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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. [ABSTRACT FROM AUTHOR]

Implementing operational strategies is a sustainable and effective way for providing good bus serviceability, but the effects of the strategies on other traffic participants, e.g., cars, have drawn little attention. This paper thus aims to explore the effects of the mutual interference between buses and private cars, when applying a bus control strategy to a regular transit line. Three threshold-based strategies are compared, including (a) holding control (HC); (b) limited boarding control (LBC) and (c) holding combined with limited boarding control (H-LBC). A cellular automaton based model is proposed to depict the interaction between cars and buses, and the model parameters are calibrated using data collected from a real-life bus route in Beijing, China. The control strategies are evaluated by their benefits for three stakeholders involved in the system, including passengers, bus operator and car drivers. Simulation results show that a good bus control strategy does not only improve the efficiencies of bus operating and passenger travel, but also speed up the car running by alleviating traffic congestion. In turn, the car volume is an important factor when setting the optimal parameter for control strategies. Moreover, the comparison suggests that H-LBC outperforms the other two strategies in improving the service level for passengers, buses as well as cars, especially under crowded scenarios. [ABSTRACT FROM AUTHOR]

The foldable and the side-slip seats are designed to facilitate the aircraft boarding process by providing wider spaces. Yet, these futuristic concepts have not been investigated exhaustively concerning boarding time performance and the sensitivity of various factors. Thus, we test the effectiveness of such two new concept seats by using a cellular automaton (CA) based aircraft boarding model. Simulation results confirm the potentials of improving efficiency by using the two innovative seats, and of which the foldable seat prevails over the side-slip seat in boarding time. About 12.7% and 30% time reduction could be achieved for the side-slip seat and the foldable seat by taking the conventional seat performance as a baseline, and this value could be further increased by using some other refined boarding strategies. Moreover, the foldable seat exhibits much robustness to the variation of the boarding conditions than the side-slip seat and thus could provide a much reliable boarding environment. [ABSTRACT FROM AUTHOR]

The asymmetric simple exclusion process (ASEP) is a paradigmatic model for nonequilibrium systems and has been used in many applications. Airplane boarding provides another interesting example where this framework can be applied. We propose a simple model for boarding process, in which a particle moves along a one-dimensional aisle after being injected, and finally is removed at a reserved site. Different from the typical ASEP model, particles are removed in a disorderly or a parallel way. Detailed calculations and discussions of some related characteristics, such as mean boarding time and parallelism indicator, are provided based on Monte-Carlo simulations. Results show that three phases exist in the boarding process: free-flow, jamming and maximum current. Transitions between these phases are governed by the difference between the injection and removal rate. Further analysis shows how the scaling behavior depends on the system size and the boarding conditions. Those results emphasize the importance of utilizing the whole length of the aisle to reduce the boarding time when designing an efficient boarding strategy. [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]

A simple airplane boarding model is built much like an asymmetric exclusion process (ASEP). The dynamics of the model is constrained by local interference between passengers and global seat assignments for individuals. We perform extensive Monte Carlo simulations by using a parallel update rule to determine quantities like boarding time and sequence correlation. Our results clarify the scaling behavior in boarding process and identify a critical value of arrival time interval for boarding time threshold. Three different phases (steady, intermediate and linear) with respect to the boarding time are distinguished and the mechanism behind phase transition is further discussed. [ABSTRACT FROM AUTHOR]