Siemens ITS Digital Lab
AI and machine learning applications solve mobility challenges
Experts at Siemens visionary Intelligent Traffic Systems (ITS) Digital Lab use artificial intelligence and machine learning to develop new applications that help cities unravel even their toughest mobility problems.
Turning data into action
The intelligent use of data collected by the city, its vendors and third parties is at the heart of these state-of-the-art applications. Digital Lab analytical experts gather and enhance all pertinent data so that it generates real value.
Enhance Data
Infrastructure: traffic controllers, detection
Fleet data: connected vehicles, e-bikes, public transportation, transit schedules
Third-party data: probe car data, weather data, events, police reports
Shaped by innovation
Generate Value
See: data preparation and visualization
Understand: descriptive and predictive analytics
Act: recommendations for action and operations
Applications are created by collaborating with city departments in an agile rapid innovation process that leads to quick results for real-world mobility challenges.
Learn |
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Develop |
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Pain points |
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Follow user |
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Synthesize |
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Challenges |
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Conduct interviews |
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Prioritize |
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user through |
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along defined |
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proposed solution |
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Problem definition |
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User journey |
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Vision of solution |
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First concrete “notion“ |
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Operative pilot: Minimum |
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of solution |
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Viable Product (MVP) |
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http://siemens.com/digitallab
The ITS Digital Lab works with its customers to create software tools to improve accessibility, predictability and enhancement of mobility ecosystems.
Parking Predictions
as a Service
Issues
•Uncertainty about parking availability for commercial and passenger transport, including trucks, electric vehicles, shared and personal vehicles
•Search for parking creates traffic congestion and
air pollution
Solution |
Benefits |
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• Use AI to predict availability |
• Reduces driver’s stress from |
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24 hours in advance |
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searching for a parking spot |
• Open interfaces enable compatibility |
• Increases revenue from unused |
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with third-party systems |
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parking spots |
• Cloud-based Parking Predictions as |
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Enables dynamic pricing |
a Service (PaaS) platform enables |
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strategies |
easy access |
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Reduces vehicle emissions |
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Eventful: Event
Popularity Prediction
Issues
•Lack of information about location of popular unofficial events
•Unforeseen demand causes overcrowding, congestion and increases journey times
•Potential additional transit ridership and revenue lost to ride-sharing services
Solution
•Use AI to automatically identify unofficial events, predict popularity
•Map popular events against public transit options for proactive planning
•Use predicted event data for traffic signal planning and sign changes
•Make recommendations for on-demand transit services
Benefits
•Eliminates need for manual tracking of unofficial, popular events
•Enables proactive planning of traffic and transit services, including modified or additional transit services
•Increases ridership and captures revenues lost to ride sharing
ITS Data Hub: Traffic
Data as a Service
Issues
•Data exists across multiple systems and infrastructure
•Disconnected data difficult to fully utilize or share with vendors
•Lack of standardization and open interfaces in mobility industry
Solution
•Cloud-based Traffic Data as a Service (DaaS) platform that is vendor-agnostic
•Enables open APIs for data exchange between city and suppliers, including controller configuration and SPM
•Modern system architecture pattern is robust, scalable and enables security by design from day one
Benefits
•Allows easy data sharing with third-party vendors
•Reduces total cost of using traffic data
•Scalable, vendor-agnostic system reduces long-term investment
•Enables potential new business model enabled by traffic and transit data commercialization
Crash Hotspots
Identifier
Issues
•Accident-prone sites cause injuries and traffic-related issues
•Impact can be far reaching and life-changing for those involved
Solution
•Predict crash hotspots using data from police and incident reports
•Recommend prevention plans and countermeasures
•Integrate into automated response plans for signal timing changes, signs and messaging actions
Benefits
•Fewer accidents in high-volume locations
•Better, more automated response plans increase safety
•Improved life safety for passengers and pedestrians
Siemens Mobility–ITS
9225 Bee Caves Road
Building B – Suite 101
Austin, TX. 78733
http://siemens.com/digitallab |
© 2020 Siemens Mobility, Inc. |