Self-driving truck facts for kids
A self-driving truck, also known as an autonomous truck or robo-truck, is an application of self-driving technology aiming to create trucks that can operate without human input. Alongside light, medium, and heavy-duty trucks, many companies are developing self-driving technology in semi trucks to automate highway driving in the delivery process.
In September 2022, Guidehouse Insights listed Waymo, Aurora, TuSimple, Gatik, PlusAI, Kodiak Robotics, Daimler Truck, Einride, Locomation, and Embark as the top 10 vendors in automated trucking. And, Transport Topics in November 2022 is listing fourteen companies to know about self-driving truck; Aurora, Waymo, TuSimple, Gatik, Locomation, Torc Robotics, Waabi, Einride, PlusAI, Embark, Kodiak Robotics, Robotic Research, Outrider and Pronto. Self-driving trucks are expected to be on highways in the United States by 2027.
Several government agencies in the U.S. and Europe have announced new legislation surrounding the use of autonomous trucks. Some challenges of bringing self-driving trucks on public roads include, but are not limited to, road safety, the need for human drivers inside the vehicle, and the lack of specific regulations surrounding driverless vehicles.
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Contents
Technology
Sensors
Sensors, such as Lidar, radar, cameras, ultrasonic, and GPS, are crucial to self-driving technology. Due to different sensors performing best at different functions required for autonomous driving and the financial and technological challenges associated with relying on only one sensor, a successful self-driving truck system will likely feature many.
Multi-sensor solutions, such as one manufactured by Continental integrate many pre-calibrated sensors that work synchronously to achieve self-driving features SAE level 4 and above in modern trucks.
Mapping and localization
High-resolution mapping technology, often combined with real-time sensor data, can build and update a detailed map that provides better access to vehicle localization information.
An effective mapping technique for self-driving trucks, such as "sparse" mapping proposed by Kodiak, is built to prioritize information specific to topological, geometric, and semantic highway attributes (in alignment with the challenges often encountered by trucks).
Artificial Intelligence (AI)
Machine learning is a subset of AI that is well-suited to self-driving truck technology as machine learning algorithms allow the vehicle to learn from its environment and past experiences and make attempts to improve its ability to make more accurate and informed decisions about how to operate on the road. Self-driving truck companies like Plus are developing predictive analytic systems to predict potential hazards and risks a truck may encounter and take proactive measures to avoid accidents or other safety issues.
Sensors that measure speed, distance, and distance in combination with a detailed map and an accurate sense of the vehicle's sense of location within that map often provide the input for artificial intelligence systems built to interpret the context.
AI also monitors distance, weather conditions, freight density, truck stop and warehouse density, and autonomous vehicle legislation to generate truck routes.
Humans are thought to be better than modern artificial intelligence systems at interpreting contextual information when put against modern autonomous vehicle systems, but self-driving artificial intelligence systems are expected to improve exponentially in the next decade.
The software and hardware components govern a truck's steering, acceleration, braking, and other critical functions, such as obstacle avoidance and collision detection. Similar to self-driving cars, self-driving trucks may use a combination of GPS, inertial measurement units (IMUs), and other sensors to determine their position and orientation on the road such that it can adjust its movements, turn, make stops, gain directional cues, and make decisions on how to operate.
Economics and Advancements
Market
The trucking industry in the United States annually generates around $740 billion in revenue. In 2021, there was approximately 2.1 million truck drivers in the United States; American truck drivers earn; American truck drivers earn a median annual salary of $48,310.
According to Allied Market Research, the global self-driving truck market may have generated as much as $1 billion in revenue in 2020, and is projected to reach the market size of about $1.7 billion by 2025, growing at a compound annual growth rate of 10.4 percent from 2020 to 2025.
Employment
Economists and policy makers are concerned about the effects of automation and artificial intelligence on employment including whether some kinds of jobs will cease to exist at all, and trucking is the most concerned job. However, Karen Levy is on the view that the path to fully autonomous trucking is likely to be a gradual slope due to social, legal, and cultural factors.
Safety and Regulations
Waymo, formerly the Google Self-Driving Car Project, concluded that self-driving technology could have prevented over half of the fatal automotive collisions within the last ten years. For reference, 4,842 people died in fatal collisions involving trucks in 2020.
In the United States, individual states, such as Nevada, have addressed the regulation of self-driving vehicles (including self-driving trucks) since the 2010s. By 2017, 33 states had promulgated regulations for self-driving vehicles. The National Highway Traffic Safety Administration (NHTSA) issued new federal guidelines in response to the Self Drive Act concerning Automated Driving Systems (ADS) in autonomous cars and trucks. Components of the 2019 NHTSA guidelines include:
- SAE international levels of automation;
- Clarification on testing regulation before public ADS operation;
- Revisions to the safety self-assessment;
- Alignment of federal and state guidelines;
- Clarification on federal and state jurisdiction concerning ADS.
The NHTSA guidelines were revised in 2016 with a primary focus on lowering the number of fatalities from vehicular accidents.
The State of California announced new legislation requiring a human driver to be inside and present on all self-driving vehicles. Besides safety, the motivation for this bill stems from a concern for the trucking workforce. The trucking workforce accounts for 6% of the total U.S. workforce.
In 2022, the European Union worked to develop legislation to legalize the operation of fully self-driving trucks and buses (SAE Level 4). Part of this legislation includes eliminating the requirement for a human driver inside the vehicle.
Germany is the first country in the world to create legal parameters for fully automated cars and trucks in 2021 and 2022.
Challenges
A challenge of self-driving vehicles is identifying liability in collisions, as no driver is present. Furthermore, a challenge with self-driving trucks lies in the regulations and laws surrounding vehicles, such as those that are triggered by a collision. In the U.S., a driver in a crash with a semi-truck may sue the driver and the company to which the driver belongs but not the truck manufacturer. This poses a challenge regarding autonomous trucks as the primary stakeholders, the manufacturers, would not be legally responsible for any collisions. Additionally, the rise of self-driving vehicles may create a need for designated lanes and parking areas, as many roads and cities are not designed for autonomous vehicles.
This expands to the main challenge of the community's safety with autonomous vehicles. A main challenge for autonomous vehicles is the shift from needing a safety driver inside the vehicle. Many car manufacturers are pushing for the shift away from safety drivers to fully deliver on the impact of autonomous vehicles. Until manufacturers can go without safety drivers in the vehicle, there exists a challenge in the premise of autonomous vehicles.
Finally, autonomous vehicles are not currently designed to handle sudden changes in traffic, such as a freeway closure or live collision. While autonomous vehicles can currently switch lanes and enter merging traffic, they are not designed to interpret sudden traffic situations.
See also
