AUTOMATING TOLL CLASSIFICATION CONTROL
WITH ARTIFICIAL INTELLIGENCE

Tollsense is an AI-powered image processing software, able to detect in real time the class of a vehicle at the toll plaza, from a unique image feed and with a very high level of accuracy

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Relieving toll operators of classification errors

Despite the high number of equipment already set up at the toll plaza (optical radars and other lasers), 5 to 10% of toll transactions are still commonly manually reprocessed  by operators: a tedious and time-consuming process, expensive for tolling operators and generating numerous errors.

Based on the latest Deep Learning technologies and trained on 101 million images, Tollsense automatically detects the class of vehicles at toll booths with the same performance as a classification expert.

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WHY TOLLSENSE?

Operational efficiency

By eliminating the manual reprocessing of classification errors, operators immediately
gain in productivity: great impact on toll function ROI.

Improved
customer service

Thanks to the reduction in intercom customer calls, toll lanes are more fluid and customers more satisfied (decrease in customer claims).

Ready to scale

Tollsense is already deployed at an industrial level throughout the VINCI Autoroutes network.
It is the only AI product to have been deployed at scale in France in 2018.

Privacy-by-design

With our anonymization technology, we respect user confidentiality by blurring personal data visible on the images we process (GDPR compliant).

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PRODUCT FUNCTIONALITIES

DEDICATED interface

Management and analysis tools for supervision, easy to learn by operators (simple and intuitive interface)

quality control

A confidence rate is assigned to each response, that can be used as a filter to ensure a specific level of reliability

real-time

The API responds in less than 250 ms (cloud or on-premise processing), allowing the solution to be integrated directly in the toll IT system

flexible integration

A single API, easy to integrate into your toll systems: directly into the lane software or in your back-office, without any equipment costs

KEY FIGURES

101 million

classified vehicules

4 months

of R&D

> 99%

performance

< 250 ms

processing time

OUR REFERENCES

4 443 km network

320 toll plazas

880 M transactions / year

TOLLSENSE FOR VINCI AUTOROUTES 

PROJECT MANAGER

VINCI Autoroutes Toll Division

YEAR

2018 - 2019

BEFORE TOLLSENSE

54 300 hours per year of manual reprocessing
35% of a toll operator’s working time

AREA COVERED

After only 4 months of R&D, Tollsense was deployed at scale throughout the network for all class 2 and 5 checks, directly into the business qualification tool.

KEY FIGURES

101 M

transactions processed
so far

80%

of the manual reprocessing
workload removed

2.5 M€

yearly savings
for toll operators

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A PERFORMANCE-DRIVEN METHODOLOGY

Our Tollsense algorithm has reached unprecedented performance levels: trained on over 101 million images, it integrates almost all rare cases. It can easily be adapted according the specific needs of each client, to reach a tremendous performance:

Labelled dataSETS

The first step in any development consists of setting up a set of “labelled” data, meaning data correctly annotated with their classification outcome.

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AN AI MODEL

Using this labelled dataset, the model is then trained to study the relationship between image properties and the annotated result.

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ACCELERATING PERFORMANCE

Deep Learning enables the algorithm to self-learn and continuously improve. Thus, the more data is provided, the more accurate the model is and the more accustomed it is to recognizing complex cases such as snow, trucks, trailers, etc.

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INDUSTRIALLY DEPLOYED

Once the solution reaches the required performance level, the classification algorithm can then be deployed in production on the network. This can be done via integration in back office or directly on the toll lane.

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TOLLSENSE EVOLUTIONS

TRAFFIC DATA

Real-time vehicles classification via video analysis, for a better knowledge of your traffic

FREE FLOW

Revolutionizing tolling by providing a camera-based-only Free Flow gantry, at a lower cost