Ren-Yong Guo

Route choice in pedestrian evacuation: formulated using a potential field

A method for formulating the route choice behavior of pedestrians in evacuation in closed areas with internal obstacles is proposed. The method is implemented in a pedestrian model, in which the route choice is determined by the potential of discrete space. The potential measures the total effect of such factors affecting route choice as route distance, pedestrian congestion and route capacity. Using scenario simulations, the proposed method is compared with several existing methods. Simulation results indicate that the proposed method can simulate two classes of phenomena that cannot be reproduced accurately by those existing methods. In addition, two examples of inefficient evacuation as regards route choice are given. The two examples illustrate that, for improving the efficiency of evacuation, excessive or limited sensitivity of pedestrians to the route capacity may be unhelpful, and adding an extra route may be inefficient.

A potential field approach to the modeling of route choice in pedestrian evacuation

This study proposes a potential field algorithm for formulating pedestrian route choice behavior during evacuation in individual-based models with discrete space representation. The potential field reflects the effect of the route distance, pedestrian congestion and route capacity on route choice. Numerical simulations show that the developed model can reproduce more route choice modes in a scenario compared with several existing models. Three groups of pedestrian evacuation experiments are conducted and the proposed model reproduces pedestrian route choices effectively.

Day-to-Day Flow Dynamics and Congestion Control

For a predetermined set of an upper bound of link flows, this paper proposes a price-based congestion control scheme for achieving such a restraint target of traffic flow that evolves from day to day. On each day, drivers have to pay a toll selected from a feasible set. The tolls on each day are determined by the link flows and toll charges on the previous day and the predetermined upper bound of link flows. Several properties of the dynamical system model with the control scheme are analyzed, including the invariance of its evolutionary trajectories; the equivalence between its stationary state and user equilibrium under toll charge; the uniqueness, existence, and boundedness of its stationary state; and the convergence of its evolutionary trajectories. A special case of the model and implementation of the control scheme for several alternative targets are also given. Finally, application of the model to a traffic network is demonstrated with a numerical example. The study is helpful for better understanding the mechanism of congestion control under day-to-day traffic flow dynamics.

Are We Really Solving the Dynamic Traffic Equilibrium Problem with a Departure Time Choice

The dynamic traffic equilibrium problem has been a pivotal area of research in transportation for a few decades. The current state-of-the-art research in this area generally considers simultaneous departure time and route choice. In this paper, we theoretically prove that, in the simplest standard bottleneck model with a sufficient number of commuters, a dynamic user equilibrium (DUE) cannot be reached through a day-to-day evolution process of travelers’ departure rate—a central idea behind the iterative dynamic traffic equilibrium algorithms prevalent in the literature. We carry out our exploration with the proportional swap system and then extend our analysis to other typical dynamic equilibrium algorithms such as the network tatonnement process, the simplex gravity flow dynamics, the projected dynamical system, and the evolutionary traffic dynamics. Our investigation indicates that any algorithm analogous to the five categories of systems must be cautious in terms of convergence when it is applied to s...

Day-To-Day Departure Time Choice under Bounded Rationality in the Bottleneck Model

Abstract: We extend the proportional swap system by Smith (1984a) and the network tatonnement process by Friesz et al. (1994) to formulate the day-to-day evolution of departure time choice under bounded rationality in the bottleneck model. It is shown that the stationary points of the doubly dynamical systems exist and are equivalent to the boundedly rational user equilibrium (BRUE) points. We propose a dynamic pricing policy implemented in the day-to-day evolution process. Despite that the stationary points correspond to a set of BRUE points and the day-to-day departure rate without pricing may not converge to the set of BRUE points, the pricing policy can drive the day-to-day departure rate to reach a new equilibrium state, which is system-optimal (SO). The convergence to the SO state is theoretically proved. Finally, by numerical examples, we demonstrate the properties of the doubly dynamical systems and the effectiveness of the pricing policy.