Characterizing soft modes’ traveling in urban areas though indicators and simulated scenarios

Abstract

Nowadays, online route planners for soft modes are provided by several platforms such as Google Maps, OpenStreetMap, Here, or Waze. Itineraries are usually built using Shortest Path Problem algorithms that minimize travel time or distance. In this work, we aim to identify and quantify the main features that influence itineraries’ choice by soft modes users in urban areas, able to support multi-objective routing, using simulated scenarios. We propose a set of 21 indicators, grouped into five dimensions: Safety-Security, Comfort, Air Quality, Accessibility, and Time-Distance. Another contribution of this work is the simulation of scenarios to study soft modes’ multi-objective routing within urban areas.