Each year traffic in Europe claims more than 40,000 fatalities, of which one third are due to inappropriate speed. This makes increasing traffic safety and reducing speeding important policy objectives for public policymakers. A possible measure to help achieve these objectives is implementing Intelligent Speed Adaptation (ISA), an in-vehicle device that assists a driver in maintaining the appropriate speed. Past research in this field focuses on estimating ISA's safety benefits, as well as the impact of ISA on other criteria, such as emissions, throughput, and travel time. Coming up with a robust policy, however, also requires insights into the trade-offs the various stakeholders make with respect to these criteria. In this paper, we show how exploratory modeling in a multi-criteria multi-stakeholder context can support developing robust policies for implementing ISA.
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