The research analyzes the possibile development of road traffic liability, product liability and car insurance in the face of the progressive automation of the global vehicle fleet. Moving from a historical overview of the rules currently governing road traffic liability on the European continent, the research shows how this subject has developed over the decades, looking for a difficult balance between effective protection of injured parties and economic efficiency. As a result, road traffic liability regimes have some unique characteristics, which are expected to remain relevant even when the global vehicle fleet is composed of highly automated vehicles. The challenges posed by automation change with the degrees of technological advancement. By seeking to enhance the dialogue with technology, the research shows that there are realistic evolutions and utopian prospects, and that the excessive focus on the latter has contributed to an underestimation of the impact that more basic forms of autonomy have on road traffic. In fact, the Advanced Driver Assistance Systems (ADAS) – although they do not require amendments to existing civil liability systems – have so far been developed by requiring humans to adapt to the machine, and not the other way around. In contrast, safety needs would dictate that the software of the future be designed following a human-centered philosophy. More advanced levels of automation raise question about whether current traffic liability regimes should be amended, especially given the fact that the vehicle owner is no longer in the best position to manage risks. Preliminarily highlighting the need for a liberal and confident approach toward innovation, hypotheses for regulation that have emerged in the debate have been analyzed: given the difficulty of finding a clearly winning compromise between protecting third parties and incentivizing innovation, it is believed that the key lies in a simple, technically aware, sector-specific regulation that is adaptable to the multiple mobility scenarios of the future. The soft-law can be a useful tool for managing the technology's market debut, while waiting for evidence to suggest in which direction the technology will evolve and – consequently – the most appropriate civil liability framework.

During the years 2004-2014, the manufacturing sector within the EU countries witnessed an increase in the utilization of industrial robots, where robot density per worker approximately doubled. Considering that this is a rather recent event, studies investigating how much industrial robots impact labour productivity are still rare. At the same time, one of EU’s outspoken goals is that of working to foster productivity and economic convergence between the member states. Given the above premises, we have investigated the relation between the adoption rate of industrial robotics within the EU and its effect on labour productivity. Secondly, we have made a predictive convergence model, in terms of labour productivity. We have collected data from several sources, including the Industrial Federation of Robotics and EU KLMS, in order to build a dataset for our quantitative analysis. We have then used statistical methods such as multiple regressions and 3 stage least square analysis (3sls) to estimate our system of interdependent equations model. The results show that implementation of industrial robotics in the manufacturing sector is a driver of labour productivity. The model finally predicts upward labour productivity divergence between the member states in the years 2015-2025, assuming that the determining factors of labour productivity grow at the same pace in our forecast period as in our data sample. / Under åren 2004-2014 fördubblades i genomsnitt antalet industrirobotar per arbetare i tillverkningsindustrin inom EU. Eftersom detta fenomen är relativt nytt, är studier som undersöker industrirobotars påverkan på arbetarproduktivitet fortfarande sällsynta. Samtidigt är ett av EU:s uttalade mål att arbeta för att främja konvergens mellan medlemsländerna inom produktivitet och andra ekonomiska mått. Med ovanstående förutsättningar har vi undersökt förhållandet mellan ökad användning av industriell robotik inom EU och dess effekt på arbetskraftsproduktiviteten. För att bygga en model för vår kvantitativa analys har vi samlat in data från flera källor, inklusive Industrial Federation of Robotics och EU KLMS. Vi har sedan använt statistiska metoder såsom multipel regression och 3-stegs minsta kvadratanalys (3sls) för att estimera vårt system av ekvationer. Resultaten visar att ökad användning av industriell robotik i tillverkningssektorn driver ökad arbetskraftsproduktivitet. Därefter analyserar vi även den aktuella konvergensriktningen för arbetarproduktivitet, och vår modell förutspår uppåtgående arbetsproduktivitetsdivergens, under förutsättning att de ingående faktorerna för arbetskraftsproduktivitet växer i samma takt under vår prognosperiod som under dataunderlagsperioden. / Durante gli anni che vanno dal 2004 al 2014 il settore manifatturiero degli stati appartenenti all’Unione europea è stato testimone di un aumento dell’utilizzo dei robot industriali: la densità di robot utilizzati per ciascun lavoratore è raddoppiata. Considerato che questo è un fenomeno abbastanza recente, gli studi che investigano quanto i robot industriali influiscono sulla produttività lavorativa sono ancora rari. Allo stesso tempo, uno degli obiettivi dichiarati dall’Unione europea è quello di stimolare la convergenza economica tra gli stati membri. Date queste premesse, abbiamo studiato la relazione tra il tasso di adozione dei robot industrali nell’Unione europea e il suo effetto sulla produttività del lavoro. Inoltre, abbiamo sviluppato un modello di previsione della convergenza in termini di produttività lavorativa. Abbiamo raccolto i dati da diverse fonti, tra cui la federazione industriale della robotica ed EU KLEMS, in modo da costruire un dataset per la nostra analisi quantitativa. In seguito abbiamo usato dei metodi statistici come la regressione multipla e la l’analisi dei minimi quadrati a tre stadi (3sls) per testare il nostro sistema di equazioni indipendenti. I risultati mostrano che l’implementazione dei robot industriali nel settore manifatturiero è un elemento motore della produttività lavorativa. Infine, il modello prevede una divergenza della produttività tra i Paesi membri negli anni 2015-2025, assumendo che i fattori determinanti della produttività crescano allo stesso modo nel periodo della previsione rispetto al periodo del nostro campione.