This presentation discusses using crowdsourcing to improve urban mobility by better understanding modal split and mapping mobility infrastructure through tasks completed by individuals, city inhabitants, and crowdworkers. The project aims to design spatial crowdsourcing tasks that provide services for the common good, are gamified, and foster cooperation to help policymakers improve mobility services and policies through more accurate data collection and assessment.

1. This project has received funding from the European Union’s Horizon
2020 research and innovation programme
The Human Factor for
Urban Mobility
Luis-Daniel Ibáñez
University of Southampton
BDVA - MeetUp, May 2018

2. 3 out of 4 Europeans live in urban areas
Traffic congestion costs us €100 B yearly
Road transport is responsible for 40% of CO2
emissions
Urban Mobility matters

3. Effective estimation of modal split
= Better policy design
= Better policy assessment

4. Mobility Infrastructure
Complete mapping
Measure occupancy
= Input for policy design
= Improved mobility services

5. Additional challenges
Responsible
Development
Citizen
Engagement

6. QROWD’s value chain
Individuals City inhabitants
and workers
Crowdworkers

7. QROWD for individuals
● App as data collection enabler and as an
interaction tool.
– Information and Explanation
– Management of incentives
– Engagement

8. QROWD for inhabitants
● Spatial and non-spatial tasks that
– Provide service for the common good
– Gamified
– Foster cooperation and collaboration

9. QROWD for crowd-workers
● Re-design spatial tasks for crowd-workers
– Using virtual street imagery
– Novel interface designs