Modeling and Optimization of Traffic Flow in Urban Areas - Czech ...

2.4 Control of The Simple Intersection Model 15w( k)q( k)Simple intersection modelx M( k)NMPC( C , T ph , ± , ¹ )w( k, k+ T ph)Fig. 2.6: NMPC control loop§J10 810 710 610 510 410 9 LQ RegulatorNMPC (unknown incoming traffic)NMPC (known incoming traffic)0 1 2 3 4 5 6 7 x 10 4t [s]Fig. 2.7: Evolution of accumulated objective functionways. For example, we can extend the controller by taking into accountfuture incoming flow. In practice, we can measure this traffic in a previous,neighboring intersection (as shown by [Lei 01]) and forward this informationto the next intersection controller. In this way, the predictive controller canprepare a much better control action. Trying this approach on the simpleintersection model, adding feedforward traffic information to the NMPC isable to reduce the cost function J by about 37%. The accumulative value ofthe cost function J for different controllers is depicted in Fig. 2.7. We can seethat the NMPC yields much better results than LQR, and that feedforwardfrom the incoming traffic improves the result even further.To evaluate the sensitivity of the NMPC to the incoming flow, the fol-