zero emission vehicles, shared mobility, green and clean public transport, etc.). The paper proposes an integrated approach to urban regeneration policy and soft mobility planning, aimed at significant transport energy-saving and environmental sustainability. The attention is focused on Transport models able to provide quantitative impact indicators of these integrated policies in terms of less energy consumption for the urban community. A specific application is proposed, for demonstration purposes, with reference to an ordinary day and a specific area of the Reggio Calabria city center, subject of a specific environmental upgrading and associated reorganization of the transport supply in soft mobility terms.

Keywords: 

sustainability, urban regeneration, soft mobility, energy saving

1. Introduction
2. Urban regeneration policies and soft mobility planning
3. Models for estimation of energy consumption from urban traffic
4. An environmental requalification and soft mobility proposal
5. Scenario simulations and impact assessment on energy consumption
6. Conclusions
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