Driver and technician shortage has emerged as the most important top-of-mind issue for fleet managers. This, coupled with concerns on economic outlook and operating margins, is predicating several choices that fleet managers are making with regards to advanced truck technologies. Potential benefits of safety, technology and lower operating costs will spur growth of autonomous trucking given issues to be resolved over liability, regulations and labor. Fleets involved in crashes are facing high-dollar jury verdicts currently with worsening severity of jury awards; in addition to this, safety profile of a fleet is focused more in a crash case than specifics of the accident. Access to data from safety systems will protect fleets from false claims and also aid in reducing insurance premiums owing to lower risk of accidents. Therefore, increased opportunities exist for prospective industry participants in integrating safety and fuel efficiency benefits across various technology platforms. Performing real-time computing for advanced safety technologies’ sensor data input will require sophisticated and reliable hardware platform with sufficient high performance computing abilities; cloud platform is expected to aid in functionalities such as distributed computing and distributed storage for deep learning model training and HD map production.
The technical challenges of autonomous systems, in addition to the need for all digital components to communicate with each other continuously are expected to create gaps in the market for Tier 1 suppliers and semiconductor companies. Moreover, unfiltered, unbiased raw data will be preferred over traditional distributed processing in the future owing to the enhanced ability of the model to generate a complete view of the truck’s environment through centralized processing. In the domain of in-vehicle networks, the demand for connectivity will force OEMs to look into new network technology such as Ethernet that can handle quick, large-volume, high-speed data transmissions to enable effective coordinated control across multiple functional domains in autonomous trucks. The inclusion of crash mitigating technologies and onboard cameras as standard features in trucks is expected to significantly reduce risk of collision, thereby reducing premiums. While insurance premium parameters are largely calculated based on fleet- or driver-related data, vehicle-related data such as autonomous driving algorithms, cybersecurity, and logic robustness are expected to feature in the calculations; liability for crashes is expected to shift to truck manufacturers.
The aim of this research service is to provide a strategic overview of the heavy-duty truck safety technologies enabling autonomous driving, including analysis of key market trends, and technology trends, and integration of electronic architecture for autonomous driving.