Early estimation of multi-objective traffic flow

Intelligent Transportation Systems (ITS) have come a long way targeting problems such as increasing emissions and growing vehicle numbers. Current approaches address a variety of objectives including congestion management, collision avoidance, energy-efficiency and emission reduction. However, respective solutions typically are designed for and tailored to a predefined set of objectives. Consequently, the effects of drastically changing objectives cannot be assessed easily. To address this situation we present a lightweight approach to estimating multi-objective traffic flow early in systems engineering using non-deterministic models and stochastic optimization techniques. We demonstrate the feasibility of the framework using a basic traffic scenario and conclude with future work.