Vehicle automation technology is about to change how people and goods are transported. While autonomous cars are generally the focus of attention, long-haul trucks offer one of the most compelling use cases for self-driving vehicles.
The objective of this thesis is to derive recommendations for fleet operators/owners regarding the adoption of increasingly automated long-haul trucks. Hence, this research should include the following elements:
1. A technology overview with (a) the clarification of SAE levels and operational design domains (ODD), (b) an overview of advanced driver assistance systems (ADAS) / automated driving (AD) functions, incl. high-level assessment of technical maturity, and (c) an overview of the technical implementation, i.a., sensor sets, incl. cost estimations
2. A market analysis with (a) the description of potential customers and the corresponding value proposition (customer mix, operation models, TCO analysis for fleet operators, lack of drivers, rest time, equipment cost), (b) a competitor benchmark including truck OEMs and emerging startups, amongst others, and (c) an overview of the regulatory landscape with particular focus on the EU
3. A market outlook to extrapolate the previous findings by deriving and discussing (a) a technology roadmap, i.e., which ADAS/AD functions will likely appear when in the truck market and (b) a market sales forecast by SAE level in the EU
4. Derived recommendations to fleet operators/owners, e.g., regarding the choice of a particular technology (e.g., specific sensor set), its ideal moment of acquisition, its optimal use case (e.g., category of routes), the necessary restructuring of the business, etc.