Road safety is a priority for policymakers. On a regular basis, road accidents cause significant human and economic loss. It has been established that speed is a major cause of road accidents. Technological solution such as Intelligent Speed Adaptation (ISA) may have a large potential to alleviate the problem. ISA is a system that ‘knows’ the maximum speed of the road the driver is using, and provides the driver with feedback about this. Implementation of ISA is a challenge, however, since policymakers are faced with a range of uncertainties.
“One of these uncertainties is the exact relationship between speed and accident risk,” says researcher Datu Buyung Agusdinata. “Another is user acceptance. Usually surveys are employed to assess people’s potential interest in a new technology, but it turns out that these surveys cannot predict whether or not people will actually comply with the system once they have it installed, or use it correctly.”
Agusdinata and his colleagues use a new method called exploratory modelling and analysis, which aims to facilitate the formulation of a robust policy for implementing ISA. This method uses computational experiments across a range of assumptions about the future system and user responses. “We take into account various factors, such as external forces and policies, and analyse in which cases an ISA policy proves to be successful. Which are the criteria that determine success? Which threshold values should trigger a change in policy?”
The ultimate goal is to design robust policy: policy that leads to a traffic system that functions in an acceptable way under a wide range of circumstances, including for instance a low level of compliance or acceptance. “We don’t aim to design one optimal policy,” underlines Agusdinata, “because such a policy does not exist. Circumstances are always different. Our aim is to create a map that defines the variables that play a role, and sets out which policy would function best under which scenario. It is this kind of information that policymakers need in order to make informed decisions.”