Autonomous Inertia Estimation for Transportation

Ref-Nr: TD001

Technology abstract

Using previous experience from the Space context allied with knowledge on Transportation Systems, a Portuguese company developed a solution for High Occupancy Vehicles (HOV) application. This solution provides the technological means to classify vehicles as HOV and it can be easily integrated in existing tolling systems. We are looking for partners in integrating this solution either on existing HOV or tolling systems or in cars in communication with road management systems.

In the frame of ESA projects, GMVIS have developed algorithms for the on-board identification of the mass (M), Center of Gravity (CoG) and inertia (I) characteristics of space vehicles. These three aspects are well-known in literature as MCI and we have applied it to the Lunar Lander and Mars Sample Return missions. Inertia features of a space vehicle are known before the vehicle launch and normally change during the mission.

- Carlos Cerqueira -

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Technology Description

Congestion is a major problem in many highways and multilane roads nearby major cities in Europe and worldwide. Reduction of that congestion and, in general, a major efficiency in traffic strongly recommends that vehicles are shared by more than one passenger. Authorities promote the High Occupancy Vehicles (HOV) either facilitating the use of dedicated lanes or having reduced tariffs when using tolled highways.
This solution provides the technological means to classify vehicles as HOV and it can be easily integrated in existing tolling systems, as it is based on Stand Alone Technology and it can run on existing processors or deployed following a “System on chip” (SoC) philosophy.
This specific technology comes from the need for the autonomous estimation of spacecraft inertia characteristics in the aerospace domain, namely: the vehicle mass, centre of mass position and inertia (MCI).
This technology is a key aspect in the control of a spacecraft and its performance has a direct impact on the optimisation of the available resources. The more accurate the estimation of these parameters, the more optimised the selection of the manoeuvres to be conducted and their characteristics.

Innovations & Advantages

This technology brings three main advantages when compared with the current systems for HOV identification, which are mainly vision-based.
Firstly it is more reliable as it is harder to deceive (current systems are being deceived by placing dolls in the car to pass as passengers) and it is tailored to the car’s characteristics after a short calibration.
Secondly, this technology can be self-standing, not necessarily integrated with the vehicle’s sensors. This allows just placing a black box onto the car and starting using it.
Thirdly, it is very user friendly since it is transparent to the user, who does not need to have any knowledge on the technology running inside and it can be deployed in existing processors.

Further Information

This technology has been demonstrated in two different scenarios.
In the HOV application, the solution was able to identify all HOV scenarios correctly, in an operational environment.
As for the counting and classification of the number of passengers, the application was correct in over 95% of the tests conducted so far, showing very promising results.
All tests were conducted with two different car models.

Current and Potential Domains of Application

Congestion is a major problem in many highways and multilane roads nearby major cities in Europe and worldwide. Reduction of that congestion and, in general, a major efficiency in traffic strongly recommends that vehicles are shared by more than one passenger. Authorities promote the High Occupancy Vehicles (HOV) either facilitating the use of dedicated lanes or having reduced tariffs when using tolled highways.
This solution is based on Stand Alone Technology and provides the technological means to classify vehicles as HOV.
A by-product of this solution is that the number of passengers is also estimated along with some classification, such as adult/ children.
As a consequence, the potential domains of application are tremendous and can range from support to traffic congestion management to any equipment that could take advantage of the knowledge of its inertia features.