In major metropolitan areas, ride-sharing systems can help reduce traffic congestion and increase the transportation system’s efficiency. In this paper, we propose a Branch-and-Price based approach for solving the ride-share routing problem with flexible pickup and drop-off points. We assume a ride-sharing system where drivers have their own origins and destinations, where all the drivers’ and passengers’

Liquefied natural gas (LNG) is increasingly viewed as a promising fuel for dual-fuel ships due to its cost-effectiveness, low emissions, and alignment with regulatory requirements. However, the high methane content of LNG, ranging from 85% to 95%, presents a significant challenge because of the phenomenon of methane slip whereby unburned methane escapes from the engine’s combustion chamber and other

Instantaneous traffic queues, introducing fluctuated queuing delays, significantly affect the journey times and route choices of travelers particularly during the peak hour periods in congested road networks. Distinguished from average residual queues in static traffic assignment problems, instantaneous queues form and dissipate within minuscule time frames of a modeling period, triggered by an inflow

In this paper, we address the classical liner fleet deployment and slot allocation joint optimization problem in the maritime field with uncertain container transportation demand. We relax the assumption in existing studies that the demand distribution function is known because container transportation demand is deeply affected by the world’s economic and political landscape. With the help of advances

Rapid post-disruption recovery is essential but challenging, given the complex interactions between vehicular flows and the network supply. Simulation-based methods are widely used to assist the planner with realistic user-system interactions in the recovery measure optimization, though the application to large-scale transportation networks remains computationally expensive. This study explores the

The transit network design and frequency-setting problem (TNDFSP) plays a critical role in urban transit system planning. Due to the conflict between the level of service and operating costs, extensive research has been conducted to obtain a set of trade-off solutions between the interests of users and operators. However, most studies ignored the effects of station congestion in TNDFSP, resulting in

Traffic shockwaves, as the boundary of distinct traffic states, capture the temporal-spatial characteristics of traffic fluctuation formation and propagation. Monitoring shockwaves facilitates real-time traffic management and control to improve traffic efficiency and safety. However, detecting shockwaves is challenging due to the complex nature of traffic dynamics and limited data collection. Existing

Capacity drop, a traffic phenomenon indicating that the discharge flow from a queue is lower than the pre-queue flow, is commonly observed at freeway bottlenecks. In the literature, the majority of empirical studies on capacity drop rely on aggregated traffic flow data. To fully understand the mechanism behind capacity drop, it is essential to analyze trajectory data, which captures the microscopic

Using a game theoretic approach, this paper explores a futuristic passenger-freight co-modality system that leverages autonomous modular vehicle (AMV) technology. In our model, a transit operator and a freight carrier operate within a stylized city, transporting passengers and parcels, respectively. The freight carrier can rent the transit operator’s underutilized transport capacity during off-peak

This study investigates the optimal decisions of airports regarding charges, capacity, and passengers’ suggested arrival time at the airport (before flight departures) under different objectives (maximizing airport profit or social welfare). Our model incorporates an airport, airlines with market power, and passengers, and examines the impact on concession revenue of dwell time in (terminal) retail

Disturbances occur inevitably during daily operations of the metro system, leading to train delays and low service quality. Different from common deterministic reactive train rescheduling frameworks, taking the inherent uncertain characteristic of disturbance into account, this paper formulates a two-stage stochastic programming model to address the integration of proactive backup rolling stock allocation

This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport

Allocating land for public housing is an essential step in providing affordable housing for low-income citizens, as practiced in Hong Kong and Singapore. Locating public housing projects in suburban areas causes a spatial mismatch between public housing tenants and job opportunities, while placing public units in urban areas exacerbates the shortage of urban land, which may result in a more compact

Recent empirical and theoretical findings highlight the critical role of stochasticity in car-following (CF) dynamics. Although several stochastic CF models have been proposed, their calibration remains relatively underexplored compared to deterministic models. This article addresses this gap by utilizing four stochastic CF models to conduct a comprehensive evaluation of two existing calibration methods—minimizing

This paper explores the government's strategies to persuade multiple transport facility operators to undertake adaptation projects, particularly within the Asian doctrine governance regime, where the government exerts significant influence over facility operations. We develop a Bayesian persuasion model to analyze these strategies, focusing on the spillover effects among operators' projects and their

The paper presents a robust control method for effectively managing uncertainties and communication loss in a connected automated vehicle (CAV) platoon under the multiple-predecessor following (MPF) topology. The proposed approach incorporates uncertainties in vehicle dynamics, such as vehicle parameters and environmental resistances, into the closed-loop platoon system to enhance the robustness of

Long-term tactical infrastructure planning for a transportation network consists of deciding on renewals and major maintenance works. Such projects constitute large budget volumes and will impair the available traffic capacity during their execution, especially for railway systems. Quantitative methods that schedule and coordinate infrastructure projects together with traffic flow adaptations is however

We propose a nonparametric mixed logit model that is estimated using market-level choice share data. The model treats each market as an agent and represents taste heterogeneity through market-specific parameters by solving a multiagent inverse utility maximization problem, addressing the limitations of existing market-level choice models with parametric estimation. A simulation study is conducted to

Mixed transportation of passengers and freights is an effective strategy for reducing environmental pollution and improving the service level of railway systems. This study addresses the problem of robust train composition and carriage arrangement for the mixed transportation of passengers and freights in a high-speed railway (HSR) network. Specifically, a network-based robust optimization (RO) model

This paper studies the relative performance of congestion pricing versus tradable permits for a congested bi-modal transport system with traffic externalities, that affect passengers only, and societal externalities that go beyond the passengers. The point in this case is infection risks, as in the pandemic. We study this relative performance for the case where there are uncertainties on both traffic

The mass rapid transit (MRT) systems play a pivotal role in urban mobility services but are frequently susceptible to various disruptions. Bus bridging service is a widely-applied substitute transit service in response to MRT disruptions, which requires a significant number of buses to transport stranded MRT passengers. In practical applications, these buses may be dispatched from the nearby bus lines

Under dynamic traffic demand conditions, two issues must be addressed when perimeter control is implemented for congested areas of a road network. The first is to avoid intersection spillback at the boundaries and expansion of the congestion, and the second is to improve the output traffic efficiency of the congested areas to quickly relieve traffic congestion. To address these two issues and solve

This paper investigates solution methods for train eco-driving problems that include the classic single-train eco-driving problem, the single-train eco-driving problem with intermediate time-window constraints, and the eco-driving problem for a fleet of trains under the green-wave policy. The latter two problems are particularly relevant in modern, busy railway networks. We start from proposing a relaxed

In a macroscopic assignment model, traffic flows are distributed onto the network by means of a network loading model. The network loading propagates flows along links via a link model and through junctions or intersections via a node model. Most of the travel time delays are caused by queues forming at junctions or intersections, especially in urban networks. Therefore, the efficiency and accuracy

We initiate the study of dynamic traffic assignment for electrical vehicles addressing the specific challenges such as range limitations and the possibility of battery recharge at predefined charging locations. As our main result, we establish the existence of energy-feasible dynamic equilibria within networks using the deterministic queuing model of Vickrey for the flow dynamics on edges.

The bottleneck model has dominated the field on dynamic congestion, as it is tractable and has closed-form solutions. But it has rather specific outcomes that do not occur in most other dynamic models or under static congestion. In the bottleneck model, pricing can remove all travel delays while keeping the generalized price unchanged, making pricing much more beneficial than in other models. Thus

This paper presents a game-theoretical model of road pricing. The model incorporates an endogenized demand and path-choice user-equilibrium with variable user demand and multiple user classes. Different to most of the literature, the proposed model allows to compute in a direct way the optimal tolls, rather than by trial and error of exogenous toll values and tackles the problem of inactive paths that

Conventional intersection management relies on traffic signals to coordinate conflicting traffic flows and distribute right-of-way. However, delays caused by traffic signals remain a major burden on urban transportation systems. Emerging connected automated vehicles (CAVs) are expected to improve the intersection management by coordinating vehicle movements without relying on traffic signals. Hence

We address a multi-class traffic model, for which we computationally assess the ability of mean-field games (MFGs) to yield approximate Nash equilibria for traffic flow games of intractable large finite-players. We introduce ad hoc numerical methodologies, with recourse to techniques such as High-Performance Computing (HPC) and regularization of Loose Generalized Minimal Residual (LGMRES) solvers.

Revealing the inherent relationships among traffic flow characteristics, fundamental diagram has long been regarded as one of the pillars of traffic flow theory since Greenshields seminal work. When it is combined with the law of (mass/vehicle) conservation, dynamic modelling of traffic flow at the macroscopic level such as LWR and others have thrived. This paper shows that fundamental diagram is only

Emerging autonomous vehicle (AV) technology is expected to bring substantive benefits to the transportation systems. This study focuses on the improvement of travel efficiency in transportation networks with AVs. Inspired by the concept of price of anarchy (PoA), we introduce a novel indicator, the benefit of vehicle automation (BVA), to quantify the efficiency benefit brought by AVs. The BVA is defined

There is growing interest in employing non-normal parameter distributions on covariates to account for random taste heterogeneity in multinomial choice models. In this study, we propose a flexible, computationally tractable, structurally simple, and parsimonious-in-specification random coefficients multinomial probit (MNP) model that can accommodate non-normality in the random coefficients. Our proposed

Transportation networks are crucial for social and economic activities but are susceptible to disruptions. Rapid quantification of the impacts of network disruptions can assist in planning recovery efforts. However, gathering timely and comprehensive information for assessing transportation network state is often challenging and not always possible. This study introduces a network assessment strategy

This paper investigates the effects of new airport on a multi-airport system (MAS) with air-rail integration service and heterogeneous passengers. Vertical structure models are proposed to capture the interactions among the stakeholders: passengers, airlines, and rail operator. In the proposed models, passenger heterogeneity is reflected by a continuous value-of-time (VOT) distribution, and the total

This study explores the optimal decisions of airports on charge, capacity, and suggested passengers’ arrival time at the airport under various regulatory regimes (e.g., single- or dual-till regulation). By considering both aeronautical- and non-aeronautical businesses and further incorporating the non-linear relationship between queuing time in the check-in zone and shopping time in the retail zone

This paper investigates the impact of external uncertainty on morning commute behavior when autonomous vehicles (AVs) are introduced and interact with human-driven vehicles (HVs). We adopt the bottleneck model to study the morning commuting dynamics. In this context, we consider two potential benefits for AVs, i.e., value-of-time (VOT) compensation/reduction and capacity enhancement. We develop an

Under regular metro operation conditions, one critical bottleneck to improving metro transportation capacity is fixed-length train compositions. These fixed-length compositions are mandated to not exceed station platform lengths, thereby limiting the potential for increasing capacity to effectively accommodate oversaturated passenger demand. To this end, we focus on a flexible metro operating system

This paper constructs two-stage Nash Bargaining models to examine two types of capacity purchase agreements (CPAs) for regional airlines: one with a local government and one with a network airline. The study compares the impacts of both CPAs on airline profits, consumer surplus, and social welfare. The results show that within a specific bargaining parameter range, both CPAs increase airline profits

Supply chain (SC) has been increasingly challenged by disruption events (DEs), where super DEs (SDEs) comprising a sequence of DEs, e.g., COVID-19, pose significant threats with long-term impacts. To hedge against SDEs, SC viability has been introduced, whose distinctive feature is the ability to adapt the SC structure. Building SC viability via dynamic SC structural adaptation under SDEs, however

Disruptions on the railway network can lead to reduced availability of the railway infrastructure, which requires rolling stock dispatchers to adjust the planning of the rolling stock. In this paper, we develop fast rolling stock rescheduling methods which ensure feasibility with respect to the availability of the railway infrastructure. In particular, we explore the option of performing shunting movements

The basic corridor problem is significant for the study of traffic congestion and travel behavior, paving way to insights into the spatial dynamics of rush-hour traffic flow pattern. In light of the fact that previous studies have yielded only preliminary results, this paper considers both early and late commuters to provide more comprehensive results. By introducing the continuous schedule preference

This paper addresses traffic merging at highway intersections (labeled as OMM intersections) where mainline traffic with multiple lanes and on-ramp traffic converges, which often represent traffic bottlenecks causing severe traffic congestion and safety issues. To do that, we developed a Compliance-constrained Resilient System Optimal Trajectory Planning (CR-SOTP), which is devised as an event-triggered

Intercity multimodal transportation systems hold great promise for enhancing travel, boosting regional economies, and promoting sustainability. However, realizing their full potential hinges on effective cooperation among transport service providers (TSPs), which current practices often lack. This study proposes a novel framework to address this challenge by leveraging price competition through mobility

This study investigates an automotive maritime transportation planning problem, considering roll-on/roll-off (Ro-Ro) shipping and container shipping. Automobiles are distributed from a manufacturer to overseas dealers through maritime transportation. This transportation process involves three key decisions: the choice of maritime transportation mode for the automobiles, the shipping volume of the ships

Improving redundancy is one way of enhancing transportation network resilience by providing travelers with more alternative travel options in case of disastrous events. This paper studies an alternative means of improving network redundancy via retrofitting critical components at the strategical level, which is less constrained by the land use limitation and is less costly compared to building new

We analyse time-varying tolling in the stochastic bottleneck model with price-sensitive demand and uncertain capacity. We find that price sensitivity and its interplay with uncertainty have important implications for the effects of tolling on travel costs, welfare and consumers. We evaluate three fully time-variant tolls and a step toll proposed in previous studies. We also consider a uniform toll

This paper presents a contextual framework for solving the experience-driven traveling salesman problem in last-mile delivery. The objective of the framework is to generate routes similar to historic high-quality ones as classified by operational experts by considering the unstructured and complex features of the last-mile delivery operations. The framework involves learning a transition weight matrix

We develop interactive optimization algorithms for biobjective problems with continuous nondominated frontiers to search for the most preferred solution of a decision maker who is assumed to have an underlying linear or quasiconvex preference function. We progressively acquire preference information from the decision maker through pairwise comparisons of efficient solutions. We keep reducing the search

Optimizing traffic signal control is crucial for improving efficiency in congested urban environments. Current adaptive signal control systems predominantly rely on on-road detectors, which entail significant capital and maintenance costs, thereby hindering widespread implementation. In this paper, a novel connected vehicle (CV)-based adaptive signal control (CVASC) framework is proposed that optimizes

In one-way carsharing systems, striking a balance between vehicle supply and user demand across stations poses considerable operational challenges. While existing research on vehicle relocation, personnel dispatch, and trip pricing have shown effectiveness, they often struggle with the complexities of fluctuating and unpredictable demand and supply patterns in uncertain environments. This paper introduces

In response to increasingly stringent green regulations, ocean carriers are transitioning their emissions reduction strategy from reducing ship speeds to investing in green equipment. However, because carriers face uncertain demand and a competitive freight market, it is challenging for them to determine the timing and size of green equipment investments. Hence, we construct a real options game (ROG)

People repeatedly demand travel, using available vehicles scattered around space. What can justify vehicle withholding (i.e. preventing others from using it, for own future use) from the social welfare perspective? This paper investigates heterogeneity in the potential cost of search for alternative vehicles as such justification. It is shown that travellers whose search cost is substantially higher

The residual queue during a given study period (e.g., peak hour) is an important feature that should be considered when solving a traffic assignment problem under equilibrium for strategic traffic planning. Although studies have focused extensively on static or quasi-dynamic traffic assignment models considering the residual queue, they have failed to capture the situation wherein the equilibrium link

The gap acceptance framework is the theoretical basis for modelling traffic flow at intersections with a priority control. Reliable estimation methods for key gap acceptance parameters are important to more accurately predict key traffic performance measures such as capacity and delay. A notable challenge is that the critical gaps are not directly observable. Currently, the maximum likelihood estimator

This study investigates the impact of walking and e-hailing on the scale economies of on-demand mobility services. An analytical framework is developed to i) explicitly characterize the physical interactions between passengers and vehicles in the matching and pickup processes, and ii) derive the closed-form degree of scale economies (DSE) to quantify scale economies. The general model is then specified

The capacity region (CR) is a key index to characterize a dynamic processing system’s ability to handle incoming demands. It is a multidimensional space when the system has multiple origin–destination pairs where their service rates interact. An urban traffic network is such a system. Traffic congestion appears when its demand approaches or exceeds the upper frontier of its CR. Part I of this study

This paper considers a green vehicle routing problem termed the time-dependent green vehicle routing problem with time windows (TDGVRPTW). The TDGVRPTW is an extension of the green vehicle routing problem with time windows in green logistics. It considers time-dependent vehicle speed and aims to minimize carbon emissions. Since the travel times and carbon emissions between locations depend on the departure

This paper shows that, in a static traffic model with elastic demand, increasing a toll may raise the equilibrium trip rate through a network. The result is obtained in models with horizontal queues and rules about merges and diverges assumed in the Cell Transmission Model for Network Traffic. The paper looks at three networks: (i) a road with a fixed bottleneck at the end; (ii) a road with a “triggerneck”