Future mobility systems with self-driving vehicles
The Siemens SDV Suite: a systemic approach for autonomous driving supported by intelligent infrastructure
Mobility systems will be disrupted by autonomous vehicles maintaining and enhancing individual mobility options while expanding public transportation options. We call this an optimized transport system supported by self-driving vehicles. Benefits will include overall optimization of the transportation system, fewer vehicles on the road, improved traffic flow and better mobility access while reducing air pollution and guaranteeing increased safety.
The level of complexity and automation of transportation systems increases significantlyToday, transportation accounts for about 25 percent of the world’s primary energy consumption and around 20 percent of the global CO2 emissions. Inadequate transportation can reduce a city’s productivity (measured in GDP) by up to 30 percent, recent studies show. An optimized transportation system supported by self-driving vehicles will enhance mobility access through feeders or complement public transportation. It will improve the flow of the traffic as a result of fewer accidents and less congestion.
- Connected, intermodal, seamless travel
- SAE [Society of Automotive Engineers] Level 5 – no driver needed
- Integration of system relevant topics, such as fleet management, charging, security and infrastructure management
- Mobility as a service with intermodal routing
- Fully electric - zero CO2 emissions
- New mobility concepts - no driver, modular vehicle approach for people and goods
- Customer focus that facilitates new business models
Siemens systemic solution architecture is composed of intelligent infrastructure at the field level, consisting of components such as the Siemens Sitraffic ESCoS road site unit, lidar and radar sensors. From a software point of view, micro-services in the cloud manage the system and the actual passenger experience. Passenger services include intermodal routing and an enhanced travel information experience. Additionally, the open platform approach allows for flexible, demand-oriented integration of all kinds of autonomous vehicles.
Solving the first/last mile
Efficiency will be ensured because overcoming first/last mile issues with intermodal routing across all connected transportation modes will lead to shorter travel times and a higher level of connectivity – even in rural areas.
Adverse weather conditions
The sensors on the field level will work reliably, even during changing weather and light conditions, e.g., rain, snow, fog or glaring sunlight.
Protection of vulnerable road users
Pedestrians and cyclists in crossroad areas will be detected by sensors as they walk on sidewalks, travel down cycling paths and cross streets. Road users will receive real-time information about potentially hazardous situations.
The infrastructure will help identify potential risks, even if they are not in the vehicle’s immediate surroundings. The infrastructure will support the vehicle with expanded environment recognition. The vehicle will reduce its speed early to avoid critical situations.
Overall traffic optimization
Flexible on demand public transportation
Micro-services will manage passenger demand, collect incoming requests and calculate individual transportation recommendations. Vehicles of different sizes will carry passengers from a public transportation station to their destination. Passengers will receive their route planning, timetable and ticketing by using a mobile app.
Autonomous valet parking
The passenger in the autonomous vehicle will drop off the vehicle at a barrier and purchase a ticket via a mobile app. The infrastructure within the parking garage will guide the vehicle autonomously to a parking space.
Higher utilization of vehicles
The actual land usage will be minimized as the overall number of vehicles declines. The system will allow for maximum fleet utilization. How? By employing modularly constructed vehicles that can be used for both people and goods, among other things.