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Hub-to-hub model - low hanging (but sweet) hanging fruit of L5 autonomy.
At Checkturio, we envision being a part of the future where long-haul trucks autonomously navigate vast distances, propelled by technology rather than the constraints of human endurance. In this landscape, we believe that self-driving 40-ton vehicles will only be widely accepted when they are supported by thorough, independent vehicle monitoring, utilizing the appropriate processes and tools
The question is how far are we from that future?
The autonomous truck company Torc Robotics presents a focused, albeit limited, vision of the first step in freight autonomy: the hub-to-hub model. Troc calls this the 'safest, most scalable form of autonomous trucking.' This strategic emphasis on a simpler aspect of autonomous driving, though less intricate than the bustling chaos of urban environments, holds significant commercial value. Perfecting this model could be a crucial steppingstone to broader applications in autonomous transportation. Torc's approach highlights smart adaptation to the specific demands of long-distance trucking, where strategic choices are as vital as technical innovation.
I agree with this vision. Waymo's recent success in navigating millions of miles through complex urban landscapes like San Francisco and Phoenix exemplifies the potential to overcome the challenges of autonomous driving. Their triumph in these densely populated areas, replete with numerous obstacles, contrasts sharply with the less complicated hub-to-hub model on highways. In the highway context, the lack of urban complexities such as dense traffic and unpredictable conditions signals a more straightforward challenge. Therefore, Waymo's expertise in complex urban settings strongly indicates that the simpler hub-to-hub model is not only achievable but also more straightforward to implement and accept. This has been further demonstrated by multiple pilots executed by companies like Aurora, Torc, and Einride in collaboration with leading OEMs such as Volvo, Scania, and Daimler.
Feasibility and Profitability
The road freight market is valued at €380 billion in Europe and nearly $900 billion in the US, significantly overshadowing the US taxi and ride hailing services market, worth about $70 billion. This prompts the question: Are autonomous driving companies like Waymo and Cruise targeting a highly lucrative market?
Robotaxis primarily offer labor cost reductions, but long-haul deliveries promise threefold benefits: decreased labor costs, enhanced supply chain efficiency (quicker deliveries), and improved asset utilization. The safety and environmental impacts are noteworthy and warrant further discussion.
Currently, 60% of all road freight transportation in the EU consists of mid and long-haul drives (over 300km), making this segment of the market worth around €200 billion. In the US, it is estimated at $250 billion. Together, these two markets alone make long-haul transportation worth approximately €430 billion.
Labor Costs
Automation first and foremost promises savings in labor costs, the most straightforward and easiest to estimate component. Labor costs represent about one-third of the freight industry's expenses in the US, according to ATRI. This suggests potential annual savings of €140 billion (before accounting for hub and last mile operation costs) across the US and EU.
Enhanced Asset Utilization and Capital Cost Savings
Currently, truck efficiency is limited by drivers' biological constraints and regulations. In the EU, the driving time limit is 48 hours per week. US regulations are less stringent, but considering human limitations, we can optimistically assume that truck utilization is less than 40%. Doubling the utilization of semi-trailer tractors could halve the capital intensity of this freight market segment. Assuming an average cost of a truck trailer at €120,000, with 2.8 million tractor trailers in operation, and factoring in a 20% cost for self-driving equipment and a 5% capital cost, annual savings in the EU could be around €13.5 billion. A similar figure is expected in the US, leading to total additional savings of €27 billion.
Supply Chain Efficiency
Shorter delivery times have a significant but hard-to-quantify impact. They not only reduce inventory costs and free up capital but also open new markets by enabling sourcing from more distant regions. A conservative estimate of a 5% increase in vendors' willingness to pay due to faster deliveries suggests an additional €20 billion in revenue for the road freight industry.
Ecology and Fuel Costs
Highway driving is inherently efficient. For example, in Europe, the low-speed limit for trucks (80 km/h) leads to minimal speed variation, a key factor affecting fuel consumption on highways. In the US, where there is more speed variation, the impact could be more pronounced. However, self-driving trucks must maintain speeds comparable to other road users to be accepted. One area where fuel savings are achievable with self-driving trucks is "platooning" – driving trucks in closely spaced convoys. This can yield fuel savings of up to 17% for the middle truck in a platoon. With conservative estimates factoring in marginal savings from driving style and platooning, the fuel savings could amount to around €7 billion (EU + US) and a reduction of approximately 11 million tons of CO2 emissions (assuming 57g CO2 per tone-km).
Drivers' Quality of Life
The impact of automation on drivers' quality of life is multifaceted. While some driving jobs might be replaced, new opportunities will emerge at hubs. Long-haul driving is strenuous, both physically and mentally, and these positions are often difficult to fill.
Costs
Hardware
Autonomous trucks require a premium investment. Most companies do not publish their pricelists, so we must rely on estimates. The costliest component, LiDAR, is becoming more affordable. Estimates of the additional hardware costs are around €30,000.
Hubs
Hubs are essential for the hub-to-hub model. While they represent an investment, two silver linings exist: fulfillment centers are typically located near highways, and the need for hubs will reduce the demand for truck parking areas where drivers take mandatory breaks (in both the EU and US).
Safety 1st – vehicle inspections in autonomous future
Safety remains a crucial concern. Although incidents involving heavy trucks on highways are relatively rare, enhancing their safety is still vital. By eliminating the human factor and employing rigorous inspection processes, we can further improve highway safety. Ensuring the safe operation of these 40-ton giants on our roads will be a priority in the journey towards automation.
Safety is paramount for the acceptance of self-driving trucks. Equipping them with LiDAR, radars, cameras, and HD maps is the baseline for a safe, robust, and reliable solution. Regular and thorough inspections and monitoring, on the other hand, must be performed to ensure an airline-like industry safety record.
This is why Checkturio already offers flexible inspection software today, allowing for the integrated multimodal inspection of vehicles – not only by a mechanic or driver, but also integrating with automated data collection systems. This data feeds into our predictive maintenance system, enabling us to anticipate the risk of malfunctions and allowing mechanics to act before these occur.
In the unfortunate case of an accident, this independently collected and processed data can be crucial in the claim management process.
To discuss how we can ensure reliable and safe operations of your fleet, whether you view the road through the lenses of a LiDAR or prescription glasses, please contact us.