Urban last-mile delivery providers are facing more and more challenges with the explosive development of e-commerce. The advancement of smart mobile and communication technology in recent years has stimulated the development of a new business model of city logistics, referred to as crowdsourced delivery or crowd-shipping. In this paper, we investigate a form of crowdsourced last-mile delivery that

In this paper, we consider the vehicle routing problem with load-dependent drones (VRPLD), in which the energy consumption of drones is load-dependent and represented by a nonlinear function. To strengthen the collaboration between trucks and drones, a kind of facility called the docking hub is introduced to extend the service coverage of drones. When a truck visits the hub, a part number of parcels

Traffic at urban intersections constitute a series of complex conflicting vehicular movements and contribute greatly to the problems of traffic congestion and air pollution. The emerging of connected and automated vehicle (CAV) technologies inspires innovative ideas in traffic management at intersections; it not only enables new control paradigms, but also allows for possibilities to revolutionize

This paper proposes a multi-port berth allocation problem (MPBAP) under a cooperative environment, which aims to determine berthing times and berthing positions for all considered vessels arriving at multiple neighboring ports. The previous studies on the MPBAP (or the BAP with multiple ports) consider that multiple ports have established stable cooperation, while the port cooperation stability problem

The need for monitoring the state of a traffic network versus the costly installation and maintenance of roadside sensors constitutes the tough sensor placement problem in designing transportation networks. Placement problems naturally lie in the category of subset selection problems, which are known to be inherently combinatorial, and therefore, finding their exact solution is intractable for large

Abstract not available

The increasing trend on adopting ride-sourcing services has brought obvious benefits to short-haul transportation systems. In this paper, we investigate a dynamic ride-sourcing system, where, in each period, a constant number of vehicles (fixed system capacity) is used to satisfy random customer demands or is reallocated within an under-investigation network. To save resources, our objective is to

Attended Home Delivery, where customer attendance at home is required, is an essential last-mile delivery challenge, e.g., for valuable, perishable, or oversized items. Logistics service providers are often faced no-show customers. In this paper, we consider the delivery problem in which customers can be revisited on the same day by a courier in the case of a failed first delivery attempt. Specifically

In metro system, the fault of traction power supply system may cause the power supply shortage around the failure substation. In this case, the dispatching measure should be immediately taken to reduce the impacts of disruption on the train operation. To deal with this real-time traffic management problem, a cooperative control approach is proposed in this paper. In this approach, the time to apply

This paper presents a mixed multinomial logit-based discrete choice modelling framework to accommodate decision-makers’ errors in perceiving choice environment variables that do not vary across choice alternatives. An analysis is undertaken to evaluate two different ways of specifying errors in the choice environment variables in discrete choice models – (a) the additive specification and (b) the multiplicative

We study the design of same-day delivery (SDD) systems under the assumption that service regions are allowed to vary over the course of the day; equivalently, that customers in different locations may have access to SDD for different lengths of time over the service day or may have no access at all. This contrasts with the bulk of the literature, in which a service region is defined in advance and

We propose an analytical model to theoretically and numerically examine the impact of the introduction of e-hailing services into a region with traditional public transit, considering transit-dependent people who cannot drive themselves. For simplicity, this study considers many-to-one trip demand in a monocentric linear city. Our theoretical investigations confirm that in the short term when the service

In the context of Mobility-as-a-Service (MaaS), the transportation sector has been evolving towards user-centric business models, which put the user experience and tailored mobility solutions at the center of the offer. The emerging concept of MaaS emphasizes that users value experience-relevant factors, e.g., service time, inconvenience cost, and travel delay, over segmented travel modes choices.

Based on the status quo-dependent route choice model in Xu et al. (2017), this study encapsulates the route choice model into traffic assignment modeling and establishes a Status quo-dependent User Equilibrium (SDUE) model. The proposed SDUE model adopts the adaptive value of time (VOT) to incorporate three kinds of route choice behavior: cognitive limitations and capability constraints, satisficing

This paper investigates the effect of airport expansion on air traffic and its implications on airport congestion, airline competition and the social welfare, considering various airport administrative regimes (i.e., profit-maximization, social welfare-maximization, and budget-constrained social welfare-maximization), airline market structures (i.e., perfectly competitive, oligopoly, monopoly, leader–follower)

We develop a theory of optimal aircraft size, where the cost of the flight crew is the primary factor driving the use of larger aircraft, while passenger utility is primary factor driving the use of smaller aircraft. After fitting our model to U.S. data, we perform a counterfactual experiment where the minimum crew size requirement is relaxed from two pilots to one, a policy currently being discussed

In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance

When there are significant service disruptions in public transit systems, passengers usually need guidance to find alternative paths. This paper proposes a path recommendation model to mitigate congestion during public transit disruptions. Passengers with different origins, destinations, and departure times are recommended with different paths such that the system travel time is minimized. We model

Ride-sourcing platforms, among other solution services, offer convenience and flexibility when it comes to pick-up/drop-off time and location. Similarly, ride-splitting renders itself as an extension of ride-sourcing where platform users agree to share their rides in return for a reduced fare yet possibly a longer travel time. Despite the numerous advantages that sharing introduced to the platform

We study a delivery strategy for last-mile deliveries in urban areas which combines freight transportation with mass mobility systems with the goal of creating synergies contrasting negative externalities caused by transportation. The idea is to use the residual capacity on public transport means for moving freight within the city. In particular, the system is such that parcels are first transported

In this study, we proposed a generic Bayesian optimization (BO) framework to solve congestion pricing problems. In the BO framework, the Gaussian process (GP) serves as a surrogate model to approximate the highly nonlinear and expensive-to-evaluate objective functions. This study reveals that GP exhibits an instability phenomenon, which inherently limits the accuracy of BO. We investigate the sources

We consider the route planning problem of an unmanned air vehicle (UAV) in a continuous space that is monitored by radars. The UAV visits multiple targets and returns to the base. The routes are constructed considering the total distance traveled and the total radar detection threat objectives. The UAV is capable of moving to any point in the terrain. This leads to infinitely many efficient trajectories

With the rapid increase in residents in megacities, the passenger demand of metro systems is rising sharply and steadily, bringing immense pressure to train operations. To improve the service quality, this paper discusses systematically investigating a joint optimization of the robust passenger flow control strategy and train timetable on a congested metro line. A deterministic model for train timetabling

In macroscopic dynamic network loading, the role of the node model is to determine transfer volumes between each in- and outgoing link, while respecting in a consistent way all forward and backward-moving traffic waves (or boundary conditions) and desired turning fractions. In addition, capacity constraints on the node itself need to be respected; they result from priority rules on conflict points

Deployment of drones in delivery operations has been attracting growing interest from the commercial sector due to its prospective advantages for a range of distribution systems. Motivated by the widespread adoption of drones in last-mile delivery, we introduce the minimum cost traveling salesman problem with multiple drones, where a truck and multiple drones work in synchronization to deliver parcels

This paper studies a new variant of the vehicle routing problem with drones, i.e., the two-echelon vehicle routing problem with drones, where multiple vehicles and drones work collaboratively to serve customers. Drones can perform multiple back-and-forth trips when their paired vehicle stops at a customer node, forming a two-echelon network. Several practical constraints such as customers’ delivery

At an airport, the flights should be attached to the gates to embark or disembark the passengers. The airport gate assignment problem concerns the efficient utilization of gates by assigning flights to the gates according to the flights’ planned schedules. However, due to ever-increasing air traffic demands and unpredictable weather conditions, it is hard to expect that the flights strictly follow

Abstract not available

The emergence of bike-sharing systems has considerably improved last- and first-mile transportation systems. To ensure attractiveness to end users, operators aim to design effective service-oriented operational strategies to meet the desired service targets for users. Most existing studies focus on the service efficiency of bike-sharing systems, while service equity is overlooked. In this study, we

Trip booking and traffic rationing have been proposed as two alternative travel demand management (TDM) strategies over the last two decades. Through artificially restricting demand (vehicle travel) by booking or rationing the scarce road capacity during the peak periods, the negative externalities generated by travel demand over available supply or road capacity can be reduced. In many cases, the

This paper examines the so-called wild goose chase phenomenon in taxi systems and proposes a new mitigation strategy based on dynamic vehicle swaps. An analytic queuing network model, including a system of differential equations, is derived to yield approximate formulas for the expected system performance in the steady-state equilibria under the vehicle swap strategy. This model is solved numerically

This study proposes a hierarchical control framework to maximize the throughput of a road network driven by travel demand with uncertainties. In the upper level, a perimeter controller regulates the traffic influx into the core road network. The upper level uses a reinforcement learning algorithm that learns and responds to the traffic dynamics in the core road network without the need for an underlying

The flexible and personalized street-hailing taxi service constitutes an indispensable component of urban mobility. However, most studies have focused only on the observed demand (pickup record) while ignoring the unmet demand. If based only on such analysis, the effectiveness of demand management policies and taxi searching strategies will be undermined. Motivated by this, we develop a recursive decomposition

Liquefied natural gas (LNG) bunkering stations are areas for bunkering LNG-powered ships via a flexible hose from either a shoreside facility, shore-based/pontoon tank, or an LNG truck. The operation management of LNG bunkering stations is complex because many factors affect the operational performance, including station layout, bunkering technology, and frequent interactions among trucks, tanks, and

The information of network-wide future traffic speed distribution and its propagation is beneficial to develop proactive traffic congestion management strategies. However, predicting network-wide traffic speed propagation is non-trivial. This study develops a traffic flow dependency and dynamics based deep learning aided approach (TD2-DL), which predict network-wide high resolution traffic speed propagation

This study proposes an optimization-based approach to rank the importance of link combinations and analyze network vulnerability in extreme and near-extreme cases of disruption under the simultaneous disruption of multiple links. A vulnerability envelope concept is used, which considers the worst and best network performance under multiple-link disruptions. This study goes a step further than previous

The hub location problem (HLP) is a fundamental facility planning problem with various applications in transportation, logistics, and telecommunication systems. Due to strategic nature of the HLP, considering uncertainty and the associated risks is of high practical importance in designing hub networks. This paper addresses a risk-averse single allocation HLP, where the traffic volume between the origin–destination

Setting traffic light signals is a classical topic in traffic engineering, and important in heavy-traffic conditions when green times become scarce and longer queues are inevitably formed. For the fixed-cycle traffic-light queue, an elementary queueing model for one traffic light with cyclic signaling, we obtain heavy-traffic limits that capture the long-term queue behavior. We leverage the limit theorems

Heterogeneity in agents’ preferences is generally analysed through mixed logit models, which assume taste parameters are distributed in the population according to a certain mixing distribution. As a result, if the utility function is linear in attributes, the willingness to pay is the ratio of two random parameters and is itself random. This paper proposes a technique built on the Delta method, partly

This paper presents an efficient solution method for the matrix estimation problem using a static capacity constrained traffic assignment (SCCTA) model with residual queues. The solution method allows for inclusion of route queuing delays and congestion patterns besides the traditional link flows and prior demand matrix whilst the tractability of the SCCTA model avoids the need for tedious tuning of

We develop algorithms to analyze Information and Communication Technologies (ICT) data in order to estimate individuals’ mobility at different spatial scales. Specifically, we apply the algorithms to delineate airport catchment areas in the United Kingdom’s Greater London region and to estimate ground access trip times from a very large ICT dataset. The spatial demand is regressed over demographic

We consider the line planning problem in public transport in the Parametric City, an idealized model that captures typical scenarios by a (small) number of parameters. The Parametric City is rotation symmetric, but optimal line plans are not always symmetric. This raises the question to quantify the symmetry gap between the best symmetric and the overall best solution. For our analysis, we formulate

We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse optimization (IO) estimation, an agent-level machine learning method theoretically consistent with a utility-maximizing mixed logit model framework. The method provides joint, individual-specific, and deterministic estimation, which overcomes the limitations of discrete choice models (DCMs) given ubiquitous datasets.

This paper develops a new approach to portray the equilibrium and analyze the appropriate lane policy during different deployment stages of autonomous vehicles (AVs) by innovatively integrating Vickrey's bottleneck model into the day-to-day dynamic model. The travel cost function in the classical bottleneck model is described by considering the impact of AVs’ value of time (VOT) reduction and AV gain

Puzzle-based storage (PBS) is one of the most space-efficient types of storage systems. In a PBS unit, loads are stored in a grid of cells, where each cell may be empty or contain a load. A load can move only to adjacent empty cells. These cells are termed escorts in the literature, and their number is relatively small. When a load is requested for retrieval, a sequence of load movements is performed

This study proposes a new methodology to quantify the efficiency dynamics of a port over time. While efficiency evaluation has gained full attention in port management, researchers conducting related studies are challenged by temporal variations observed in the collected data. Existing approaches have almost exclusively relied on multivariate normal distributional assumptions of the input and output

Parking space availability is valuable information to travelers. This paper aims at modeling drivers’ behavioral changes in arrivals/departures over time of day and developing an adaptive forecasting approach for parking space availability. We propose a stochastic model that consists of two inter-connected Markov processes. First, the lower level of the model focuses on the parking behavior within

Container drayage plays a critical role in intermodal global container transportation, as it accomplishes the first- and last-mile shipment of containers. A container drayage operator dispatches a set of tractors and a set of trailers to transport containers within a local area. An important aspect of the operations is that the arrival times of service requests are uncertain, which means that the operator

This paper formulates a novel, multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP) to analyze multiple discrete-continuous (MDC) choices at a disaggregate level, including the number of instances different alternatives are chosen and the amount of consumption at each instance of choice. In doing so, the proposed model ensures a logically consistent prediction of multiple

This paper develops an integrated economic model to examine two competing ports’ investment in adaptation to climate-change disasters. The ports have asymmetric information on the actual disaster damage. In deciding on adaptation investment, the “leader” port is a better-informed first mover and the “follower” port is a less-informed follower. The government is able to acquire and verify port adaptation

Many regions of the world aim to phase out conventional private gasoline cars within ten years, requiring imminent expansion of the electric vehicle (EV) charging infrastructure. However, because of high installation and maintenance costs, many landowners (LOs), such as shopping malls and commercial building owners, hesitate to install and operate large-scale EV charging facilities of their own volition

Connected and Autonomous Vehicles is a technology that will be disruptive for all layers of traffic control. The Lagrangian, in-the-flow nature of their operation offers untapped new potentials for sensing and actuation, but also presents new fundamental challenges. In order to use these vehicles for traffic state reconstruction and control, we need suitable traffic models, which should be computationally

City logistics, as an essential component of the city operation system, aims at managing the complex flow of goods and services from providers to customers efficiently. Delays associated with peak-period traffic congestion exists in both large and small metropolitan areas. As many of the service tasks in city logistics are needed to be performed during peak hours, operators of urban management movement

We develop a model for empirical evaluation of the social costs and benefits of street parking charges. From the model, we derive an expression for optimal parking charges and occupancy levels: in optimum, parking search costs are balanced against the loss of consumer surplus from unused parking spaces. Contrary to rules-of-thumb common in practice, optimal occupancy levels are not constant but depend

While much attention was paid to the interactions of human-driven and automated vehicles at the microscopic level in recent years, the understanding of the macroscopic properties of mixed autonomy traffic flow still remains limited. In this paper, we present an equilibrium model of traffic flow with mixed autonomy based on the theory of two-player games. We consider self-interested traffic agents (i

Apps which allow customers to check waiting times in real time on their smartphones become increasingly popular across many industries. Waiting time information is ambiguous in the sense that it is good news for some customers and bad news for other customers depending on whether they get to know that they have to wait short or long times, respectively. This paper studies the strategic choice of information

On-demand ride-sourcing platforms have quickly emerged and become ubiquitous in our daily lives. Motivated by the rising public concern about service quality in the ride-sourcing market, this paper aims to examine the impact of exclusion policy that can serve as both quality management and supply regulation strategy. With an exclusion policy, the platform excludes low-quality service providers/drivers

This paper investigates the multi-type traffic sensor location problem for simultaneous estimation of origin-destination (OD) demands and link travel times while also considering the two sources of spatial covariance effects on a road network with uncertainties. The first source is the statistical correlation of the vehicular traffic demands for different OD pairs in a typical hourly period (e.g.,

Parking occupancy in a delineated area is defined by three major parameters – the rate of car arrivals, the dwell time of already parked cars, and the willingness of drivers to continue their search for a vacant parking spot. We investigate a series of theoretical and numeric models, both deterministic and stochastic, that describe parking dynamics in an area as dependent on these parameters, over

A recent empirical study (Shi and Li, 2021) showed that commercial automated vehicles (AVs) became more unstable as the headway was set to a smaller value, implying possible intrinsic tradeoffs between safety, mobility, and stability aspects in AV following control design. This study aims to analytically explain the underlying vehicle control mechanism that dictates these tradeoffs. To this end, a