In the DIT4TraM project we develop control concepts and algorithms with swarm intelligence for the widest possible range of applications during this project period. On this page we introduce the four main applications of the DIT4TraM concepts.
1. Cooperative connected traffic management
How do we optimally distribute traffic at the micro level of, say, an intersection? Traditionally, the local traffic management system distributes the green of the traffic lights among the traffic participants. But in DIT4TraM we investigate the extent to which (connected) traffic participants themselves can achieve optimum green-time allocation. Such a local solution requires information about the type of road user, the destination, and the preference, combined with a set of ‘priority rules’ and incentives.
2. Cooperative distributed traffic management
In this application, traffic control systems, ramp metering systems and other local systems work together to optimize the network. To this end, they negotiate with their ‘neighbors’ about the measures. For example, does dosing traffic here not cause inconvenience further down the road? How do we ensure that pedestrians, cyclists, shared cars, and public transport get the priority they deserve, while coordinating the flow of car traffic as well as possible?
3. Decentralized demand management
In this application field we work with tradable multimodal travel permits. The idea is that travelers buy or sell their ‘permit’ to a ride among each other, depending on the demand at that moment. Those who need to travel to a busy destination at a busy time will automatically pay more. Those who are more flexible can save money by postponing a planned ride, sharing the ride or traveling with another modality. We investigate the extent to which this decentralized approach leads to fewer peak loads and a better distribution of passengers. Where necessary, the government will intervene by, for example, capping the number of permitted (car) trips.
4. Cooperation between transport services
Public transport companies and commercial mobility services have different objectives and are, in a way, competitors. Here, too, we examine the extent to which the mutual interactions between these actors organize themselves into a stable, possibly optimal situation and the extent to which (limited) interventions, such as agreements on mutual coordination, can prevent a suboptimal situation.