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Physica
North-Holland
Physica

North-Holland

0378-4371

Physica/Journal Physica
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    Machine learning approach versus probabilistic approach to model the departure time of non-mandatory trips

    Rasaizadi, ArashFarzin, ImanHafizi, Fateme
    11页
    查看更多>>摘要：Unbalanced distribution of trips during the time is one of the factors influencing traffic congestion at some hours of a day. Identifying the significant factors on travelers' departure time choice and predicting their behavior helps maintain the balance in the time distribution of trips. For this purpose, this study employs and compares two machine learning and probabilistic approaches to model the departure time choice, including four choices, morning peak, noon peak, evening peak, and non-peak hours. Probabilistic support vector machine (PSVM) and multinomial logit (MNL) models calibrated based on the origin-destination data of Qazvin, and the evaluation and comparison of these two models made based on two applications of identifying the significant factors on the departure time and predicting the departure time. In terms of interpretability, the MNL model results have an indisputable advantage due to the lack of interpretable coefficients and parameters in the PSVM model. On the other hand, machine learning models' predictive power partially covers the disadvantage of not being interpretable. The results show that the PSVM model can predict the departure time with 53.96% accuracy than the 49.98% accuracy of the MNL model. The maximum balanced accuracy for predicting morning peak, noon peak, and non-peak options is 69%, 53%, and 60%, respectively; obtained by the PSVM model and the MNL model predicts the evening peak option with a balanced accuracy of 52% more accurate than PSVM. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Car-following characteristics and model of connected autonomous vehicles based on safe potential field

    Jia, YanfengQu, DayiSong, HuiWang, Tao...
    16页
    查看更多>>摘要：Aiming at the characteristics of connected and autonomous vehicle (CAV) which makes autonomous decision by perceiving the surrounding environment, a safe potential field model including lane marking potential field, road boundary potential field and vehicle potential field is established to describe the safe risk of CAV in the process of driving. In the process of building the safe potential field model, aiming at the defect that the existing vehicle potential field function has independent gravitational and repulsive expressions, a unified function of vehicle potential field based on Lennard-Jones potential is established by referring to the relationship of intermolecular interaction, and the parameter of vehicle's acceleration is considered into the vehicle potential field model. The statistical analysis of the parameter reveals that the change of acceleration directly affects the distribution of vehicle potential field and reflect the dynamic trend of vehicle's safe potential field under different driving states. Then, the safe potential field is applied to the car-following behavior of CAV, and the model's parameters are calibrated by Shanghai natural driving dataset; Finally, compared with the existing classic IDM and VTH models, the simulation results show that: the model still has smoother response curves in the three car-following scenarios designed to improve the safety and efficiency, which verifies the effectiveness of the model. The research results can lay a theoretical foundation for decision making behavior of safe driving, and also provide a unique way for the research of CAVs' safe technology. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    The solution of Lanchester's equations with inter-battle reinforcement strategies

    McCartney, Mark
    9页
    查看更多>>摘要：A two army conflict made up of repeated battles with inter-battle reinforcements is considered. Each battle is modelled via Lanchester's 'aimed fire' model and three reenforcement strategies; constant, and linearly and quadratically varying (with respect to post-battle troop levels) are investigated. It is shown that while a constant reenforcement strategy will always lead to an outright victory via a simple partitioning of the two dimensional army strength space, linear reinforcement can lead to stalemate, and quadratically varying reinforcement can lead to stalemate, with quasi-periodic and chaotic behaviour, and the creation of fractal partitioning the army space. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Thermal fluctuations in a realistic ionic-crystal model

    Gangemi, RobertoCarati, AndreaGalgani, LuigiGangemi, Fabrizio...
    11页
    查看更多>>摘要：We investigate the thermal fluctuations of the ionic motions in a Born model of ionic crystals, namely, a model in which the electrons are eliminated, being replaced by suitable effective potentials among the ions. The model is studied in its classical version, computing the Newtonian trajectories of the ions. The general motivation is that, although being an essential ingredient within Green-Kubo linear response theory, thermal fluctuations apparently were not studied systematically by molecular dynamics methods, as was done instead for the approach to equilibrium in the Fermi-Pasta-Ulam problem. The time evolution of the fluctuations is studied in terms of the time-changes of the mode-energies of the system. The stages of the "regression" of the fluctuations are described, from a first stage of strong time-correlations up to a final decorrelation, and a comparison with the process of approach to equilibrium is performed. Finally, the dependence on specific energy is investigated. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Understanding the influencing factors of bicycle-sharing demand based on residents' trips

    Hu, BeibeiZhong, ZhenfangZhang, YanliSun, Yue...
    18页
    查看更多>>摘要：Bicycle-sharing is an eco-friendly transportation operating model in the context of "Internet Plus" and the sharing economy. It not only meets the short-distance travel needs of residents but has great significance for promoting the sustainable development of urban public transportation. However, a series of problems have appeared in the bicycle-sharing market, such as unreasonable resource allocation, low operating efficiency and management difficulties. Based on booking data and GPS trajectory data in Beijing of Mobike, this paper statistically analyzes the spatial and temporal distribution characteristics of residents' bicycle-sharing trips. Then, we construct a multi-factor influence model of bicycle-sharing demand based on a negative binomial regression and variable selection model, which quantifies a series of factors that influence bicycle-sharing trips, such as population and the regional economy, building land attributes, transportation accessibility, weather, and climatic conditions, etc. The results show that, firstly, there is a spatial imbalance in the distribution of bicycle-sharing demand among different districts in Beijing. Bicycle-sharing demand is mainly concentrated in the six core districts of the city, with more than 80% of all demand. We also find that the bicycle-sharing demand has different distribution characteristics on working days and nonworking days. Compared with nonworking days, residents' demand for bicycle-sharing on weekdays shows obvious peak periods in the morning, noon, and evening. Secondly, factors that have a major impact on the demand for bicycle-sharing include: per capita disposable income, pass facilities, parking lots etc. Among them, factors such as per capita disposable income, pass facilities, parking lots and bus/subway stations have a significant positive influence on bicycle-sharing demand. However, the number of functional zones such as airports, ports and marinas, tourist attraction and automobile sales has a significant negative influence. In addition, a comfortable temperature and good air quality encourage residents to use bicycle-sharing more for travel, while high humidity is not conducive to bicycle-sharing. We suggest that companies and related departments should jointly participate in the regulation and management of the bicycle-sharing industry, in various aspects such as bicycle scheduling, bicycle management and industry systems. In this way, cities can allocate bicycle-sharing resources reasonably and improve overall operating efficiency. The advantages of bicycle-sharing can be better used to promote the sustainable development of urban public transportation in the future. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Exploring the resilience assessment framework of urban road network for sustainable cities

    Liu, ZhizhenChen, HongLiu, EnzeHu, Wanyu...
    21页
    查看更多>>摘要：Urban space for new transportation facilities cannot meet the increasing traffic demand. Afterward, scholars gradually increased attention to the resilience evaluation of urban road networks. Therefore, we proposed a resilience assessment framework of the urban road networks, including the resilience performance index, the robustness index, and the recovery index. Then we simulated the cascading failure based on a nonlinear load-capacity model with two capacity control parameters: alpha and beta. Results show that the intersection-based attack has the most significant impact on resilience, and resilience is positively correlated with the node degree of the attacked intersection. The increase of alpha and beta could enhance the resilience, and the urban road network achieves the best resilience performance when alpha = 0.3, beta = 0.5. Compared with the deliberate attack strategy, the resilience performance under the random attack strategy is more robust. This research can provide the foundation for optimizing urban road networks and multi-mode urban public transit networks. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Scheduling wheel inspection for sustainable urban rail transit operation: A Bayesian approach

    Zheng, PengjunHuang, ZhaodongChien, StevenZhu, Wei...
    15页
    查看更多>>摘要：Scheduling the wheel inspection is critical to ensure the safety and sustainability of urban rail transit (URT) operation. The common wheel inspection is conducted on a fixed-interval basis, determined by empirical practices. However, the relationship between the distance of wheel travel and wheel wearing condition subject to track alignment is uncertain. A Bayesian model is developed to schedule the timings of wheel inspections which meet the safety thresholds for sustainable train operation. In the case study, the historic wheel inspection data of a real-world URT line was collected and analyzed, which indicates that wheel reprofiling follows a Weibull distribution. The suggested wheel inspection plan by the proposed model is compared with fix-interval inspection. The results show that the inspection frequency can be significantly reduced before yielding 180,900 km wheel travel, which satisfies the wheel reliability as 0.95. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier