Feedback | Mobility and Artificial Intelligence: Don’t fall into the trap of continuous innovation

In France, from July 14, 2022, drivers will be allowed to activate Level 3 autonomous driving software, under some strict conditions, to drive without their hands. This amendment testifies to the progress of the artificial intelligence solution applied to mobility, which still stands against a technological wall in spite of everything, especially in securing interaction between vehicles and other road users.

Artificial intelligence should not pave the way for “continuous innovation”

The relaxation of the law in the West is not necessarily good news. This proves that the application of artificial intelligence in the field of mobility is often considered by our decision makers as a “continuous solution”. Emerging legal guidelines thus encourage the adoption of a model based on individual vehicles, which is still responsible for 60.7% emissions from the EU transport sector. It is no wonder that in the United States, a single driving country, about thirty states have already approved autonomous vehicles on open roads.

Although counter-intuitive, the idea that an autonomous electric vehicle will provide a slightly more favorable carbon footprint than just a thermal vehicle is slowly emerging in the scientific community. Indeed, the artificial intelligence application, according to the conclusion of a report conducted in March 2021 by La Fabric Ecological, could generate 1.3 million gigabytes of data and vehicles per year, with which it needs to add carbon footprint associated with construction. Autonomous vehicles loaded with technology. This must be accompanied by a number of indirect effects, such as the durability of the urban expansion model or even the increase in road congestion by increasing the number of buyers, the numerous possibilities (work, read 6) attracted by the possibility of passive driving.

The autonomous vehicle model will be generalized as an individual mode of transport, above all, in the context of the transition to an environmentally sustainable society, quite the opposite. Autosomalism, even autonomous, remains a curse.

Artificial intelligence must be at the service of integrated and shared mobility

In this context, working on factors that support model transitions from cars to public transport, artificial intelligence needs to become a tool in the service of more integrated and shared mobility. As such, it will certainly contribute to making collective mobility safer, more fluid, and more accessible. Which remains within our reach in a relatively short time.

In terms of security, operational applications are thus numerous. In the United States, American company Remark Holdings has actively contributed to reducing the frequency of accidents on the Florida Line Brightline, one of the deadliest rail sections in the United States, thus depriving itself of a large portion of humanitarian aid. In France, Altamtris, an associate of the SNCF Réseau group, uses artificial intelligence as a vector for predictive maintenance, making it possible to avoid dangerous interference, and limiting the impact on train traffic.

In terms of liquidity and accessibility, the development of intermodal solutions – commonly referred to as “”Mobility as a Service “ -, allows the optimization of the use of different modes of transport through digital applications, whose activity is still much higher in the silo, thus becoming one of the priorities for all mobility. Future mobility projects using artificial intelligence do not lag behind and respond to the priority of promoting model transfers from cars to public transport, such as Nancy Urbanloop, making autonomous capsules possible to reach city centers from peri-urban areas.

To make artificial intelligence a tool for environmental and shared mobility, public authorities must provide legal framework guidelines and integrate public investment. And not a tool to perpetuate a model of society whose environmental emergency invites us to come out as soon as possible.

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