Optimization of R&D resource intensity in intelligent transport systems

The problem of the high resource intensity of research and development (R&D) processes in the field of intellectual transport systems (ITS) is caused by the lack of replicated “boxed” solutions, the high degree of uncertainty of research tasks and the shortage of highly specialized specialists. In conditions of tight product release cycles and limited human resources, the involvement of leading engineers in testing search hypotheses and early prototyping is accompanied by significant alternative costs and a decrease in the efficiency of core operating activities. Based on the theory of organizational ambidexterity, a management model is proposed that assumes an institutional separation of the flows of “exploitation” (support and development of a stable product) and “exploration” (R&D activities). A key element of the model is a mechanism for delegating mathematically and algorithmically complex research tasks to interns under the methodical guidance of a mentor, which allows isolating the research context from operational turnover and minimizing risks to the core product. The proposed approach was tested as part of the development of the correspondence matrix calculation module on the Netvision platform. A mathematical model of the problem based on the transformation of video data into an oriented graph in which vertices correspond to camera clusters is described, and the edges correspond to weighted displacement flows. A prototype (Proof of Concept) and a web-based visualization interface were implemented, which made it possible to identify and systematize specific artifacts of video analytics data, including time drifts and geo-positioning errors. It is shown that the proposed model provides a multiple reduction in the cost of prototyping not only due to differences in the level of remuneration, but also by maintaining the full-time team's focus on high-value-added tasks. The conclusion is made about the need to transform the HR strategy of R&D-oriented companies: sustainable scaling of the model requires priority selection of candidates with a strong fundamental background, since the quality of interns' human capital is becoming a critical factor in technological orientation and the pace of innovative development.