| Summary: | The automotive industry is undergoing radical changes due to increased focus on electrification, automation, and ride sharing. Several OEMs and technology startups are making significant advances in autonomous technologies to enable driverless operations. Long haul trucking/ freight applications are expected to see the deployment of autonomous technologies before they are deployed in consumer cars given the deterministic operational design domain the trucks operate in. Most of the current R&D on driverless applications is focused on propulsion (i.e moving the vehicle from one point to another without the assistance of a human driver). To realize truly autonomous long-haul cargo transport, several other ancillary functions outside propulsion would have to be designed to be autonomous. This thesis attempts to take a top-down system thinking approach to explore such functions and propose architectures that would enable end-to-end autonomy and a roadmap towards achieving this over the next decade.
Use case analysis is performed to understand typical functions carried out during cargo transport. The technology readiness, societal readiness, and perceived return on investment of the technologies required is assessed. These high-level functions are then categorized into a set of architectural decisions and an architectural space is created by possible combinations of these decisions. The architectural space is represented as a technology readiness versus return on investment tradespace and architectural choices on the pareto frontier are analyzed. A technology roadmap of necessary is proposed. An analysis of possible off nominal scenarios is conducted, relative to the ability of the architectures to deal with them.
The main takeaway from this work suggest focusing on truck platooning as a near term goal towards partial autonomy which would realize immediate fuel saving benefits. Real time weight sensing, additional automation in performing activities like loading/ unloading cargo (for minimizing trip delays and increasing fleet throughput), pre-trip vehicle checks, automation in fault actions while en-route are also achievable within the next decade and would lead to significant cost savings and minimize operational losses for fleets. The analysis also indicates the need of onboard technologies to facilitate interactions with external human agents (a human machine interface) and increased reliance on faster data connectivity, transfer, and bigger data storage. The study of current state of art technological development suggests that the challenges in realizing autonomous long haul cargo transportation lie not only in the maturity of low TRL technologies, but also in the integration and tuning of existing technological solutions to suit the freight industry. Achieving full autonomy is not possible within next ten year timeframe due to the maturity of technologies required to address certain critical off nominal scenarios (e.g a truck getting hijacked or vandalized, malicious actors filling incorrect fuel in the truck, cargo spilling out on the freeway while a driverless truck is enroute etc) and associated infrastructural frameworks (laws, insurance, ownerships). The study synthesizes these insights and presents the levels of autonomy that would be achievable within next decade and technological needs to achieve fully autonomous operations in longer run.
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