Feedforward feedback iterative learning control method for the multilayer boundaries of oversaturated intersections based on the macroscopic fundamental diagram

The feedback control based on the model and method of iterative learning control, which in turn is based on the macroscopic fundamental diagram (MFD), mostly belongs to the classification of single-layer boundary control method. However, the feedback control method has the problem of time delay. Therefore, a feedforward feedback iterative learning control (FFILC) method based on MFD of the multi-layer boundary of single-area oversaturated intersections is proposed. The FFILC method can improve the effectiveness of boundary control and avoid the time-delay problem of feedback control. Firstly, MFD theory is used to determine the MFD of the control area; the congestion zone and the transition zone of the control area are identified; and the two-layer boundary of the control area is determined. Then, the FFILC controllers are established at the two-layer boundary of the control area. When the control area enters into a congestion state, the control ratio of traffic flow in and out of the two-layer boundary is adjusted. The cumulative number of vehicles in the control area continues to approach the optimal cumulative number of vehicles, and it maintains high traffic efficiency with high flow rates. Finally, The actual road network is taken as the experimental area, and the road network simulation platform is built. The controller of the feedforward iterative learning control (FILC) is selected as the comparative controller and used to analyse the iterative effect of FFILC. Improvements in the use of traffic signal control indicators for the control area are analysed after the implementation of the FFILC method. Results show that the FFILC method considerably reduces the number of iterations, and it can effectively improve convergence speed and the use of traffic signal evaluation indicators for the control area.

Studies Regarding Semaphoring Effectiveness in Oversaturated Intersections

Need for transport accelerated growth recorded in the past years results in worsening road congestion phenomenon, with negative effects in all domains of life. Thus, some road junctions’ capacity is exceeded during peak hours and traffic lights are not effective any more. In these situations, modifications to infrastructure or/and changes in the local policy plan are required. However, these cannot be performed immediately and remain rather a solution that will operate later. The authors attempt to find out a satisfying semaphoring scheme for these time slices, outlining the effects.

The Over-Saturated Traffic Identification Based on Cell Transmission Model

In order to identify the oversaturated intersections accurately, the fundamental cell transmission model was modified to satisfy the oversaturated traffic flow. Then, several traffic information was obtained from the modified CTM to identify different oversaturation. The simulation example shows that the sum of queue is suitable for evaluating the oversaturation of whole network, and the queue length and queue intensity are suitable for evaluating the oversaturation of local intersection.