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Koki Satsukawa

Publications and source records attributed to Koki Satsukawa.

10 recordsLinked to original sources

Flexible and Reliable Network Design for Emerging Transportation Services: Multi-stage Stochastic Programming Approach

This paper proposes a general framework for flexible and reliable network design problems (FR-NDPs). The framework enables planners to change infrastructure investments in response to realized uncertainties, while ensuring desired levels of reliability. Motivated by emerging transportation services such as shared autonomous vehicle (SAV) systems, where historical data are scarce and technological developments uncertain, FR-NDPs integrate strategic investment decisions with operational control. We formulate the FR-NDPs as risk-averse multi-stage stochastic problems to be solvable by stochastic dual dynamic programming (SDDP) and establish sufficient conditions under which strategic and operational subproblems converge to the global optimum. We illustrate applications to SAV capacity expansion and integrated SAV-BRT (Bus Rapid Transit) route design, and numerical experiments on a Midtown Manhattan network highlight three key findings: (i) flexibility and reliability act complementarily to hedge against severe scenarios while mitigating the loss of expected performance; (ii) flexibility in investment planning allows dynamic risk hedging, with risk-averse planners reducing early-stage investments to preserve adaptability; and (iii) differences in operational flexibility between SAV and BRT systems are reflected in strategic decisions, with risk-averse planners tending to refrain investment in transport modes with lower operational flexibility.

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Queue Replacement Approach to Dynamic User Equilibrium Assignment with Route and Departure Time Choice

This study develops a hybrid analytical and numerical approach for dynamic user equilibrium (DUE) assignment with simultaneous route and departure time choice (RDTC) for homogeneous users. The core concept of the proposed approach is the generalized queue replacement principle (GQRP), which establishes an equivalence between the equilibrium queueing-delay pattern and the solution to a linear programming (LP) problem obtained by relaxing some conditions in the original DUE-RDTC problem. We first present a method for determining whether the GQRP holds. Based on the GQRP, we then develop a systematic procedure to obtain an exact DUE solution by sequentially solving two LPs: one for the equilibrium cost pattern, including queueing delays, and the other for the corresponding equilibrium flow pattern. Computational results on networks of varying scales confirm the effectiveness of the proposed method.

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A bottleneck model with shared autonomous vehicles: Scale economies and price regulations

This study examines how scale economies in the operation of shared autonomous vehicles (SAVs) affect the efficiency of a transportation system where SAVs coexist with normal vehicles (NVs). We develop a bottleneck model where commuters choose their departure times and mode of travel between SAVs and NVs, and analyze equilibria under three SAV fare-setting scenarios: marginal cost pricing, average cost pricing, and unregulated monopoly pricing. Marginal cost pricing reduces commuting costs but results in financial deficits for the service provider. Average cost pricing ensures financial sustainability but has contrasting effects depending on the timing of implementation due to the existence of multiple equilibria: when implemented too early, it discourages adoption of SAVs and increases commuting costs; when introduced after SAV adoption reaches the monopoly equilibrium level, it promotes high adoption and achieves substantial cost reductions without a deficit. We also show that expanding road capacity may increase commuting costs under average cost pricing, demonstrating the Downs--Thomson paradox in transportation systems with SAVs. We next examine two optimal policies that improve social cost, including the operator's profit: the first-best policy that combines marginal cost pricing with congestion tolls, and the second-best policy that relies on fare regulation alone. Our analysis shows that these policies can limit excessive adoption by discouraging overuse of SAVs. This suggests that promoting SAV adoption does not always reduce social cost.

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A Paradox of Telecommuting and Staggered Work Hours in the Bottleneck Model

We study the long- and short-term effects of telecommuting (TLC), staggered work hours (SWH), and their combined scheme on peak-period congestion and location patterns. In order to enable a unified comparison of the schemes' long- and short-term effects, we develop a novel equilibrium analysis approach that consistently synthesizes the long-term equilibrium (location and percentage of telecommuting choice) and short-term equilibrium (preferred arrival time and departure time choice). By exploiting their special mathematical structures similar to optimal transport problems, we derive the closed-form solution to the long- and short-term equilibrium while explicitly considering their interaction. These closed-form solutions elucidate the discrepancies between the effects of each scheme and uncover a paradoxical finding: the introduction of SWH, in conjunction with TLC, may increase the total commuting costs compared to the scenario with only TLC, without yielding any improvement in worker utility.

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Queue replacement principle for corridor problems with heterogeneous commuters

This study investigates the theoretical properties of a departure time choice problem considering commuters' heterogeneity with respect to the value of schedule delay in corridor networks. Specifically, we develop an analytical method to solve the dynamic system optimal (DSO) and dynamic user equilibrium (DUE) problems. To derive the DSO solution, we first demonstrate the bottleneck-based decomposition property, i.e., the DSO problem can be decomposed into multiple single bottleneck problems. Subsequently, we obtain the analytical solution by applying the theory of optimal transport to each decomposed problem and derive optimal congestion prices to achieve the DSO state. To derive the DUE solution, we prove the queue replacement principle (QRP) that the time-varying optimal congestion prices are equal to the queueing delay in the DUE state at every bottleneck. This principle enables us to derive a closed-form DUE solution based on the DSO solution. Moreover, as an application of the QRP, we prove that the equilibrium solution under various policies (e.g., on-ramp metering, on-ramp pricing, and its partial implementation) can be obtained analytically. Finally, we compare these equilibria with the DSO state.

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Stability analysis of a departure time choice problem with atomic vehicle models

In this study, we analyse the global stability of the equilibrium in a departure time choice problem using a game-theoretic approach that deals with atomic users. We first formulate the departure time choice problem as a strategic game in which atomic users select departure times to minimise their trip cost; we call this game the 'departure time choice game'. The concept of the epsilon-Nash equilibrium is introduced to ensure the existence of pure-strategy equilibrium corresponding to the departure time choice equilibrium in conventional fluid models. Then, we prove that the departure time choice game is a weakly acyclic game. By analysing the convergent better responses, we clarify the mechanisms of global convergence to equilibrium. This means that the epsilon-Nash equilibrium is achieved by sequential better responses of users, which are departure time changes to improve their own utility, in an appropriate order. Specifically, the following behavioural rules are important to ensure global convergence: (i) the adjustment of the departure time of the first user departing from the origin to the corresponding equilibrium departure time and (ii) the fixation of users to their equilibrium departure times in order (starting with the earliest). Using convergence mechanisms, we construct evolutionary dynamics under which global stability is guaranteed. We also investigate the stable and unstable dynamics studied in the literature based on convergence mechanisms, and gain insight into the factors influencing the different stability results. Finally, numerical experiments are conducted to demonstrate the theoretical results.

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Global stability of day-to-day dynamics for schedule-based Markovian transit assignment with boarding queues

Schedule-based transit assignment describes congestion in public transport services by modeling the interactions of passenger behavior in a time-space network built directly on a transit schedule. This study investigates the theoretical properties of scheduled-based Markovian transit assignment with boarding queues. When queues exist at a station, passenger boarding flows are loaded according to the residual vehicle capacity, which depends on the flows of passengers already on board with priority. An equilibrium problem is formulated under this nonseparable link cost structure as well as explicit capacity constraints. The network generalized extreme value (NGEV) model, a general class of additive random utility models with closed-form expression, is used to describe the path choice behavior of passengers. A set of formulations for the equilibrium problem is presented, including variational inequality and fixed-point problems, from which the day-to-day dynamics of passenger flows and costs are derived. It is shown that Lyapunov functions associated with the dynamics can be obtained and guarantee the desirable solution properties of existence, uniqueness, and global stability of the equilibria. In terms of dealing with stochastic equilibrium with explicit capacity constraints and non-separable link cost functions, the present theoretical analysis is a generalization of the existing day-to-day dynamics in the context of general traffic assignment.

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Non-existence of queues for system optimal departure patterns in tree networks

This study proves the non-existence of queues for a dynamic system optimal (DSO) departure pattern in a directed rooted tree network with a single destination. First, considering queueing conditions explicitly, we formulate the DSO problem as mathematical programming with complementarity constraints (MPCC) that minimizes the total system cost which consists of the schedule and queueing delay costs. Next, for an arbitrary feasible solution to the MPCC, we prove the existence of another feasible solution where the departure flow pattern on every link is the same but no queue exists. This means that the queues can be eliminated without changing the total schedule delay cost. Queues are deadweight losses, and thus the non-existence theorem of queues in the DSO solution is established. Moreover, as an application of the non-existence theorem, we show that the MPCC can be transformed into a linear programming (LP) problem by eliminating the queueing conditions.

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Dynamic traffic assignment in a corridor network: Optimum versus Equilibrium

This study investigates dynamic system-optimal (DSO) and dynamic user equilibrium (DUE) traffic assignment of departure/arrival-time choices in a corridor network. The morning commute problems with a many-to-one pattern of origin-destination demand and the evening commute problems with a one-to-many pattern are considered. Specifically, a novel approach to derive closed-form solutions for both DSO and DUE problems is developed. We first derive a closed-form solution to the DSO problem based on the regularities of the cost and flow variables at an optimal state. By utilizing this solution, we prove that the queuing delay at a bottleneck in a DUE solution is equal to an optimal toll that eliminates the queue in a DSO solution under certain conditions of a schedule delay function. This enables us to derive a closed-form DUE solution by using the DSO solution. We also show the theoretical relationship between the DSO and DUE assignment. Numerical examples are provided to illustrate and verify the analytical results.

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Dynamic system optimal traffic assignment with atomic users: Convergence and stability

In this study, we analyse the convergence and stability of dynamic system optimal (DSO) traffic assignment with fixed departure times. We first formulate the DSO traffic assignment problem as a strategic game wherein atomic users select routes that minimise their marginal social costs, called a 'DSO game'. By utilising the fact that the DSO game is a potential game, we prove that a globally optimal state is a stochastically stable state under the logit response dynamics, and the better/best response dynamics converges to a locally optimal state. Furthermore, as an application of DSO assignment, we examine characteristics of the evolutionary implementation scheme of marginal cost pricing. Through theoretical comparison with a fixed pricing scheme, we found the following properties of the evolutionary implementation scheme: (i) the total travel time decreases smoother to an efficient traffic state as congestion externalities are perfectly internalised; (ii) a traffic state would reach a more efficient state as the globally optimal state is stabilised. Numerical experiments also suggest that these properties make the evolutionary scheme robust in the sense that they prevent a traffic state from going to worse traffic states with high total travel times.

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