AI solution for analysing & redesigning bus traffic systems

Purpose and goal: Purpose: Develop new digital technologies and methods for increased efficiency and attractiveness.

Objectives: Develop (1) analysis tools that show the real need for mobility, (2) optimization tools that increase transport efficiency through alternative design of bus networks, (3) introduce the analysis tool in the work of overviewing rural traffic, (4) demonstrate how predictive analysis of vehicle movements and on/off-boarding enables automation.

All development goals have been achieved. Continued validation, testing and development prior to commercial use is required. Expected results and effects:

The analysis tool is expected to be ready for commercial use shortly. There is strong interest for commercial it when validation is completed.

The optimization tool has the potential to increase transport efficiency in bus traffic: The project shows an increase in mobility by 37%. Since this technology challenges existing processes and solutions, further exploration is required.

That technology now exists for real-time optimization in traffic management can affect different parts of public transport: procurement, production processes, travel quality and traffic info. Approach and implementation:

An analysis tool has been developed that identifies total movement, market share of publ. transport/car, travel time ratio of publ. transport/car. This information is then linked to demographic data.

A method has been developed for redesigning bus systems, aiming to increase transport efficiency. The analysis tool and a technology that maximizes movement are key components. The project has demonstrated real-time optimization for automated decisions in traffic production. All development has been done in collaboration between the three need owners and Commuter Computing.