Work

Democratizing Urban Mobility Through an Open-Source, Multi-Criteria Route Recommendation System

Year: 2024

Type: conference-paper

Abstract: Urban navigation systems traditionally optimize for efficiency, thereby overlooking environmental factors and personal preferences. This paper introduces Routify, a novel multi-criteria recommender system for personalized urban route selection. Routify advances the state-of-the-art in route recommendation through: (1) integration of diverse environmental data (air quality, noise levels, green spaces) with real-time IoT inputs; (2) a dynamic weighting algorithm allowing fine-grained user control over routing parameters; (3) transparent decision-making via an interactive interface displaying edge-level information; and (4) a community-driven feedback mechanism that continuously refines recommendations. We have implemented Routify as an open-source platform, facilitating further research and development. Experimental results from 1000 origin-destination pairs demonstrate significant improvements in user-defined environmental metrics (up to 32.98% increase in green index for walking and 16.91% reduction in noise levels for cycling) compared to traditional routing systems. These improvements come with slight trade-offs in distance, especially in walking mode. Our research contributes a comprehensive framework for multi-criteria route recommendation, balancing individual preferences, environmental factors, and community insights in urban navigation.

Source: ACM Conference on Recommender Systems (RecSys)

DOI: 10.1145/3640457.3691702

Authors: Alexander Eggerth, Javier Argota Sánchez-Vaquerizo, Dirk Helbing, Sachit Mahajan

Institution: ETH Zurich

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: bronze

Funder: European Commission