FAQ

Frequently asked questions

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Here, you will find some answers to the most frequently asked questions. For more information, don’t hesitate to contact us.

  • Great road safety: 95% of the accidents are caused by human error. Higher levels of autonomy can reduce dangerous human behaviors, such as impaired driving, drunk or drugged driving, speeding and distraction.
  • Personal freedom: ride-sharing and mobility on demand (“mobility as a service”) can fundementally improve people’s daily mobility. In addition, seniors or people with disabilities, who are self-sufficient but cannot drive, can gain great indepence thanks to autonomous vehicles. 
  • Saving money: Autonomous vehicles can help avoid the costs related to car accidents and medical issues, as well as expenses related to vehicle ownership. In a fully automated vehicle, occupants can pursue more productive activities, such as working, thus saving time. 
  • Environmental benefits: transportation accounts for most CO2 emissions worldwide. Car-sharing and optimised transportation can improve mobility efficiency and therefore reduce emissions globally.

SAAM is the most important association in the field of self-driving vehicles in Switzerland. It strives to make a sustainable contribution to passenger mobility and freight transportation. The association brings together a large number of important stake holders through an interdisciplinary approach.

SAAM promotes networking and collaboration between its members. Thanks to the synergies created, projects are developped together in a cost and resource optimized way.

Globally and in Switzerland, an increase in transport services is expected in the future and public transports will grow at an above-average rate compared to private motorised transport. Although Covid-19 is slowing down the forecast growth and changing mobility behaviour, it can still be assumed that demand will increase in the long term. Studies show that this growth market will be shaped by the trends of digitalisation, sustainability and sharing. There are already various On-Demand services that only drive when needed and can be ordered by customers via apps. Thanks to “pooling”, different customers travelling in the same direction can share the same vehicle. Self-driving vehicles are seen as a logical and necessary further development of On-Demand systems. This future combination of demand-responsive transport will permanently change existing transport systems. An association like SAAM is therefore needed to actively shape these developments.

Reports showed that the isolated pilot projects were very cost-intensive. Due to the now efficient bundling of forces in the association, we can achieve an optimal use of resources and can use the financial means efficiently.

SAAM is financed through membership fees. The association sees itself as a platform for linking different stakeholders in a meaningful way and thus implementing innovative ideas and tasks in the focus areas outlined above through joint cooperation. 

Individual members have already initiated various pilot projects in the past, but there has been no direct coordination between the parties. Through the SAAM association, these duplications can be eliminated and synergies created. In this way, projects with self-driving vehicles can be implemented in a cost and resource optimised manner.

The pandemic in particular has shown that classic public transport must be adaptable and versatile in order to survive major crises. One trend is particularly clear. The services are increasingly being adapted to the personal needs of the customers and must be able to offer maximum flexibility. Along with the electrification of vehicle fleets, this is currently one of the most important developments in passenger transport. SAAM will play a leading role in the testing and implementation of automated driving in combination with a personalised, flexible service.

There are already initial proposals for joint pilot projects, see page Projects. For example, a member of SAAM has proposed to transform an ordinary vehicle into an autonomous vehicle by using a kit for retrofitting. Then, the vehicle could be remotely supervised by teleoperation. This would enable the vehicle to drive a predefined route on its own. The fundamental advantage of this system is that existing fleets could be automated quickly and cost-effectively. The list of projects is available on this website.

There are three major hurdles that will need to be crossed in order for automated vehicles to be commercialised and running. These are technological, regulatory and societal factors.

On the technological side, the highest priority is the reliable functioning of all systems that communicate with each other, such as video cameras, radar and lidar sensors as well as the GPS system must protect themselves against total failure by means of a redundant structure, just like in an aircraft. Plus, sensors are not yet capable of functioning in all-weather and hazardous situations. Moreover, digital networking makes robot cars just as vulnerable to hacker attacks as PCs, and a small software error can cause a whole series of accidents. In regards to machine learning algorithms, there is to date no widely accepted solutions to ensure that they are safe. The development of cutting-edge research and development is therefore of immense importance.

In regards to societal barriers, there is a certain proportion of the population that still fear AVs. One of the main reasons is the recent fatal accidents in which autonomous cars were implicated. Also, autonomous vehicles have no room for error, as accidents are overly mediatised given the ethical threats posed by machines potentially harming humans.

Lastly, regulatory issues are complex as they depend on many factors such as the country in which the accident took place, the level of automatization, the ownership of the vehicle, the external factors of the accident, the source of the failure (was is the driver or the system that caused the accident?). That said, the current regulatory framework allows for partially automated systems to circulate on public roads (L2*). In case of accident where the vehicle’s driver is at fault, the liability will often go the vehicle’s owner. However, as vehicles become completely autonomous (L5*), the liability may shift to the vehicle manufacturers or technology providers if the accident originates from a system failure. The regulatory implications are still unclear for L3* and L4* vehicles, where drivers or teleoperators can take over the automated vehicle if it is in a hazardous situation. A new law ordonnance will soon come to light in Switzerland regarding the L3* and L4* issues.

*Levels of automated driving, from 0 to 5, where 5 consists of fully autonomous vehicles where no steering wheels are needed inside the vehicle. More information on automation levels here.

While full autonomous driving is not yet possible on Swiss roads due to regulatory limitations, the area of public transports, however, has been able to showcase different pilot projects on individual and short bus routes, named “last mile solutions”. These projects running in Switzerland represented the first approach to understand the current technological obstacles and to test the acceptance of the population towards autonomous vehicles.

Through these activities, Switzerland took a pioneering role, especially in the public transports area, given that the first pilot where people were transported in an automated shuttle took place in 2015. In the future, fully automated public transports will open up new perspectives, especially to transport people and goods on short distances on all public roads. These will be supervised using technologies such as teleoperation. On the longer term, it will be possible to make mobility more demand-oriented and to partially eliminate the existing rigid courses and bus lines.

It will still take time before automated vehicles can circulate on public roads. However, there is a noticeable dynamic currently going on in this area. The technology required for automated driving is continuously improving. The acquisition costs will decrease in the next few years due to the expected market growth. It is therefore expected that a breakthrough can be expected in five to ten years.

Currently, transport operators have been launching automated shuttles project in an individual approach. However, the idea is now to join forces for future pilot projects. Therefore, it is definitely conceivable that different operators will serve a common fleet. These projects will include partners from a number of different areas. These include research institutions, industry, transport companies, cities and municipalities, etc. We consider that an interdisciplinary approach favors ideas and innovation.

The use of technology is similar to some extent. This means that comparable radar systems are used in rail-based systems as well as on road-based systems.

Another component of pilot projects with self-driving vehicles will be that automated vehicles act as feeders to the railway. This means that, in addition to the physical connection (so-called first/last mile), a digital integration of such forms of service is required.

The main purpose of SAAM is to link the various stakeholders in a meaningful way in order to implement innovative ideas and tasks in the focus areas outlined in joint cooperation. Only by working together can we find out how autonomous vehicles can be used in public spaces without problems in the future.

The association does not see its purpose in the research and development of new technologies. Rather, SAAM is concerned with the technologies available on the market and examines the extent to which these can be used sensibly for future mobility systems or what additional customer benefits can be generated.

While machine automation has already been well established and working for decades, such as the production of vehicles which is entirely automatized, it is not yet the case for the vehicle’s driving capabilities. The reason is that the action of driving a vehicle in a mixed daily traffic, a constantly changing environment, is immensely more complex, for which classical automation programming is no longer sufficient.  Therefore, a new approach is required which comprises of two relatively new elements, being very large computing capacities on the one hand and extensive real-time data on traffic systems on the other. It is only with the use of artificial intelligence that it is possible to solve the complex issues raised by automated driving. In addition, in order for autonomous vehicles to be socially accepted, they must be safer than conventional vehicles. Indeed, one can tolerate an accident being caused by a human, but not if it is caused by a machine. As a result, automated vehicles must meet strict functionally safety and cybersecurity standards.

Two major user categories are identified amongst many others: private individual transport and collective transport.

The private individual transport user category has currently been at the heart of the current car manufacturer’s business models. This includes personal use vehicles (e.g. family cars) and commercial vehicles (e.g trucks). However, it is not certain that autonomous vehicles will thrive in this segment mainly due to the high costs that these new technologies will incur on the users. Indeed, the components and hardware such as sensors, lidars, radars, cameras may discourage people to buy such vehicles as the cost-benefit ratio will not be so evident.

The second user category is the collective transport where the ownership of an autonomous vehicles will tend to be replaced by transportation services, so called “mobility as a service”. This would result in lower sales of privately owned vehicles, but would favour a broader collective use of vehicles, as even children or people with disabilities who previously couldn’t drive will now have access to vehicles. People will be able to order autonomous vehicles, so called “on demand” services, via a sharing model or a centrally operated vehicle fleet provided by a phone app or platform.

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