Public transport is very good to offer a service along a line, but the demand is actually from point A to point B. If we had smaller vehicles, we could actually satisfy this point to point demand directly. And if we could make these smaller vehicles also driverless, then the cost would go down and that would actually offer a really attractive service.
Further developing autonomous and flexible mobility solutions for public transport is a task of the KelRide research project. It is funded by the Federal Ministry of Digital Affairs and Transport.
The project combines two very important topics, on the one hand autonomous mobility and, on the other, digitalization. We need both in order to improve public transport services. Analogously, we are faced with limits that we cannot overcome without such new technologies.
Improvements are intended to enable greater flexibility and optimal integration into the everyday lives of users.
We in Kelheim expect many things because autonomous buses and cars are the only way for mobility in the future. So society is aging and the people want to be mobile and individual mobile, and the only way is autonomous buses and autonomous cars.
To this end, the KelRide research project is integrating an autonomous on-demand ride-pooling service into the public transport network.
Our vehicles utilize a wide range of different sensors, for example, LiDAR sensors, cameras ,or GPS. With this perception means we achieve a 360 degree view around our vehicle and thus ensure safe operations on public roads.
Our highest priority is that the vehicle is always in a safe condition, no matter how bad the weather is. The technology must always be able to analyze the weather condition and its impact on the vehicle and react accordingly.
The further development of the operating software is intended to enable vehicles to drive safely and reliably, even in bad weather.
Sustainability has always been very important for passengers of autonomous shuttles. They actually want to use the autonomous shuttles when the weather is bad, when they don't want to walk or take their bike, when it's raining or it's foggy. Up to now, these weather conditions have been a challenge for autonomous shuttles. We had some limitations, and the whole KelRide project is about improving performance in this important weather.
At various locations in Europe, together with the vehicles, manufacturer, software, TU Berlin, and testing service providers, the project team is pursuing these exact tasks to improve suitability in all types of weather.
The main challenge for rain or snow or storm situations is to be able to filter out these particles. We have differences between the snowflake, which is bigger, and a drop of water or a fog, which can vary in density. We want to find the right balance to be sure we can filter out these particles. The KelRide Project brings us an opportunity to test in real-life conditions our solutions to tackle rain, snow, or storm situations.
We as an independent testing institute, ensure that the manufacturer's specification meets the regulation. We do that by testing the vehicle in real-life scenarios. On our proving grounds, such as ZellaZone, we can simulate different weather conditions in the form of scenarios and test if the vehicle can master such situations flawlessly.
As part of the KelRide project, in addition to being suitable in all types of weather, the flexible on-demand solution on variable routes and at flexible times is an important part of the research. Autonomous vehicles must be able to know these variable routes and control them flexibly as needed.
Our main challenge for the flexible routing is to map perfectly the area we drive on to provide a safe and as complete as possible route for the on-demand application so that we can drive between one station and another as fast as possible.
Passengers book on-demand rides either through an app or via phone, and based on their pickup and drop-off destinations, we then pass on missions to the autonomous vehicles so it knows where to go. Our intelligent algorithm pulls together different riders headed in the same direction in order to create a highly efficient and highly flexible public transit network.
Since July 2020, Kexi on-demand transport has been operated in the district of Kelheim, which also provides a framework for the practical implementation of the KelRide Project. At the end of the KelRide Project term in 2023, a mixed Kexi fleet consisting of autonomous and conventional vehicles will complete the public transport service in the district's research area, particularly over the last mile.
So in the future, we'll continue to always add developments to be even more performant in very harsh conditions. But even further than that, the idea is really to deploy the EasyMile solution at scale in level 4, and that's something that we are actively working on. So more complicated traffic conditions, higher speeds, and especially, we are in the future, really focusing on rural transportations. There is a very high demand today for transporting people, elderly people, in villages, in rural conditions, at higher speed. And that's going to be one of our developments now.
The improvements from our side, from the project consortium, are definitely the speed of the vehicles. It's still very limited, and secondly, there's the quality of service. So we need more vehicles in the fleet to really enhance the quality of service, and with that also the area of service. Right now, it's very limited to the core city center, and this should be expanded to the whole region of Kelheim. And also this concept and Blueprint can then be scaled to Germany or even Europe.
We live in a time of great transformation to our mobility, we need climate neutral offers that are affordable to everyone across the board. To do this we need a variety of mobility services and must analyze a lot of new things in practice. Autonomous systems offer us enormous opportunities but need to be tested within the scope of live operation, and such pilot projects, those pioneers, enable us to learn and therefore we support and found them.