Why autonomous trucks are carrying serious weight
- Mergers and acquisitions continue to propel the self-driving truck industry towards more widespread realization
- Firms are navigating the right combination of complex sensor and data technologies, with some claiming ‘in general, the simpler the better’
- The full impact on policy, supply chains, and drivers remains to be seen, but there are significant considerations required at every step of development
Volkswagen’s heavy-truck business – The Traton Group – took a minority stake in TuSimple this week. Their agreement marks plans to launch a development program that will use Traton’s Scania trucks equipped with TuSimple’s automated vehicle technology. The companies will run testing on a route in Sweden, with a view to expediting the rollout and widespread use of driverless truck fleets on roads throughout Scandinavia, Germany, and other countries.
The aim is Level 4 autonomy, meaning full automation without human intervention under “defined driving conditions and applied in all markets.”
The partnership – which sees TuSimple expand its autonomous vehicle operations beyond the US and China to Europe – also furthers both companies’ connection with commercial trucking powerhouses Navistar International. And favoring purpose-built machines over the retrofitting of existing fleets, the newly-formed trifecta ups of ante in the now hotly-competitive race to bring autonomous trucks into real-world deployment.
The race is on to meet demand for autonomous trucks
Since 2013, venture capital investment in trucking and logistics-related technologies have soared from just over US$100 million to what, in 2020, seems to set surpass US$2 billion. The innovation associated with autonomy – and the fabled self-driving truck, above all – has attracted the most interest. Their proponents point to perks around delivery times, costs, and the counteracting of a truck driver shortage.
With 65% of consumable goods in the US trucked to market, a report by McKinsey & Company said autonomous trucks would change the cost structure and utilization of trucking. This is compounded by ever-greater pressure from e-commerce. Automation at every point in the supply chain is proving vital to cope with demand— autonomous trucks are estimated to save 45% in operating costs (between US$85 billion and US$125 billion) for the US for-hire trucking industry. The fledgling industry is attracting the keen interest and convergence of a strange combination of cutting-edge start-ups and age-old, well-oiled stalwarts.
Back in ’17, Elon Musk rolled out Tesla’s fully electric semi-truck, capable of 500 miles between charges and 80,000 pounds in carrying capacity. Every step of the way, its Autopilot technology has been developed, nudged, and rivaled by a smorgasbord of competitors, one of which – Nikola – has claimed Tesla’s creation infringes its own patents.
Last year, Daimler bought autonomous vehicle firm Torc Robotics, acquiring “advanced, road-ready technology” for level 4 autonomous driving, while last year, Plus.AI conducted the first real-world commercial freight delivery by a self-driving truck, carrying 40,000 pounds of Land O’Lakes butter in a three-day trip across the United States.
What will change?
For starters, as the race for autonomous trucking passes the finishing line, and all starters are joined by more and more competitors, daily operating times will increase.
This necessitates the surrounding supply chain to shift, expand, and mold to new reality of operation. Such a shift will be incremental, and won’t be seamless. Companies working in logistics and dealing with goods across the supply chain will need to put a renewed onus on flexibility and around-the-clock operations, which is no mean feat.
Ultimately, capturing economic gains from autonomy requires mastering an (almost) entirely new set of processes and systems, designed to keep vehicles rolling in a manner that not only assures safety – for any inefficiency will be exposed and scrutinized – but also provides a positive return on investment. Over time, we would expect to see a more balanced utilization of routes, as well as a reduction in mixed traffic and commuter congestion. If the technology is nailed, then peak hours of travel can be circumnavigated to provide greater assurance on cargo arrival times, partnered with improved safety of fellow road-users.
Then there are the drivers. Though decreasing in popularity (and increasing in attrition), truck driving has historically proven a steady and widely viable job for blue-collar workers the world over. Losing these jobs – or even seeing them jeopardized – could devastate job prospects for relatively unskilled workers. Goldman Sachs economists predict that the growing trend of autonomous vehicles could cost up to 300,000 jobs a year across all driving industries.
As a promising inverse to the above, the slow diffusion of autonomous technology throughout countries – and the world – will leave ample time for operational optimization and monitoring of economic impact and job prospects. It won’t be a mass-job-loss overnight scenario, and new opportunities will inevitably arise across the supply chain as the traditional driving gig wanes.
Amongst governments and policy-makers, there are (and when you consider the above, understandably so) a multitude of opinions and takes on the future of autonomous vehicles. Debate across this spectrum of acceptance will likely consume considerable time, and place blocks in the road for autonomous vehicle firms.
And despite the competition in the market, the need for data sharing will only increase, as will common analytical tools. Being insular with information may serve the host company well, but doubtlessly plays fast and loose with the human lives around these autonomous machines. Time-series, machine learning, and AI will all contribute to a perpetual drive in efficiency. The race to get autonomous trucks on the road will soon play second fiddle to the race to maintain their forward motion through continuously optimized analytics.
This is why the car and truck manufacturers leading the self-driving vehicle “revolution” – including the newly formed Traton and TuSimple partnership –have significant R&D and analytics departments. Autonomous technology, operations, and policies are on an upward trajectory, and we will soon see more vividly how their application impacts supply chains and human factors.
Navigating the nuances of autonomy
Stefan Seltz-Axmacher, CEO of Starsky Robotics, claimed that ‘when it comes to safety engineering, in general, simpler is better’. His firm is aiming to put technology into everyday use and to have 5-50 autonomous trucks next year. Though in their relative infancy, autonomous trucking systems – the cameras, radars, and sensors used to determine distance, the scheduling of breaks in line with local laws – are pretty far along the road as is.
That said, with autonomy tied closely to safety, many businesses are, Seltz-Axhmacher argues, over-complicating the logistical elements of their technologies. The maintenance and sustainability of new transportation tech is vital to the success of autonomous vehicles (as much, if not more so, than the initial development and implementation of such solutions).
In short, the coming years will be tricky to navigate. No one company or conglomerate (Volkswagen/TuSimple included) is preaching the case of being cavalier, but too many bells, whistles, and fine-tuned, nit-picking, overlapping technologies may only serve to a) delay the benefits of autonomous transport, and b) leave systems susceptible to internal confusion and errors.
It’s an exciting time for transport, but the road ahead is complex, and a holistic view of autonomy’s potential is vital to its safe implementation.