AI expertise and technology, transportation and logistics knowledge, infrastructure availability, financial resources, human capital.

Assess impact of re-routing inland transport of shipments in terms of time, economy and environment through AI and ML, reducing, therefore, time processes and costs of transport, either economically and environmental. The solution lets the exchange of slots minimising idle time at container terminals achieving a ship-to-train interconnection and a greater flexibility, frequency and regularity of services; optimising the use of trains/trucks and reducing port’s environmental footprint as well as disturbances to the local population. 

The next steps are: Data collection and analysis, algorithm development and improvement, marketing and sales, customer support, partnership building

The market segment is Transport and Logistics and the targeted customers are logistics operators and shipping agents. The service is oriented to an existing B2B market composed of private railway operators offering a transport service or shipping agents contracting this service

AI algorithm can improve efficiency and reduce emissions in logistics chains by addressing inefficiencies in ports and hinterland and combined with autonomous shunting services, it can increase efficiency in ports. Railway operators can generate revenue from the solution, which can be used for further development and improvement and could be adapted to other logistics scenarios. The algorithm combined with JIT rail shuttle service can minimize handling movements and costs of transport, providing economic and environmental benefits.

In the short/medium term, the suitable exploitation pathway for the JIT KER will be “technology development”, in order to continue advancing on the progress of the service to achieve a ready-to-market result. The different steps to consider in this exploitation pathway are the integration and customization of the algorithm in the shipping agents and railway operators’ systems and processes to ensure a seamless operation. The next step will be the validation of the result by a pilot testing to ensure the accuracy and effectiveness of the result. The fourth step will be monitoring and improving the performance of the algorithm. Finally, the algorithm will be implemented for the JIT rail shuttle service between the port of Valencia and logistics facilities in several destinations. For the long-term exploitation pathway, a good option could be the creation of a joint venture between the partners involved in the Decision Support Algorithm development.