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金沢大学理工研究域地球社会基盤学系, How many base travel groups (models) are necessary for clarifying the long-term day-to-day dynamics of intercity travel? In the past, several travel purposes (e.g., sightseeing, business, etc.) have been assumed. However, mobile-phone location data enables us to answer the above question because of their detailed time-series information. In this study, we propose a method for deriving the basic travel groups necessary for clarifying the time-series changes by applying nonnegative tensor factorization (NTF). This method is applied to the time-series data of several long-distance travelers to the Ishikawa prefecture, to where the Hokuriku High-speed rail (HSR) has been newly extended. Based on this, the number of base travel groups necessary for predicting the effect of the new HSR is estimated as twelve, which is greater than the number used in the previous demand forecasting models. The estimated groups include components that appear to correspond to different travel purposes (e.g., sightseeing, business, and homecoming), as in previous surveys. These results confirm that the methodology proposed in this study can clearly extract groups with different elasticities, due to the traffic service. The HSR effect can be clarified by dividing it into several characteristics and detailed components. In addition, if multiple HSR effects are analyzed, a more accurate demand-forecasting model for the new HSR service can be proposed., Embargo Period 12 months

In order to design sustainable urban transport systems, the inclusion of the behaviors of different stakeholders is imperative. In this study, we formulated the interactions of behaviors between transport operator, landowner, workplace, residence, route and mode choices, and location of firms and businesses through a combined unified model of land-use and transport system. The commuters have two mode choices for traveling: private car and public bus. They are inclined to choose a transit mode with minimum traveling costs. We combined two models, maximization of operator profit constrained by bus frequency, while maintaining the formulation of other stakeholders through an assignment sub-model. The resulting formulation is bi-level, which is optimally solved for a small-sized instance containing two zones. The findings suggest that if the bus fare is reduced, the demand of public bus is increased. However, the operators’ profit is optimized within a certain range of fares and is lowered when the fare is too low or too high. It is determined that maximum bus frequency does not guarantee maximum profit to the service operator. The impacts of traveling costs on residence choice behavior suggest that if link fares are more, many of people opt not to travel between different zones. The analysis results presented in this paper are calculated for two types of link fares: a fixed fare (30 currency), and a range of link fare (5 to 100 currency). Different variants of the same formulation can be applied for real settings to better comprehend the nature of the model and its applications.

While most existing closed-form discrete choice models can be regarded as special cases of McFadden's generalized extreme value model, recently, alternative frameworks of McFadden's generalized extreme value model, which maintain closed-form expressions, have been proposed; these include the weibit model, which uses the Weibull distribution for its random component. In this paper, we develop a generalized closed-form discrete choice model which include both logit and weibit models as special cases, by introducing the q-product random utility, in which the relationship between the systematic component and the random component can be either additive, multiplicative, or in-between, depending on the value of the parameter q . We show that, when imposing the Gumbel distribution on its error component (instead of assuming the additive case as the logit model), the parameter q depicts decision maker's risk attitude in the sense of the Arrow–Pratt measure of relative risk aversion, which would be a behavioral foundation of the model. We also show that the model can be straightforwardly extended to incorporate statistical dependence across alternatives. The performance of the proposed model is examined by using two case studies; one on travel-route choices and the other on transport-mode choices.

金沢大学融合研究域融合科学系, To estimate travel times through road networks, in this study, we assume a stochastic demand and formulate a stochastic network equilibrium model whose travel times, flows, and demands are stochastic. This model enables us to examine network reliability under stochastic circumstances and to evaluate the effect of providing traffic information on travel times. For traffic information, we focus on travel time information and propose methods to evaluate the effect of providing that information. To examine the feasibility and validity of the proposed model and methods, we apply them to a simple network and the real road network of Kanazawa, Japan. The results indicate that providing ambulance drivers in Kanazawa with travel time information leads to an average reduction in travel time of approximately three minutes. © 2016., Embargo Period 24 months

This study proposes a generalized multinomial logit model that allows heteroscedastic variance and flexible utility function shape. The novelty of our approach is that the model is theoretically derived by applying a generalized extreme-value distribution to the random component of utility, while retaining its closed-form expression. In addition, the weibit model, in which the random utility is assumed to follow the Weibull distribution, is a special case of the proposed model. This is achieved by utilizing the q-generalization method developed in Tsallis statistics. Then, our generalized logit model is incorporated into a transportation network equilibrium model. The network equilibrium model with a generalized logit route choice is formulated as an optimization problem for uncongested networks. The objective function includes Tsallis entropy, a type of generalized entropy. The generalization of the Gumbel and Weibull distributions, logit and weibit models, and network equilibrium model are formulated within a unified framework with q-generalization or Tsallis statistics. © 2015 Elsevier Ltd., Embargo Period 24 months

This study proposes a generalized multinomial logit model where heteroscedastic variance and flexible shape of utility function are allowed. The novel point of our approach is that, while the model is theoretically derived by applying a generalized extreme value distribution to the random component of utility, the model maintains its closed-form expression. Also, the weibit model, where the random utility is assumed to follow the Weibull distribution, is a special case of the proposed model. This is achieved by utilizing q -generalization method developed in Tsallis statistics. Then, the generalized logit model is incorporated into a transportation network equilibrium model. The network equilibrium model with the generalized logit route choice is formulated as an optimization problem under uncongested networks. The objective function includes Tsallis entropy, which is a type of generalized entropy. The generalization of the Gumbel and Weibull distributions, logit and weibit models, and network equilibrium model is made within a unified framework with q -analysis or Tsallis statistics.

Traffic flows in real-life transportation systems vary on a daily basis. According to traffic flow theory, such variability should induce a similar variability in travel times, but this "internal consistency" is generally not captured by existing network equilibrium models. We present an internally-consistent network equilibrium approach, which considers two potential sources of flow variability: (i) daily variation in route choice and (ii) daily variation in origin-destination demand. We particularly aspire to a flexible formulation that permits alternative statistical assumptions, which allows the best fit to be made to observed variability data in particular applications. Joint probability distributions of route-and therefore link-flows are derived under several assumptions concerning stochastic driver behavior. A stochastic network equilibrium model with stochastic demands and route choices is formulated as a fixed point problem. We explore limiting cases which allow an equivalent convex optimization problem to be defined, and finally apply this method to a real-life network of Kanazawa City, Japan. © 2014 Elsevier Ltd., Embargo Period 24 months

The multinomial logit model is expressed as a closed-form equation, and plays an important role in the field of tra sportation. The Gumbel-distributed utility in the multinomial logit model is restrictive in certain applications, especially in ro te choice behavior and network equilibrium analysis, although it is mathematically convenient. The range of variation of utility in the logit model is unbounded. The Gumbel distribution is left-skewed and has a very thi tail to the left. In additionFor example, the utility in the multinomial logit has a the homogeneity of homosce astic variance. In this study, the multinomial logit model is extended by generalizing the Gumbel-distributed utility to allow heteroscedastic variance and flexible shape. Then, the generalized logit model with a generalized Gumbel distribution is incorporated into the transportation network equilibrium model. The network equilibrium model with a generalized logit route choice is formulated as an optimization problem under uncongested networks. The objective function includes Tsallis entropy, which is a type of generalized entropy. In this study, the generalization of the Gumbel distribution, logit model, and network equilibrium model has a unified framework with q-analysis or Tsallis statistics.

This article formulates a discrete-time dynamic traffic assignment (DTA) model and, under certain conditions, shows the existence and uniqueness of network equilibrium. Several theoretical issues need to be tackled. The inflow to a link in a particular discrete (time) period does not necessarily exit within the same period. We consider how flow is passed from one link and period to the next, and the corresponding costs. Under the proposed model, flow departing within a discrete period may experience different link travel times in different discrete periods, even if the flow chooses a single route. Route travel time must then be defined so that route and OD costs are meaningful. To this end, quasi-real route travel time is defined. Based on this definition, a quasi-equilibrium condition for DTA is proposed; a semi-dynamic analogue of user equilibrium. The existence and uniqueness of this equilibrium solution are proven. © 2013 © 2013 Hong Kong Society for Transportation Studies Limited., Embargo Period 12 months

Conditions on transportation networks vary significantly during the course of a day. Public transit and (private) automobiles constitute the actual forms of transportation that use such networks in many urban areas. Public transportation by rail is more reliable than by automobiles or buses; therefore, ordinary static and deterministic traffic assignment models with combined mode and route choices may not be suitable to assess a transportation network that includes public railways. In addition, within-day dynamics and reliability need to be incorporated in such a model. In this paper, the authors use a semi-dynamic traffic assignment model that considers within-day dynamics by improving the static traffic assignment model. Also, stochastic travel times are incorporated into the model. They propose a semi-dynamic traffic assignment model with mode choice between public transit and automobiles, route choice with stochastic travel times, and an accompanying computing algorithm. This model enables an assessment of within-day dynamics of transportation networks and travel time reliability of public railways.

交通ネットワークの状況は一日の中で大きく変化するため，従来までの静的な均衡配分（日配分）による交通量配分は十分ではないことが多いと考えられる．この問題に対応するために，これまでに時間帯別配分モデルが提案されている．しかし，既存の時間帯別モデルでは，時間帯間での交通量の扱いに問題があるものが多い．本研究では，リンク上の交通量が次の時間帯に残留することによって，交通ネットワーク上で混雑の時間・空間移動を記述することが可能な時間帯別配分モデルを提案する．そして，解の存在及び一意性を示す．さらに，そのモデルを仮想ネットワークに適用し，従来の時間帯別配分モデルの計算結果と比較することにより，モデルの特性や妥当性について検証する．

In this paper, we assume that network flow is normally distributed due to stochastic travel demands, and develop a stochastic model of semi-dynamic assignment that is able to consider congestion's time-space movement. Also, drivers' risk attitude to uncertain travel time is incorporated using the efficient travel time.We formulate the stochastic model of semi-dynamic assignment as a non-linear complementarity problem, and propose an algorithm with the conjugate gradient method. Further, the model is applied to Kanazawa road network and examine the validity of the model and applicability to a real-world network

Drawing from the literature on the minority game, this study proposes that predictive travel time information provided to drivers to assist with their route choices may not influence network flow; under the condition that route choices are made repeatedly by the same group of drivers, the drivers self-organize to reach the same network equilibrium regardless of the contents of the predictive travel time information given. A numerical example supports this conjecture by showing that improvements in network flow are negligibly small even when precise information on travel time is provided. If no predictive information is present, the results of agent-based route choice simulation studies indicate that higher levels of the cognitive capabilities of drivers tend to produce more self-organization and stable network flows and that information on those routes a driver did not take is important for this self-organization.

現実の交通ネットワークでは，様々な要因によりその交通量や旅行時間は日々変動している．事故や災害などが生じていない通常の交通状況下では，交通量・旅行時間の変動の主要な原因の一つは，交通需要の変動である．本研究では，交通需要が正規分布に従って確率変動するとともに，配分された交通量も正規分布に従う確率的な交通ネットワーク均衡モデルを提案する．このモデルは現実の交通ネットワークの不確実性や時間信頼性の評価を可能とするものである．そして，そのモデルを金沢市の道路ネットワークに適用し，金沢道路ネットワークの旅行時間の不確実性・信頼性評価を行う．さらに，推定した金沢道路ネットワークの旅行時間の確率変動下で，緊急車両に情報提供を行うことの効果分析を行う．

This study introduces an ecotravel coordinator program to reduce car use. In this system, ecotravel coordinators are put in charge of several people. They organize ecotravel meetings and are responsible for taking the initiative. During the meetings participants recognize and deepen their understanding of their travel behaviors and devise their own plans for reducing car use. The aim of this study is to examine the validity of the ecotravel coordinator program through an experimental method. One result of the experiments was that the ecocoordinators and the other participants reduced their car travel mileage 54% and 48%, respectively. Nonparticipants, however, almost never reduced their travel mileage (1.4% reduction). Thus, experiment results indicate that the system is fairly effective for reducing car use.

The residents' participatory bus management needs residents' self-direction. But almost people lacks it's self-direction. so the leadership of administration is in need. In this paper, we verify the possibility of bus planning's success by residents under the leadership of administration. We can make clear that, the planning is effective, if we consider demands of local residents enough.

人々が移動する場合, 単に所要時間 (旅行時間) が短いだけでなく, 確実に到着出来ることを求めていることが多く, 交通計画や交通管制等の際, 単に旅行時間だけでなく, その不確実性等を評価することが不可欠である. しかし, 確率的利用者均衡は経路選択に確率的効用理論 (ランダム効用理論) を用いているだけであり, ワードロップ均衡と同様に配分される交通量や旅行時間は確定的である. 以上のように従来の均衡モデルでは, 交通ネットワークの不確実性や時間信頼性を十分に評価することは出来ないことが分かる. そこで, 本研究では, 交通ネットワークの不確実性や時間信頼性の評価等に必要となる, 交通量及び旅行時間が確率分布であるネットワーク均衡モデルを定式化する. そして, そのモデルを金沢市の道路ネットワークに適用し, 現況再現性やモデルの妥当性について検討する.

In general, it is difficult to investigate social phenomena mathematically or quantitatively due to non-linear interactions. Statistical physics can provide powerful methods for studying social phenomena with interactions, and could be very useful for them. In this study, we take a focus on fashion as a social phenomenon with interaction. The social interaction considered here are “bandwagon effect” and “snob effect.” In the bandwagon effect, the correlation between one's behavior and others is positive. People feel fashion weary or boring when it is overly popular. This is the snob effect. It is assumed that the fashion phenomenon is formed by the aggregation of individual's binary choice, that is, the fashion is adopted or not. We formulate the fashion phenomenon as the logit model, which is based on the random utility theory in social science, especially economics. The model derived here basically has the similarity with the pioneering model by Weidlich (Phys. Rep. 204 (1991) 1), which was derived from the master equation, the Langevin equation, or the Fokker–Planck equation. This study seems to give the behavioral or behaviormetrical foundation to his model. As a result of dynamical analysis, it is found that in the case that both the bandwagon effect and the snob effect work, periodic or chaotic behavior of fashion occurs under certain conditions.

本研究では, 人々に直接自動車利用を抑制するように訴えることによって自動車利用が減少するのかを検討するために, 主婦・会社員の一般の被験者および学生の被験者に自動車利用抑制を要請し, パネル的なアンケート調査により, 自動車利用の変化を調査した. 統計的検定の結果から, 要請により, 一般の被験者は自動車利用を抑制する傾向があり, 特に主婦は有意に自動車利用を抑制することが分かった. しかし, 学生は要請によっては自動車利用を抑制する傾向は見られず, 個人属性により要請に効果があるのかが異なる結果となった. 元々環境意識が高かった被験者と低かった被験者に分類し, 検定を行った結果, 元々高かった被験者はそれ以上環境意識を向上させ, 自動車利用を減少させることは難しく, むしろ, 元々は低かった人の方が環境意識の向上・自動車利用の抑制が見られた.

We make an analysis of vehicles' behavior and their decision-makings at the merging points on the public road and the expressway. In this paper, we examine the factors and the mechanism of gap choice behavior of merging vehicles and the difference between the public road and the expressway, in which the traveling velocities and the lengths of merging points are largely different. Then, we construct a fuzzy model of gap choice behavior based on the analysis results. Also, we investigate the spots where the vehicles turn the wheel and start merging or changing the lane, and make its fuzzy model.

In most of logit models, linear utility functions have frequently been used. We propose a utility function with neural network, and make a logit model with it. We apply the model to the giveway behavior at the merging point on the road, and examine the validity of the model. As a result, it is founded that the logit model with neural network utility function describes the giveway behavior more elaborately than the conventional logit model and its goodness of fit is also better. Thus, we confirm that the logit model with neural network utility function is valid.