A conceptual framework for using feedback control within adaptive traffic control systems

Existing adaptive traffic control strategies lack an effective evaluation procedure to check the performance of the control plan after implementation. In the absence of an effective evaluation procedure, errors introduced in the system such as inaccurate estimates of arrival flows, are carried forward in time and reduce the efficiency of the traffic flow algorithms as they assess prevalent traffic conditions. It is evident that the feed-forward nature of these systems cannot accurately update the estimated quantities, especially during oversaturated conditions. This research is an attempt to develop a conceptual framework for the application of feedback control within the basic operation of existing adaptive traffic control systems to enhance their performance. The framework is applied to three existing adaptive traffic control strategies (SCOOT, SCATS, and OPAC) to enable better demand estimations and queue management during oversaturated condition. A numerical example is provided to test the performance of an arterial in a feedback environment. The example involves the design and simulation test of Proportional (P) and Proportional-Integral (P1) controllers and their adaptability to adequately control the arterial. A sensitivity analysis is further performed to justify the use of a feedback control system on arterials and to choose the type of controller best suited under given demand conditions. The simulation results indicated that for the studied arterial, the P1 controller can handle demand estimation and queuing better than P controllers. It was determined that a well designed feedback control system with a PI controller can effectively overcome some of the deficiencies of existing adaptive traffic control systems

EVALUATION OF FEEDER BUS SYSTEMS WITH PROBABILISTIC TIME-VARYING DEMANDS AND NONADDITIVE VALUE OF TIME

The paper presents a comparison of optimal fixed route conventional bus (CBS) and flexible route subscription (SBS) bus systems. The systems are compared in terms of average cost per trip, including the operator and user costs, as an objective function to be minimized, with vehicle size, route spacing, zone size and headway as the system decision variables. The systems serve probabilistic demand that varies over a ten-hour operating period with a higher number of trips in the morning and afternoon periods. Passengers are assumed to have non-additive value of time. Average cost per trip is calculated for a numerical example in order to compare the suitability of a particular service under various demand conditions. For this particular example, the CBS has the lower cost service. However, the operator can further reduce the cost of daily operation by providing the CBS in periods of high demand and operating the SBS in off-peak periods. In general, the threshold value of demand at which one system is more cost effective than another is readily calculated. A sensitivity analysis is conducted to show the effect of varying model parameters on the objective functions and the decision variables