Barcelona, September 14, 2017.- The Logistics of the automobile always anticipates technologies that later are integrated in other economic sectors. For this reason, we must be very attentive to the technological advances in the automotive industry. Today we quote an interesting analysis of Business Intelligence, an entity that is defined in these words: BI Intelligence, Business Insider’s premium research service, provides in-depth insight, data, and analysis of everything digital. Our research is fast and nimble, reflecting the speed of change in today’s business. We give you actionable insights that enable smarter and better-informed decision-making. We publish in-depth reports, news, and an exhaustive library of charts and data focusing on key areas of tech: mobile, e-commerce, digital media, payments, the Internet of Things, and more.

Machine Learning Will Enable On-Demand Route Optimization For Deliveries

Route optimization is already a pressing issue for logistics companies and organizations that rely on them to deliver goods. A growing list of companies has already begun adopting more sophisticated technologies to help optimize routes for speed and fuel efficiency. For example, UPS finished the deployment of its ORION route optimization algorithm in the US in late 2016, and is working on expanding its use to international markets.

As on-demand delivery schemes begin to take hold in long-haul trucking and last-mile deliveries, it will force companies to generate more optimized routes more quickly to enable faster pickups and deliveries. That will require instantly aggregating and analyzing a wide range of both historical and real-time data on weather, traffic, and construction delays, as well as historical data regarding demand for pickups and dropoffs.

Using such data, a courier’s route for a late afternoon last-mile package delivery could be redirected through an area where there’s typically high demand for package pickups during that time of day, increasing the likelihood that the courier will pick up an extra package for delivery on the way. This will enable on-demand logistics and delivery providers to deliver more orders more quickly, while also better managing their operational costs.

Platooning Technology Will Take Off In Long-Haul Trucking In The Next 2 years

Automated platooning software — which allows multiple trucks to autonomously follow each other in a closely bunched convoy — will start to make its way into commercial long-haul trucking vehicles in the next year or two. Startup Peloton, for example, is planning a limited commercial release of its platooning solution later this year, with a full launch scheduled for 2018. Several truck manufacturers, including Volvo, also have plans to introduce platooning technologies to their models in the near future.

Once it reaches market, platooning software will see quick uptake within the trucking industry. That’s because it can reduce the single biggest cost for trucking fleets: fuel consumption. By following each other very closely together, platooning trucks face less wind resistance, which boosts their fuel efficiency.

In a test involving a two-truck convoy, Peloton found that its software improved the fuel efficiency of the lead truck by 4.5%, while the rear truck saw a 10% boost. This improved fuel efficiency will increase demand for the technology, as truck operators seek to integrate it across their fleets over the next few years.

Congress Will Pass Self-Driving Car Legislation In The Next Year, But The Actual Rules Will Take Much Longer

Congress will likely pass legislation in the next year that will direct the Department of Transportation to draft regulations for self-driving cars. Both the House and Senate have introduced legislation regarding self-driving technology with bipartisan support, indicating that there’s wide acknowledgement among legislators that this disruptive technology must be addressed quickly.

The House is currently set to debate a bill that would allow the Department of Transportation to exempt specific numbers of autonomous vehicles from federal safety requirements, while also directing the agency to overhaul the nation’s motor vehicle safety standards to account for autonomous technologies. However, regulators will likely take several years to draft those safety standards, even with a push from Congress.

Drafting regulations will require extensive field testing and reaching a consensus among various stakeholders, including car companies and consumer advocacy groups. Right now, the National Highway Traffic and Safety Administration (NHTSA) lacks the staff and resources to conduct this wide-ranging field work and industry outreach in anything less than five years, according to former NHTSA administrator Joan Claybrook.

NHTSA also remains without a director, and it seems unlikely to get much support from the White House, which has let its self-driving car task force fall apart in recent months.

That means NHTSA is unlikely to release real self-driving car regulations before 2020. In the meantime, automakers will have to wrestle with the confusing patchwork of state regulations around self-driving cars that has emerged in recent years. Twenty US states have now passed self-driving car regulations that overlap and sometimes conflict with each other.

That means automakers have to account for all of these various state regulations when building self-driving vehicles, a ponderous task that has stalled innovation. However, the expanded exemptions in the Congressional bill will allow automakers to put far more self-driving cars on the road for testing purposes over the next few years.

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