Research team studies carpooling decisions


PICTURE: Illustrative view After

Credit: Christiane Kunath

By carpooling, the trips of two or more customers with similar origins and destinations are combined into a single taxi trip. The concept can make a significant contribution to sustainable urban mobility. However, its acceptance depends on human needs and behavior. For example, while shared journeys generally offer a financial benefit, passengers may suffer inconveniences in terms of comfort and travel time. These factors give rise to different adoption behaviors that explain the usage patterns seen in 360 million real-world ride requests from New York and Chicago in 2019. The study has now been published in the journal Nature Communications .

Carpooling (or carpooling) is more effective in places with high demand and a large number of requests for similar journeys. However, it has been difficult to answer if and under what conditions people are really willing to adopt carpooling. In their study, the researchers decipher the complex incentive structure that underlies the decision to adopt or not to carpool. In a game theory model, they describe the adoption of sharing for all users who book rides from the same location.

The researchers demonstrate how the interactions between these individuals lead to two qualitatively different models of acceptance. In one, the willingness to share rides is still high. In the other case, however, the willingness to share rides declines as the overall demand for rides increases. If there are only a few users in the system, the number of carpool bookings increases with the number of ride requests, but if there are a lot of users, usage stabilizes. The relative number of requests for shared journeys therefore decreases – despite an optimized route with shorter detours for passengers when demand is high.

“Passengers are speculating on whether they can take advantage of the cheaper fare when sharing a ride, but they actually hope to be carried alone and therefore directly from A to B due to the low demand for rides,” explains David Storch, PhD student to the President of Network Dynamics and lead author of the study. When demand is high, for example during normal peak hours, the chances of being carried as a single passenger are lower – “Passengers almost certainly lose their comfort when sharing a ride. They tend to book the more expensive fare more often to travel alone. “

In an analysis of more than 360 million actual travel requests in New York and Chicago, the researchers were able to identify the demand patterns they had previously found in their model, confirming the validity of their results. The analysis shows that, depending on the starting point of the journey, the two adoption patterns exist in parallel in the two cities. Malta Schröder, Associate Researcher at the Chair, interprets the results as follows: “Given that the two adoption models coexist in cities, a moderate increase in financial incentives is probably already sufficient to greatly increase the acceptance of carpooling in cities. ‘other places and for other User Groups. ”


Title: Incentive Driven Transition to High Rideshare Adoption.
Authors: David-Maximilian Storch, Marc Timme, Malte Schröder
Nature communications
DOI: 10.1038 / s41467-021-23287-6
https: // /articles/s41467-021-23287-6

About the Network Dynamics Chair
The Chair of Network Dynamics headed by Professor Marc Timme was created in 2017. The aim of this Chair of Strategic Professor TU Dresden affiliated to both the former Cluster of Excellence “Center for Advancing Electronics Dresden” (cfaed) and at the Institute of Theoretical Physics is to connect the knowledge of applied mathematics and theoretical physics with applications in biology and engineering. This is the first chair in network dynamics of this interdisciplinary type in Central Europe. Since networks are almost everywhere around us, the research team aims for a unifying understanding of the fundamental mechanisms underlying the collective dynamics of large, interconnected nonlinear systems by combining first principles theory with analysis and analysis. data-driven modeling. A significant part of their work focuses on the study of emerging phenomena and the development of new conceptual perspectives on complex systems as well as on the theoretical computational tools necessary to understand these systems. This fundamental understanding forms the basis for predicting, and eventually controlling, the dynamics of complex networked systems in all disciplines.
http: // www.cfaed.tu-dresden.from /cfnd-about

About cfaed
cfaed is a research cluster at TU Dresden (TUD). As an interdisciplinary research center for electronics perspectives, it is located at TUD as a central scientific unit, but also integrates nine non-university research institutions from Saxony as well as TU Chemnitz as cooperating institutes. With its vision, the cluster aims to shape the future of electronics and launch breakthrough new applications, such as electronics that do not require startup time, are THz imaging capable, or support technology. complex biosensor. These innovations bring performance improvements and imaginable applications that would not be possible with the pursuit of current silicon chip based technology. To achieve its objectives, cfaed combines the thirst for knowledge of the natural sciences with the innovative power of engineering.
http: // www.cfaed.tu-dresden.of

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