Abstract
AI research applied to urban and interurban mobility seeks to improve systems
transport through the optimization of the distribution of resources, such as vehicles and
stations, to efficiently meet the demand for travel.
This approach considers crucial aspects such as environmental sustainability, experience
the economic viability of the operator and proposes solutions that balance these
often conflicting interests. With the use of artificial intelligence techniques, such as
agent-based modeling, changes can be experienced in the infrastructure of
transport and its operations prior to their actual implementation, thus ensuring practical
and adapted to the specific needs of urban and rural areas. This comprehensive approach
allows the creation of more adaptive, efficient and respectful transport systems
environment, significantly improves mobility of people within environments
and effectively connects interurban areas.
The urban and inter-urban mobility service is mainly aimed at a wide range
companies and public entities interested in optimizing transport systems. Among them
transport operators who manage bus, tram and metro services, to search for the
improved operational efficiency and user experience. Also logistics companies and
freight transport focused on route optimization, efficient distribution of goods
and reduced costs and environmental impact. As well as developers of technological solutions
for intelligent mobility. And municipal and regional public entities responsible for
transport planning and regulation.