Real-time information feedback based on a sharp decay weighted function
Information feedback strategy, serving as the critical part of intelligent traffic systems, has been treated with growing emphasis. In recent years, a variety of feedback strategies have been proposed. Despite the fact that these strategies have been proved to enhance the traffic efficiency, we find that the road capacity has not been saturated and there is still plenty of room for improvement. Based on the analytic approximations, we found the reason why corresponding angle feedback strategy is superior to weighted congestion coefficient feedback strategy. Given that the sharp decay of the weighted coefficient is the key point, we proposed an efficient feedback strategy called the exponential function feedback strategy (EFFS). We applied it to both the symmetrical two-route model with two exits and that with a single exit. The simulation results indicate that, compared with other strategies, EFFS has decided numerical advantages in average flow, a physical quantity used for depicting the road capacity. Even more importantly, EFFS stands out for its convenient application as well as its fitness for modeling the rugged roads.
traffic flow exponential decay weighted function cellular automaton model intelligent transportation system