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Societal benefits
Safety:
In the EU in 2018 38% of all road fatalities occurred in urban area (Key figures 2020 – Road safety
targets, DG MOVE). Considering that urban traffic is typically low speed, the number of non-fatal
crashes with personal injury is disproportionately higher in urban areas compared to non-urban roads.
Safety-enhancing measures in cities will thus be particularly effective in the reduction of injuries.
Efficiency and the environment:
Automated driving technologies will increase the efficiency of the transport system and reduce traffic
congestion regardless of whether they are used in individual transport, in collective mobility services
or in goods transport. In turn, smoother traffic will reduce fuel consumption and emissions. This is
especially true in urban traffic due to the concentrated demand for mobility. Here, too, however, the
prerequisite is a high penetration rate of highly automated vehicles and organized interaction in the
traffic environment. Automated driving technologies, for example improved fleet management, have
the potential to optimize vehicle usage and future mobility services. In the end, this optimised use of
automated mobility modes even shows a potential to reuse space in urban environments and improve
the liveability in cities.
Accessibility and social inclusion:
With automated on-demand mobility services, people with reduced mobility will have a new source of
mobility and better access to city centers and remote locations. Automated driving allows people to
stay mobile for longer and greater participation in their social life. The population in cities will continue
to grow in the coming years – and with it the need for transport. With fully automated and driverless
vehicles this gap can be closed. This will not remove the existing mobility offers (taxis, public
transportation, etc.) in cities, but will complement them in an efficient way.
Demonstrations
Demonstration projects shall support the impact assessment of L4 automation use cases like car valet
parking and shuttle services and facilitate the assessment of acceptance and affordability. Moreover,
demonstration projects will offer room for the early deployment of L4 automated driving in public
transport, goods delivery and municipal services in urban areas.
Use Cases (examples)
The most beneficial applications of automated vehicles in urban area require the ability to drive
autonomously without a driver who must remain alert and ready to take control if the system is unable
to execute the task. One example is Automated Valet Parking, where the real added value comes from
the driver even leaving the vehicle before parking. So the relevant urban use cases are Level 4
applications. Deployment will happen stepwise and according to very defined ODDs (typically low
speed) and infrastructure needs of the specific functionality.
Use cases can be clustered in
• Restricted applications like automated parking, gated areas working with low speed,
• Red carpet use cases on dedicated lanes,
• Residential last mile transport of people and goods,
• Bus(-like) applications on pre-defined routes in mixed traffic and
• Taxi-like operations working on flexible routes in a defined road network.
Vehicle Enablers
Predictive, automated driving requires a situational understanding. The prerequisites for this include,
for example, an understanding of topology, traffic guidance, intentions, road rules, patterns of
behaviour and the interaction between road users.