AI and Mobility in Rural Regions
If Germany wants to achieve its climate goals, the transportation sector must make a considerable contribution. In 2021, the sector produced around a fifth of all greenhouse gas emissions in Germany. There is plenty of room for cutting those emissions. According to the 2022 Climate Action Report, it is likely that the goal of reducing transportation sector emissions to a maximum of 85 million tons of CO2 equivalent by 2030 will be missed by approximately 41 million tons of CO2 equivalent – if there are no changes to current trends. One reason for the transportation sector’s poor emissions performance is the ongoing dominance of cars, i.e., motorized individual passenger vehicles. Private vehicles accounted for 74 percent of all passenger traffic in 2019, yet bus travel, rail and cycling all produce lower emissions than cars, assuming average occupancy. From the perspective of climate protection, it is necessary to significantly increase their share.
The think tank Agora Verkehrswende points out that shifting to public transportation is particularly challenging for the roughly 30 million people who live in rural regions of Germany, whose share of total passenger-vehicle traffic is around 37 percent. Population numbers in rural areas are shrinking, and that has led to lower public transportation occupancy rates. Financially, it has grown more difficult to maintain public transport networks in such regions, and the options available have declined. For many people, that has translated into a longer distance to the next bus or train stop, and thus a higher hurdle in the way of doing without a private vehicle. Those who have no driver’s license or their own car face limited mobility in rural regions. The result is a lack of equal access to mobility, which makes equal participation in society more difficult.
Digital networks simplify access to car-sharing options and to public transportation, which is why they are frequently touted as a driving force behind the mobility transition. But whereas digital options in densely populated urban areas are a lucrative business for the mobility industry, sparsely populated rural regions with low user rates remain unattractive. AI-supported mobility could change this. Autonomous, networked minibuses can lower labor expenses and be flexibly deployed in rural areas. Such an affordable and efficient development in sparsely populated areas should encourage more people to give up their cars. The Association of German Transport Companies believes that autonomous buses have great potential, and in its immediate plan for the mobility revolution, it has formulated the goal of advancing automation in public transport by 2030. The development of autonomous and networked vehicles is also being pushed at the political level. Since 2016, for example, the German Ministry for Digital and Transport has invested around 256 million euros into 72 research projects in the field, with one of the goals that of achieving Germany’s climate goals in the transportation sector. But will such efforts be enough to meet the urgent challenges of implementing a climate-friendly mobility strategy? And what about the sustainability of the AI systems that will be deployed and of the infrastructure they require? The SustAIn team sought answers to these questions by taking a closer look at the example of autonomous buses in rural regions.