AI for mobility research: Towards fully automated travel diaries

Our current transport systems are facing a number of fundamental challenges. These include growing urbanization, and the generation of numerous other externalities like congestion, noise- and local air pollution, which can be partially attributed to old transport planning methods. This has led the transportation sector to be one of the largest contributors to greenhouse gas emissions.

Travel diaries are one of the primary data collection and mining tools used in a large proportion of the traditional transport research fields. They record individually reported information about performed trips, traditionally using paper & pencil. Since the advancements in big data, GPS sensory/availability, and machine learning methods, this task can be fully automated and done with much higher accuracy. The resulting data provides the basis for many modern transport planning applications, in academia as well as in praxis. MOTIONTAG and ETH Zurich Institute for Transport Planning and Systems (IVT) work together on various research projects to leverage this technology and drive change in the mobility sector.

In this webinar you will learn:

• Why traditional transportation diaries aren’t enough anymore and which pain points are removed when doing smartphone-based surveys.
• How data with high granularity helps researchers understand mobility behaviors and what types of questions they can help answer.
• About the most recent studies from the IVT.

“My group has been engaged in travel diary collection and analysis since its beginning in 1999. Over the years the traditional way of collecting diaries by paper-and-pencil surveys has become less productive in terms of data quality and response.”

– Prof. Dr. Kay Axhausen – Professor and Chair of the Transport Planning at the ETH Zurich