The digitization of economic processes is advancing across all sectors, contributing to the development of Industry 5.0. A key element of this fifth industrial revolution is the activation of robotic economic activity. Recently, advancements in autonomous robotic transport have been implemented in practice. However, both the practical application of unmanned vehicles and scientific developments in this field have shown low efficiency in the implementation of projects for the autonomous transportation of goods and passengers. This inefficiency stems from insufficient attention to the accounting and management aspects of autonomous robotic transport operations. The scientific and practical novelty of this study lies in improving accounting and management practices in the context of digitalization, specifically by addressing the fundamental transformations in economic processes caused by the use of autonomous vehicles. The key organizational factors influencing accounting for robotic transport operations include the type of transported objects, fuel and energy resource consumption, human involvement, the capacity and number of goods (or passengers) transported at one time, continuous operation, maintainability, software update capabilities, autonomous interaction with other transport means, and communication and information sharing with customers of transport services. A method for digitizing the accounting of fuel and energy costs, personnel wages, social activity deductions, depreciation, operational costs, and other costs related to the functioning of autonomous robotic transport has been developed. This method leverages IoT data and considers the organizational prerequisites mentioned. The use of two-dimensional calculation units, such as "kilogramkilometre" and "passenger-kilometre" units, for the digitalization of cost calculations for passenger and cargo transportation via autonomous robotic transport has been proposed. Additionally, the procedure for determining the cost of transport services for end users and the formation of information arrays for the innovative management of transport enterprises has been refined. The elimination of organizational restrictions in managing autonomous transport operations, alongside the need for information synchronization between transport enterprises and other business entities within the information ecosystem of a smart city, highlights future research prospects in this area.
