By M. Papageorgiou
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Additional info for Applications of Automatic Control Concepts to Traffic Flow Modeling and Control
Cannot ~(k) is a zero m e a n noise. however, speed, eqn. 4) we i n t e n d Since from eqns. 3. ¢ (k) is an a d d i t i o n a l inaccuracies and the s e g m e n t of /48, of qo and w ° as input v a r i a b l e s ys (k) = where leaving for d e n s i t y in figure ql and w I as o u t p u t sidered resp. the d e v e l o p m e n t the k t h entering speeds the of these in the s p e c i f i c a t i o n of the 46 [p(k) A v(k+l) ql(k) T J Iv(k) + n(k)] + qo(k) T w = (k) o p(k) A Recall that + [qo(k)-ql (k)] is the n u m b e r of v e h i c l e s p (k)" A at time k T.
The Complex stored data (internal site) ,12, is replaced for each choice of a new parameter the value of the cost functional •QQ the parame- of the cost functional set chosen Of course, to figure set of points ~ space. After each iteration ter set with the worst value routine. of the cost functional. 2 - Optimization structure 37 reach a sufficiently no f u r t h e r small improvement region achieved by further however, it is not e a s y to d e c i d e has b e e n actually repeat iterations. reached.
That have been safety considerations than control purposes. installed, of traffic phenome- It should be noticed, an oversaturated as an optimization models, performance cri- inter- p r o b l e m on the which will be presented in 23 Mathematical models of traffic at road intersections quite different than the ones of traffic street described up to this point. are flow on a long This is due to the fact, that attention is focused on the intersection phenomena, built up of queues etc. rather than on the process of traffic flow.
Applications of Automatic Control Concepts to Traffic Flow Modeling and Control by M. Papageorgiou