Climate impacts of automated and connected driving

Previous studies have come to the conclusion that the effects of automated and connected driving on the climate will primarily depend on three factors: (1) the fuel efficiency of vehicles, (2) the effect on the flow of traffic and (3) the impact on the overall volume of traffic, which in turn­ is a consequence of­ users’ mobility behavior. ­Depending on the development of these factors, two basic scenarios can be derived. In the best-case scenario, a­ combination of increased fuel efficiency of vehicles,­ an optimized traffic flow and a significantly lower traffic volume leads to a reduction in CO2 emissions. In the worst-case scenario, the­ attractiveness and convenience of automated and connected driving leads­ to an excessive­ use of motorized private transport, which increases the volume of traffic and­ mitigates or potentially even overcompensates the­ positive effects­. These positive effects include potential savings in energy consumption and greenhouse gas emissions, but also the creation of more attractive urban spaces.

Best-case scenario: CO2 reduction through higher­ efficiency and lower traffic volume

Automated and connected vehicles can contribute in several ways to reducing CO2 emissions and thus to climate protection. First, such vehicles are very likely to consume significantly less fuel,­ thereby reducing CO2 emissions. For instance, researchers at the University of Michigan believe that automating driving­ can reduce­ CO2 emissions by up to­ 9% compared with conventional vehicles. For one, it is assumed that as the­ technology­ matures, the­ weight of the vehicles and thus fuel consumption will decrease. This is mainly due to the fact that the size of automated vehicles­ could be increasingly adapted to the number of passengers. An additional efficiency potential results from the interconnectivity of the vehicles, whereby a significantly optimized traffic flow can be achieved. If cars are connected to each other and to the infrastructure, traffic can be controlled better and influenced more directly. For example, automated and connected vehicles can warn each other of dangers, drive in convoys (­so-called “platooning”), reduce speed before traffic lights and avoid traffic jams. Due to this constant driving style, adapted to the traffic, traffic flows more efficiently. This in turn leads to lower fuel consumption and a reduction in emissions.

In addition to the effect on fuel consumption and the traffic flow, the effects of automated and connected driving on the traffic volume as a whole are of central importance. Even if CO2 emissions per vehicle are reduced, the overall effect on CO2 emissions, as well as other traffic-related emissions such as air pollutants, depends on how many vehicles are on the road and how many kilometers they cover. This in turn­ depends in particular on how the vehicles­ are used. The greatest potential for reducing CO2 emissions arises when automated vehicles are used­ collectively in the form of shared mobility services. The term “shared­ mobility” covers mobility services which are shared by users, either simultaneously or successively­. Hence, the user is not necessarily the owner of the vehicle. In addition to local public transport, this includes services such as “ridehailing” and “ridesharing”. Ridehailing refers to the­ direct booking, usually by app, of a private ride for­ a time and distance-based fare. Among the most prominent representatives of this category are companies such as Uber, Lyft and Didi Chuxing. Ridesharing, on the other hand, refers to the joint use of a vehicle for passenger transport. Examples of providers of such services are the online platform BlaBlaCar and Daimler’s car2go. Such services, which could completely redesign transport and mobility structures, are particularly expected in urban environments. ­Through them, the­ need for single journeys and­ individually used vehicles could be significantly reduced, which would also decrease the total number of vehicles.

­Simulations for Lisbon and Helsinki already show how large the (theoretical) bundling potential of existing mobility needs­ is, especially in­ urban areas. For the Portuguese capital, researchers at the International Transport Forum (ITF) have calculated that­ the number of vehicles could be reduced by up to 90% compared to today if all current traffic were handled by fleets of automated vehicles (shared taxis) alone. In the event that such automated shared taxis completely replace passenger cars, buses and conventional taxis, a 62% reduction in CO2 emissions would be possible in Lisbon. Using identical­ simulations for Helsinki, the scientists conclude that CO2 emissions could be reduced­ by 28% and congestion by 37%.

Lastly, the positive effects could be strengthened even further, provided that all­ automated vehicles are operated purely electrically. This could not only reduce CO2 emissions, but also eliminate air pollutants and thus make cities­ more livable. In view of the numerous automated test vehicles that are already on the road purely electrically, this seems quite likely in the long term. However, experts assume a long transition period. Ultimately, it must also be borne in mind that the effects on emission reduction­ depend to a large extent on the­ energy sources used to generate electricity for charging electric vehicles as well as on CO2 emissions during battery production.

Worst case scenario: CO2 increase through mass use­ and increased traffic volume

A large part of the positive effects discussed depend centrally on the question of whether people are actually prepared to switch to shared mobility services, i.e. to increasingly forego owning their own vehicle. An­ alternative scenario is also conceivable, in which the­ attractiveness and convenience of automated driving leads to an increase in­ motorized private transport while at the same time weakening public transport. Public transport in particular is threatened by a vicious circle: If passenger numbers in public transport­ fall ­due to increased mobility comfort and thus a shift in demand towards­ automated (individual) vehicles, this will lead to price increases or a drop in quality in public transport in the medium term, which will further weaken its ­competitiveness. In this case, not only the share of automated vehicles in the modal split (a measure of the distribution of transport demand between different modes of transport) would increase, but also the overall traffic volume. This could massively weaken or even overcompensate the positive savings potential of automated vehicles.

In addition to the promised gain in comfort, new user groups could also contribute to an increased traffic volume. For instance, automated vehicles open up new opportunities for mobility for the elderly, young people, people with­ disabilities and the population in rural areas. In addition, it is conceivable that professionals could be driven by their automated vehicle to their place of work­, then sent it back to the suburbs for free parking and­ be picked up again in ­the evening. ­This could lead to an increase in commuter traffic and offset the positive effects on the climate and the environment.

If attractive “shared mobility” services aren’t established, and instead focus rather is on­ personal comfort gains and the creation of supplementary­ mobility offers in individual transport, automated vehicles could­ further exacerbate the existing negative effects of road traffic. ­This applies at least as long as no complete electrical solution, including a clean electricity mix, has been implemented.

How can the positive potential be leveraged best?

Although the future effects of automated and connected driving on the climate are difficult to quantify due to the numerous determinants, decision-makers from industry and politics can already actively set the right course today to make the­ best possible use of the positive potentials. In­ order for the beneficial­ effects of automated and connected driving on the climate to dominate, intelligent island systems (see diagram below) must be integrated into a connected, coordinated overall system. Moreover, an uncontrolled growth in private motorized transport must be prevented.

The integration of intelligent island systems requires the creation of framework conditions for the establishment of effective traffic flow management. This is because fleets of automated vehicles can only have a positive effect on traffic congestion if­ their use is precisely controlled. This requires that the overall responsibility for the creation of highly connected local transport systems between public and private companies is meaningfully defined. In addition, the question arises to what extent­ the legal framework for the regulation of public transport­ must be adapted­ with regard to new supply models. ­Urban planning activities must also be initiated, in particular to optimize urban transport systems with regard to mixed traffic between automated and conventional vehicles. Interconnectivity for collaborative­ automated driving­ should also be ensured to­ achieve optimized traffic flow. This includes, for example, investments in intelligent road infrastructure that enable platooning or priority planning at intersections.

In order to­ prevent an uncontrolled growth of individual motorized traffic,­ several measures are possible. First of all, the demand for mobility must be­ intelligently controlled, for example by introducing a dynamic city toll for (automated) individual vehicles. This toll could be higher at peak times and thus­ bolster the price advantage of public transport and automated taxi fleets­ compared to individual motorized transport. Ultimately, attractive shared mobility services­ with a high capacity utilization­ must­ prevail­ over­ automated individual transport. Here, it is important to ensure close links between private and public actors. In order to­ be able to permanently replace­ individual transport solutions,­ such “shared mobility services”­ must also be made available around the clock. Furthermore, the cost advantage of public transport should be secured and an­ attractive range of services guaranteed. This­ also includes providing comprehensive intermodal door-to-door services and integrating automated vehicles where suitable.

Situation in China and Germany

While Germany plays a­ leading role in the technological development of automated driving­, China today offers the better framework conditions for a sustainable future of mobility. This applies both with regards to the social acceptance of automated “shared mobility” services as well as to the­ diffusion of electro-mobility in Chinese cities.

Through massive government intervention, China has become the world’s largest and most important market for­ electro-mobility. And the Chinese government continues to set itself ambitious targets: By 2020, at­ least five million purely electric vehicles are to drive on China’s roads­. ­These strengths in the field of­ electro-mobility open up the­ possibility for ­China to­ also quickly and reliably equip automated and connected vehicles with electric drives in the future.

According to a study published in 2017 by management consulting firm Roland Berger, China is also­ ahead of Germany in terms of shared mobility. ­Beijing has been pushing ahead with the development of corresponding­ products and services – always in combination with electric vehicles – for years. For instance, the Chinese government attaches great importance to the integration of automated vehicles in the field of ridehailing. An example is the Chinese start-up Pony.ai which plans to ­deploy a fleet of 20 highly automated ridehailing vehicles in the southern Chinese city of Guangzhou as early as 2019. In July 2018, ­the Daimler-backed start-up Momenta­ also signed a contract with the eastern Chinese city of Suzhou to offer a fleet of automated vehicles as soon as possible. For this, the social acceptance of “shared mobility” services and the willingness to completely forego one’s own vehicle are key success factors. Here, too, China has a lot of potential. According to­ the consulting firm PwC Strategy&, 79% of Chinese consumers are “definitely” or at least “­perhaps” willing to give up their own vehicle as soon as fleets of fully automated vehicles become available. In the EU, however, this figure stood at only 44%. As a result of all these factors, the­ consulting firm­ predicts that by­ 2030, shared automated vehicles will account for 36% of total road transport­ in China, compared with only 15% in the EU.

Outlook

Whether automated and connected driving will have a positive or negative impact on the climate and the environment will strongly depend on­ how society, the economy and the public sector deal with these new technological possibilities and how they use the wide-ranging possibilities to design new mobility services. In particular, future mobility behaviour, technological breakthroughs and their market penetration as well as the necessary further development of regulatory frameworks are currently difficult to predict.

Although China at the moment seems to be equipped with better­ framework conditions than Germany, the­ awareness that behavior patterns, laws and business models must change fundamentally is present in both countries. The challenges are the same: to create a connected, coordinated transport system and at the same time­ limit the uncontrolled growth of motorized individual traffic. ­If climate and environmental protection­ are to be taken­ seriously­, both Germany and China must provide solutions. Here, both countries can benefit from their increasingly close partnership in the field of automated and connected driving.