How simulations make autonomous mobility plannable

An interview with MOIA Mobility Consultant Tom-Erik Kuhlen

Tom-Erik explains how clients use simulations to make data-driven decisions for autonomous mobility

How will autonomous mobility transform our cities and how can its benefits be made tangible? At MOIA, the answers begin with models. MOIA Mobility Consulting uses simulations to show how new mobility services impact traffic flows, emissions, and public transport utilization, long before a single vehicle is deployed.

These models make visible how many vehicles are needed, which areas can be served efficiently, and what effects autonomous on-demand services have on existing transport systems. For transport planners and city authorities, this provides a valuable foundation to make data-driven decisions tailored to their specific region.

Tom-Erik Kuhlen works at MOIA as a Senior Transport Modeling Specialist in the Mobility Consulting team. He focuses on models, simulations, and their analysis, advising clients from various cities and regions in their decision-making processes. In this interview, he explains how models are developed, the role they play in political and strategic decisions, and which arguments are particularly persuasive.

What exactly do you do at MOIA?

I work in the Mobility Consulting team. Our task is to make visions measurable through modeling and simulations. To do this, we use data, transport models, our experience from operating our ridepooling service in Hamburg, and insights from various consulting projects on autonomous driving.

Our simulations allow us to design different scenarios. For example, we model scenarios with varying fleet sizes or different service areas. Based on this, our clients can clearly see the impact that different types of autonomous mobility services would have in their region.

Using data, we can determine how new services can be integrated into existing transport systems and what benefits they create.

How do models and simulations influence decisions?

Models and simulations make ideas tangible and enable data-driven decision-making. The visual presentation of the simulations help stakeholders to imagine new mobility services. The analytical results allow different scenarios to be compared and evaluated. Using our models, we analyze how factors such as fleet size influence service quality, how new services affect residents’ travel behavior, and how many emissions can be saved by a given transport measure. Our goal is to demonstrate how autonomous mobility complements existing transport systems and which added value it creates. By providing data and visualizing effects, our clients, such as public transport operators, cities, and private companies, can make well-informed decisions.

Which data is crucial for your models and simulations?

For an initial model, publicly available data is sufficient, such as population data, points of interest like restaurants, bars, and airports, as well as our own observational data from Hamburg. For more detailed analyses, we enrich the models with additional data, including workplaces, households, and commuting patterns. In our most detailed simulations, we model all modes of transport, from pedestrians to metro systems. Each simulated individual then makes decisions within the model based on their own needs, choosing between different modes of transport.

How does autonomous mobility change cities and regions?

This depends a lot on the region itself. For the first time, autonomous mobility can provide public transport quality in rural areas, comparable to that of cities.  Waiting times and walking distances to the next transport option are reduced, fundamentally changing people’s daily lives. In cities, autonomous mobility increases efficiency, reduces emissions and noise, and frees up space, as a more efficient transport system requires fewer parking areas and narrower roads. This improves quality of life and makes the transport system more equitable. Additionally, autonomous vehicles are safer than human drivers. In the long term, they can also help address staff shortages in public transport.

How should autonomous mobility be deployed to create value? Is the rule “the more vehicles, the better”?

That depends on the region as well. There is no one-size-fits-all solution. Autonomous mobility must always be considered as part of the overall system. In Europe, most cities already have well-developed public transport systems. To encourage more people to switch from private cars to public transport, more convenient solutions are needed. Autonomous, on-demand services can play a key role here. In suburban areas, autonomous shuttles can replace underutilized bus lines, especially during off-peak hours. In rural areas, they can serve as feeder services or even as a basic transport offering.

How important is the interaction between different modes of transport?

Intermodality, the interaction between different modes of transport, is essential. Each mode has its own strengths and weaknesses, so an efficient and comfortable system can only be achieved through their combination. For example, autonomous shuttles can serve as effective feeder services to rail-based transport.

What challenges exist when integrating autonomous mobility into existing transport systems?

Transport systems are extremely complex, especially because many different interests must be balanced. Our goal is to deploy autonomous vehicles in a way that improves the overall system. Achieving this requires a careful balance of interests. This is exactly where our models and simulations provide support.

What role does acceptance play in the successful integration of autonomous mobility?

Acceptance plays a crucial role. People need to experience and try autonomous vehicles themselves, because visibility builds trust. In Hamburg, we see that openness increases as vehicles become visible on the streets and as we communicate their use through various channels.

Three years ago, the topic was still largely conceptual. Today, there are real-world examples. This changes the discussion: autonomous mobility is no longer a promise for the future, it is already working. Real-world safety data from existing services, such as Waymo in the United States, also helps demonstrate that autonomous vehicles are significantly safer than human drivers.

One last question, Tom-Erik: What is your vision for the mobility of the future?

Mobility shapes our quality of life. It determines what our cities look like, how noisy they are, how space is distributed, and who has access to opportunities. Autonomous mobility can improve all of this. In cities, it enables more efficient transport systems with less noise, fewer emissions, and more space for people. In rural areas, it provides everyone with the freedom to travel from A to B, regardless of age, driver’s license, or car ownership.

My vision: a transport system built for everyone. Autonomous driving is the key to achieving this.

Unlocking the full potential of autonomous mobility through simulation

Autonomous mobility will fundamentally transform cities and regions. To fully leverage its potential across different needs and regional conditions, simulating various scenarios is essential. This enables data-driven decisions on how autonomous services can best enhance existing transport systems in a region.

MOIA Mobility Consulting’s models deliver exactly that: visually tangible, data-driven insights. They show what a city could look like with autonomous vehicles, how mobility behavior might change, and what impact this has on overall quality of life.

Simulations are the first step toward significantly improving transport systems through autonomous mobility.

Further articles on this topic:

• Find out in our Germany simulation what impact a nationwide autonomous ridepooling service would have.
• Read more about the Mobility Impact Analyzer Tool, which enables customers to run simulations themselves for their region.