In the context of smarter mobility, decisions need to be made on various different levels: strategic, tactical and operational. The strategic level includes processes and activities for setting long term goals, policy development and visions. At the tactical level decisions are made on projects, funding and establishment of networks and partnerships. At the operational level it involves the implementation of projects and provision of solutions to many complex problems.
Therefore, is distributed decision making the answer to the many decision making challenges for smarter mobility?
Distributed decision making is hard, it requires the distribution of information, authority and resources. There can be fundamental difficulties in making and coordinating decisions that will serve the interests holistically and also the operators within it. There can be tension between the need to control operators involved and the need to let them respond to the demands of their own immediate situation.
At its simplest, a decision situation faced by a one person decision maker involves a static world about which everything can be known and no formal representation of knowledge is required. Distributed decision making means the opportunity for more views to evolve and be heard. Yet it can be problematic if the shared past and present experience leads the players to think similarly while taking confidence in numbers. (Lanir, 1982).
The individuals in a distributed decision making system need to have a shared concept of the vision and objectives at a fairly high level of generality that allows them to work effectively in the constrained environment for which they have more detailed knowledge. Achieving this requires both training so that distributed operators share conceptions and distributing current information so that they can stay in touch conceptually. (Carley, 1986).
However, from an operational standpoint, the system has the ability to use individuals and materials interchangeably, as well as its relative insensitivity to the loss of any particular units. As a distributed decision making system, benefits include the existence of a shared organisational culture, the ease with which components can interpret one another’s actions and the opportunity to create widely applicable organisational policies. One of its main advantages is the ability to develop task specific procedures, policies and communications.
Distributed decision making for Smarter Mobility has the additional complication of requiring decision support systems as decision aids.
Computerised decision making aids have the ability to handle large amounts of information rapidly (Behn and Vaupel 1983) and can be very effective in supporting distributed decision making systems. They can incorporate the wisdom of the most accomplished experts regarding a particular category of problem. However, for them to work effectively for the distributed decision making system depends on their capabilities and on the appropriateness of the faith placed in those capabilities. Therefore, any enhancements to the expert systems should improve their usefulness for distributed decision making provided operators within the system understand what they do and how well they do it.
It was demonstrated in the report that the modelling of a mathematical decision aid provided information on transport emissions in a highly populated urban area, to inform decision making on transport issues. Also, the application Stochastic and Evolutionary games and multi Bayesian agents demonstrated the ability to tackle an urban traffic flow control problem, although there were some limitations identified.
In relation to stakeholder engagement in a distributed decision making system, the principles of Game Theory can provide a useful aid to create stakeholder synergy. This focuses on decision making settings where each other’s decision can influence the outcome and well-being of the other players as well as all players in some cases, therefore each player has to think of how the opposing player will act in order to maximise their payoffs/ benefits.
A general conclusion therefore is that Distributed decision making has the potential to address smarter mobility, as it captures the cumulative change in the nature of multi person decision making that has been wrought through advances in technology. The progress in development has increased the distance over which individuals can maintain contact, the speed with which information and instructions can be shared, the amount of information being created and the information load, the opportunities for monitoring operator’s behaviour and the automation of instructions.
For smarter mobility, one of the most distinguishing features of distributed decision making is that it comprises the diversity to manage the flow of information between people and transport as well as the capability to facilitate hierarchic governance (centralised decision making) and market/network governance (decentralised decision making).
However, the design and specification of a distributed decision making system needs to bear in mind the reality of the individuals at each node in it. A key component at the core of distributed decision making systems are the people who have to get the work done.
It needs to ensure that the design process is not dominated by issues with the most recent complication. Also, if the designers are unfamiliar with the world of the system operators, they need to learn about it to ensure that problems are dealt with effectively. In addition, and in accordance with case studies undertaken, for distributed decision making systems to be effective they must disseminate responsibility for their various functions. This dissemination needs to include the collection, sharing and interpretation of information as well as the decision to undertake various classes of actions.