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

• Synthesize

• 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.