Projects - Orange Traffic

Modernizing Origin-Destination Transportation Modeling Through Floating Car Data

Written by Test | Jun 15, 2026 7:59:55 PM

To support transportation planning and mobility modeling across Québec, the ministère des Transports et de la Mobilité durable (MTMD) mandated the development of large-scale origin-destination (O-D) matrices using anonymized floating car data (FCD) .

Through a collaboration between Orange Traffic’s Innovation Mi8 division and SMATS Traffic Solutions, the project leveraged a cloud-based analytics platforms and advanced processing methodologies to produce detailed vehicular movement patterns across four major Québec regions using FCD:

  • Montréal
  • Québec
  • Sherbrooke
  • Trois-Rivières

The initiative demonstrated how FCD can complement and modernize conventional transportation modeling approaches while providing broader network visibility, improved scalability and enhanced operational intelligence.

The Challenge

Traditional origin-destination surveys remain essential for transportation modeling, but they present several limitations:

  • Limited visibility on peripheral and transit movements
  • Reduced understanding of commercial vehicle patterns
  • High operational complexity and cost
  • Limited scalability for continuous monitoring

The MTMD sought a more comprehensive and data-driven approach capable of capturing:

  • Internal and external trip patterns
  • Regional and interregional vehicular flows
  • Commercial vehicle movements
  • Hourly origin-destination demand across large territories

In addition, the solution needed to support transportation modeling efforts for future infrastructure and mobility planning initiatives.



The Solution

The solution combined:

  • SMATS’ iNode mobility analytics platform
  • TomTom agregated FCD for passenger vehicles
  • Geotab / Altitude FCD for commercial vehicles
  • Advanced map-matching and trip reconstruction methodologies

Across the four territories, hundreds of internal zones and peripheral gateways were analyzed to reconstruct large-scale mobility patterns. The solution enabled the production of detailed O-D matrices by:

  • Region
  • Hour of day
  • Vehicle category
  • Origin and destination zone

Technology & Methodology

The solution relied on anonymized mobility datasets collected from:

  • Connected vehicles
  • GPS systems
  • Mobile applications
  • Commercial fleet telematics

SMATS’ iNode platform processed passenger vehicle mobility data while Geotab Altitude supported truck movement analytics.

Key analytical processes included:

  • GPS trace processing
  • Map-matching to the road network
  • Trip segmentation
  • Origin-destination pairing
  • Vehicle classification
  • Statistical validation

The methodology enabled the creation of:

  • 24-hour O-D matrices
  • Passenger vehicle matrices
  • Truck movement matrices
  • Regional flow analysis
  • Peripheral gateway movement analysis

Key Benefits

Province-Scale Mobility Visibility

The project provided a macro-level understanding of vehicular flows across four major Québec regions.

Enhanced Transportation Modeling

The generated O-D matrices complemented conventional household surveys and improved transportation simulation capabilities.

Commercial Vehicle Intelligence

Unlike traditional surveys, the methodology incorporated truck movement analytics using commercial fleet data.

Scalable & Cost-Efficient Data Collection

The use of FCD reduced the need for extensive physical field data collection infrastructure.

Continuous & Flexible Analytics

The platform-based approach enables repeatable and scalable mobility analysis for future transportation initiatives.

Results

The project successfully delivered:

  • Origin-destination matrices for four Québec urban regions
  • Passenger vehicle and truck movement analytics
  • Hourly traffic flow intelligence
  • Peripheral gateway movement analysis
  • Large-scale mobility pattern visibility for transportation planning

The initiative also demonstrated the operational viability of mobility big data as a complementary tool for transportation modeling and infrastructure planning.

Strategic Impact

This project highlights how intelligent mobility analytics can support transportation agencies in:

  • Modernizing transportation planning
  • Improving infrastructure decision-making
  • Better understanding regional mobility behavior
  • Enhancing long-term transportation simulation models
  • Supporting data-driven mobility strategies

Through its collaboration with SMATS, Orange Traffic continues to expand its expertise in intelligent transportation systems, mobility analytics and real-time transportation intelligence solutions.

Partners

Orange Traffic / Innovation Mi8

Turnkey intelligent transportation and mobility analytics solutions provider specializing in real-time traffic intelligence, monitoring and transportation innovation.

SMATS Traffic Solutions

Advanced mobility analytics provider specializing in probe vehicle data processing, transportation intelligence and cloud-based traffic analytics platforms.