Localyse - What does Google offer to traffic professionals

What does Google offer to traffic professionals? (and what’s missing?)

Jelle Draijer Pierre Maere

Before

After

"PUT YOUR' LOCATION DATA TO WORK.

Google Cloud Partner Location Based Services - specialisation

TomTom Partner Here Partner

● We are location data driven ● Team ○

Traffic & Mobility focussed

CASE 1

BRANCHING ANALYSIS

CASE 1: BRANCHING ANALYSIS ● Problem: ○

‘I want to visualize how traffic navigates through the city to identify bottlenecks and cutthrough traffic’.

CASE 1: BRANCHING ANALYSIS ● Problem: ○

‘I want to visualize how traffic navigates through the city to identify bottlenecks and cutthrough traffic’.

● Solution: ○

ODIQ, a Google Maps based platform allowing users to understand traffic flows and congestion depending on time and day.

CASE 1: BRANCHING ANALYSIS ● Problem: ○

‘I want to visualize how traffic navigates through the city to identify bottlenecks and cutthrough traffic’.

● Solution: ○

ODIQ, a Google Maps based platform allowing users to understand traffic flows and congestion depending on time and day.

● Approach: ○

○

Data: ■ Google Maps APIs: real-time traffic data ■ TomTom: historical data Infrastructure: ■ Google Cloud

CASE 2

CITY OF LEUVEN (POLICE DEPT.)

CASE 2: CITY OF LEUVEN (POLICE DEPT.) ● Problem: ○

Excessive speed is a major problem in a city context. However, it is difficult to identify the most problematic locations and to be able to respond to complaints from inhabitants.

CASE 2: CITY OF LEUVEN (POLICE DEPT.) ● Problem: ○

Excessive speed is a major problem in a city context. However, it is difficult to identify the most problematic locations and to be able to respond to complaints from inhabitants.

● Solution: ○

A HERE based platform where the 85th speed percentile is updated on a weekly basis, allowing to easily detect where speed is being exceeded depending on time and day. It allows to detect structural problems and assess the impact of road works or circulation plan

CASE 2: CITY OF LEUVEN (POLICE DEPT.) ● Problem: ○

Excessive speed is a major problem in a city context. However, it is difficult to identify the most problematic locations and to be able to respond to complaints from inhabitants.

● Solution: ○

A HERE based platform where the 85th speed percentile is updated on a weekly basis, allowing to easily detect where speed is being exceeded depending on time and day. It allows to detect structural problems and assess the impact of road works or circulation plan

● Approach: ○

HERE data visualized in a custom developed platform

CASE 2: CITY OF LEUVEN

CASE 3

CITY OF BRUSSELS

CASE 3: DYNAMIC SIGNS TO COMMERCIAL CENTERS ● Problem: ○

The city of Brussels did not have a clear idea where visitors did their shopping and how often. The mode of transport was a question mark as well.. How to boost the number of visitors AND to convince them to do the last mile by foot or bike?

CASE 3: DYNAMIC SIGNS TO COMMERCIAL CENTERS ● Problem: ○

The city of Brussels did not have a clear idea where visitors did their shopping and how often. The mode of transport was a question mark as well.. How to boost the number of visitors AND to convince them to do the last mile by foot or bike?

● Solution: ○

GPS coordinates to identify 50 relevant locations for physical signs with information such as: direction, travel time and length..

CASE 3: DYNAMIC SIGNS TO COMMERCIAL CENTERS ● Problem: ○

The city of Brussels did not have a clear idea where visitors did their shopping and how often. The mode of transport was a question mark as well.. How to boost the number of visitors AND to convince them to do the last mile by foot or bike?

● Solution: ○

GPS coordinates to identify 50 relevant locations for physical signs with information such as: direction, travel time and length..

● Approach: ○ ○

Telecom data to understand the postal code visitors came from depending on the destination, time and day.

Google Maps API’s to determine the routes depending on the mode: car, public transport, bike or by foot.

CASE 4

CONFLICT ANALYSIS

CASE 4: NEAR-ACCIDENT ANALYSIS ● Problem: ○

Unfortunately severe or deadly accidents occur on intersections. Based on gut feeling or short observations, infrastructural changes are made. There’s a need for objective data to convince stakeholders such as inhabitants, other political parties, etc.

CASE 4: NEAR-ACCIDENT ANALYSIS ● Problem: ○

Unfortunately severe or deadly accidents occur on intersections. Based on gut feeling or short observations, infrastructural changes are made. There’s a need for objective data to convince stakeholders such as inhabitants, other political parties, etc.

● Solution: ○

3 to 7 days of video footage to count all traffic, look at turning movements for all modes, violations and (near)-accidents. In a dashboard all incidents can be viewed based on severity. These videos take away all subjectivity.

CASE 4: NEAR-ACCIDENT ANALYSIS ● Problem: ○

Unfortunately severe or deadly accidents occur on intersections. Based on gut feeling or short observations, infrastructural changes are made. There’s a need for objective data to convince stakeholders such as inhabitants, other political parties, etc.

● Solution: ○ ○

3 to 7 days of video footage to count all traffic, look at turning movements for all modes, violations and (near)-accidents, together with partner Idaso.

In a dashboard all incidents can be viewed based on severity. These videos take away all subjectivity.

● Approach: ○ ○ ○

2 cameras are installed during a specific time frame (GPDR compliant!)

All video footage is analyzed and visualized according to severity (Ai).

A consulting firm comes with suggestions to make the intersection safer based on this data.

WRAP UP ●

Which data source fits best with your use-case? > Check for data characteristics ○ high # probes, historical data, speed data, intensity, etc.

●

Combining (big) data sources with ‘local surveys’ ○ Validate ‘gut feelings’

●

Localyse can help you with providing; ○ the data ○ the dashboards ○ ..add value by putting your location data to work.

> ‘..to measure is to know..’

Jelle Draijer jelle.draijer@localyse.eu

Pierre Maere pierre@geomobility.eu

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