News

Our paper Bike Network Planning in Limited Urban Space was accepted for publication in Transportation Research Part B: Methodological!

This paper was part of the e-bike city project, a multidisciplinary initiative at the department exploring the effects of a radically changed urban road space with priority on cycling. Planning a suitable bike network is a core challenge in this project. In our paper, we introduce a novel optimization method for placing new bike lanes with minimal impact on other travel modes.

Our approach leverages the concept of Pareto-optimality: When car lanes are repurposed as bike lanes, car travel times inevitably increase. The key question is: By how much? Pareto-optimal solutions are the street networks that present the best trade-off between car accessibility and bikeability. To quantify bikeability, we introduce the concept of “perceived bike travel time”, based on research showing that cyclists perceive dedicated bike lanes as faster. Our experiments show that the optimization approach outperforms other methods by proposing networks that have both lower car travel times and lower perceived bike travel times.

Check out our paper or get in touch if you are interested to know more!

Further resources:

• Open-source code
• Web app for bike network planning (beta)

A new paper, titled “Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories”, was presented at the 16th International Conference on Spatial Information Theory (COSIT 2024).

This paper introduces the Spatial Nudging framework—a theory-driven approach that maps out nudging strategies in the mobility domain, with a focus on cycling. The framework integrates physical and digital interventions to promote sustainable mobility, drawing from behavioral theories such as Nudge Theory and the Theory of Affordances. Additionally, we propose a graph-based workflow that uses cognitive graphs and the Fine-to-Coarse heuristic to model how cyclists perceive their environment. This method generates cognitive routes that align perceived affordances with the physical environment, closely resembling real-world cycling trajectories.

For more details, check out our paper!

Ayda Grisiute gave a talk at the 8th Cycling Research Board Meeting (CRBAM). The presentation, titled “Conceptualizing Spatial Nudging: A Theoretical Framework for Integrating Interventions to Promote Cycling“ introduced Spatial Nudging framework that delineates nudging practices in the mobility domain and offers a theoretically integrated perspective on promoting cycling through spatial interventions.

In addition, Ayda presented a poster titled “Building a Planning Tool for the E-Bike City Vision,” which showcased a web application created by two geomatics students. The tool helps urban planners reallocate road space for bike lanes using various optimization strategies.

Check out the poster here!

As the ecosystem of transport planning and evaluation metrics, tools, methods, and services grows, there is a pressing need to enhance domain interoperability and interpretability. In our new paper, titled “An ontology-based approach for harmonizing metrics in bike network evaluations“ , we construct a formal ontology, VeloNEMO, a formal ontology designed to capture the key attributes of bike network evaluation metrics and resolve terminological inconsistencies across them. We also introduce a machine-readable knowledge graph that compiles existing metrics, allowing for more efficient meta-analyses of various evaluation strategies. To further enhance transparency, we offer recommendations for making metric descriptions more comparable across different evaluation approaches.

For more details, check out our paper!

What is the potential for integrating vehicle-to-grid with car sharing in the future? As part of the V2G4Carsharing project, we simulated scenarios for 2030 and quantified the benefits in terms of monetary savings and peak shaving effect. In our case study done in collaboration with the swiss car sharing provider Mobility, we found that Mobility could offer flexibilities between 12 to 50 MW, dependent on the scenario. There is a sweet spot where both car sharing and power grid operators benefit.

Our paper titled Vehicle-to-grid for car sharing – A simulation study for 2030 was now published in Applied Energy! Check out the paper here.

Get in touch if you are interested to learn more, or checkout our project code base and the car sharing simulator.

Our paper on “Quantifying the dynamic predictability of train delay with uncertainty-aware neural networks” has been published in Transportation Research Part C!

In light of the importance of accurate delay prediction for transport services and passengers, many predictive methods have been proposed. However, they hardly account for the involved uncertainty and there is a lack of work analysing the dynamic predictability over time. We fill this gap with an uncertainty-aware neural network and a framework for describing the predictability by the prediction horizon. The results on Swiss train delay data show 1) an exponential decay of the predictability by the horizon, 2) a significant portion of (aleatoric) data uncertainty in contrast to model uncertainty, and clear advantages of the NN compared to MC models.

For more details, check out our paper! This work was done in collaboration with the Institute for Trans­port Plan­ning and Sys­tems at ETH Zurich.