Search

The staggered work hours (SWH) policy is a practical strategy for managing travel demand, aiming to spread out the temporal distribution of travel volume by adjusting the schedules of travelers' activities. The influence of the SWH policy on the commuting patterns of passengers using bus transit is not yet clear. We addressed this issue in a many-to-one bus line, treating commuters as Q-learning agents learning to minimize regrets by selecting appropriate bus runs. The learning outcomes reveal a SWH-induced equilibrium, where commuters departing from the same station with the same work start time experience identical minimal commuting costs, regardless of the chosen bus. Subsequently, we investigate the effectiveness of SWH policy by manipulating two key control variables: the division of travel demand between two categories of travelers and the staggered time interval. The results confirm that congestion during peak hours can potentially be mitigated by carefully selecting the above two key parameters. Correspondingly, we provide optimal control boundaries for these two parameters to design an effective SWH policy. Furthermore, we explore the combined impact of physical distancing and SWH policy on traffic flow patterns during an epidemic outbreak. Concurrently, we assess the infection risk through a surrogate index, revealing that the SWH policy has a positive effect in mitigating the risk of contact exposure., Author(s): Shengjie Qiang (corresponding author) [1]; Qingxia Huang [2] 1. Introduction One feasible solution to alleviate urban congestion is the implementation of travel demand management measures. These measures aim to [...]

The traditional method of relieving boarding congestion is to reduce aisle and seat conflicts by optimizing the boarding strategy. Here, we focus on another way of smoothing the passenger flow for a novel cabin installed with side-slip seats. Three aspects are discussed in this work. First, we explore the characteristics of fast boarding sequences that benefit most from side-slip seats using a simulated annealing algorithm. Second, we introduce three alternative strategies and evaluate their efficiencies using a realistic aircraft boarding model. The result shows that the boarding time could be largely reduced by adopting the new strategies. Sensitivity analyses also imply that side-slip seats are tolerable to the number of inexperienced passengers who are unfamiliar with the side-slip seats. Besides, the infection risk is also discussed as a function of ticket validation time at the check desk. Third, a boarding assistant system is designed to implement the proposed strategies. [ABSTRACT FROM AUTHOR]

Budget airlines adopt free boarding strategy when conducting passengers to board the airplanes. In such a boarding strategy, passengers are not offered any preassigned seats, and they choose their favorite seats freely once they are inside the airplane. A simulation framework based on cellular automaton is developed to mimic the dynamics of passenger flow in the free boarding process. In the model, each seat in the cabin is assigned a positive value to characterize how desirable it appears to the overall passengers. A logit-based discrete choice principle is applied to formulate the seat choice behaviors of passengers. The influence of the sensitivity parameters on the mean boarding time is discussed to identify the different classes of behavior exhibited by the model. The numerical results illustrate that the new model can qualitatively reproduce some dynamic properties of the free boarding process. Besides, two grouped strategies in a manner of freestyle are proposed, and quantitative comparisons are made with those involve assigned seats. [ABSTRACT FROM AUTHOR]