Siemens ITS Digital Lab User Manual

Enhance Data
Infrastructure: traffic controllers, detection
Parking Predictions as
Enhance Data
Infrastructure: traffic controllers, detection
Fleet data: connected vehicles, e-bikes, public transportation, transit schedules
Parking Predictions as a Service
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
Parking Predictions as a Service
Eventful: Event Popularity Prediction
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
Generate Value
See: data preparation and visualization
Parking Predictions as a Service
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Crash Hot Spots
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
Generate Value
See: data preparation and visualization
Understand: descriptive and predictive analytics
Parking Predictions as a Service
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Crash Hot Spots
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
Generate Value
See: data preparation and visualization
Understand: descriptive and predictive analytics
Act: recommendations for action and operations
Parking Predictions as a Service
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Crash Hot Spots
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
Generate Value
See: data preparation and visualization
Understand: descriptive and predictive analytics
Act: recommendations for action and operations
Shaped by innovation
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 Investigate Ideate Experience Develop
• Pain points
• Challenges
Problem definition User journey Vision of solution First concrete “notion“
• Follow user
• Conduct interviews
http://siemens.com/digitallab
• Prioritize
• Follow customer/ user through proposed solution
of solution
Operative pilot: Minimum
• Rapid prototyping along defined milestones
Viable Product (MVP)
Parking Predictions
Parking Predictions as a Service
Parking Predictions as a Service
Eventful: Event Popularity Prediction
Parking Predictions as a Service
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Parking Predictions as a Service
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Crash Hot Spots
The ITS Digital Lab works with its customers to create software tools to improve accessibility, predictability and enhancement of mobility ecosystems.
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
• Use AI to predict availability 24 hours in advance
• Open interfaces enable compatibility with third-party systems
• Cloud-based Parking Predictions as a Service (PaaS) platform enables easy access
Benefits
• Reduces driver’s stress from searching for a parking spot
• Increases revenue from unused parking spots
• Enables dynamic pricing strategies
• Reduces vehicle emissions
Eventful: Event Popularity Prediction
ITS Data Hub: Traffic Data as a Service
Crash Hotspots Identifier
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
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
Issues
• Accident-prone sites cause injuries and traffic-related issues
• Impact can be far reaching and life-changing for those involved
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
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
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
• 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
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
Benefits
• Fewer accidents in high-volume locations
• Better, more automated response plans increase safety
• Improved life safety for passengers and pedestrians
http://siemens.com/digitallab
Siemens Mobility–ITS
9225 Bee Caves Road Building B – Suite 101 Austin, TX. 78733
© 2020 Siemens Mobility, Inc.
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