This paper investigates two fundamental questions related to safety and insurance in the age of automation. First, we touch upon the question of safety and liability under infrastructure-assisted automated driving. In such an environment, automakers provide vehicle automation technology while infrastructure support service providers (ISSPs) provide smart infrastructure services. Additionally, customers

The profit-oriented bike-sharing industry, such as Mobike in China and Limebike in the USA, has widely adopted the free-float mode, which allows users to rent and return bikes without any restrictions with regard to stations. Compared to the traditional station-based mode, this new mode improves convenience and satisfies a variety of travel demands, but it also results in higher operating costs and

This paper investigates a variant of the heterogeneous fleet vehicle routing problem (HVRP) that incorporates soft time deadlines for customers and allows for tardiness at penalty costs. Distinct vehicle types feature varying fixed usage costs and utilize different road networks, resulting in differences in both travel times and travel costs. The objective is to optimize fleet assignment and vehicle

Urban freight data analysis is crucial for informed decision-making, resource allocation, and optimizing routes, leading to efficient and sustainable freight operations in cities. Driven in part by the COVID-19 pandemic, the pace of online purchases for at-home delivery has accelerated significantly. However, responding to this development has been challenging given the lack of public data. The existing

Implementing passenger flow control strategies is an effective approach to reducing commuter travel delays and ensuring crowd safety in a congested metro network. Due to the intricacy of the interweaving of passenger flows between various lines and stations, the development of a scientific passenger flow control strategy is challenging in the networked mode of operation. The first-in-first-out (FIFO)

This study introduces a graph theory-based model that addresses the link flow observability problem in traffic networks by optimizing passive sensor deployment. The model aims to determine the minimal number of sensors and their optimal placement. It constructs a virtual network and uses isomorphic graph theory to map between the original and virtual networks, ensuring consistency in nodes, links,

We consider a combined truck-drone delivery problem with stochastic truck travel times and soft time windows. A fleet of homogeneous trucks and drones are deployed in pairs to provide delivery services to customers. Each drone can be launched from and retrieved to its truck multiple times, and in each flight, a drone can serve one or more customers. Our objective is to determine the truck routes and

This paper studies an intermodal container terminal (IMT) location and design problem, where the IMT operator wants to locate a set of open-access IMTs and design their capacity levels to maximize its profit. Following the IMT operator’s decisions, network users, responsible for container transportation, will independently choose their routes and may procure intermodal services from the IMT operator

In this paper, we determine a welfare-optimal investment strategy for bicycle networks while considering the joint impact of travel time savings and induced demand throughout the investment horizon. The paper extends an expansion strategy with fixed demand recently published in Paulsen and Rich (2023). Accommodating induced demand requires that we can express how expansions of the network affect demand

We propose to enhance the efficiency of road bottlenecks by strategically implementing metering-based priority (MBP) schemes. Under MBP, a portion of the bottleneck capacity is reserved for priority users but made available for nonpriority users when no priority users are queueing. Previous studies have found that MBP is Pareto-improving regarding individual trip costs with homogeneous users, but its

The full link flow observability problem is to identify the minimum set of links to be installed with sensors in a traffic network that allows the unique determination of all link flow volumes. In our previous work (Shao et al., 2016), we proposed a flow conservation system using turning ratios as prior information, and suggested that installing sensors on all exclusive incoming road links in the traffic

Given the increasing heterogeneity of the types of aircraft operated, many airlines have switched from the traditional team scheduling approach to the individual scheduling approach for cabin crew planning. The individual approach not only allows for greater scheduling flexibility, but also helps achieve better utilization of available manpower through cross-class substitution (i.e., assigning a high-class

The aviation industry has proposed the collective goal of achieving net-zero carbon emissions by 2050. In addition to the existing market-based methods (MBMs), the use of renewable energies, in particular, sustainable aviation fuel (SAF), could be one of the most promising means for achieving this long-term target. This paper investigates how an SAF mandate from the government can lead to heterogeneous

In this paper we provide a statement of dynamic spatial price equilibrium (DSPE) in continuous time as a basis for modeling freight flows in a network economy. The model presented describes a spatial price equilibrium due to its reliance on the notion that freight movements occur in response to differences between the local and distant prices of goods for which there is excess demand; moreover, local

This paper develops a new generalized statistical modeling approach for choice problems where decision-makers are faced with a continuous set of alternatives. In the existing literature, decision-making behavior is usually analyzed in the context where there are only a few discrete alternatives from which decision-makers may choose. This paper generalizes this approach and investigates the scenario

Train timetable during the end-of-service period is crucial for passenger accessibility and operation cost in urban rail transit networks. Existing studies have investigated the last train timetabling problem for improving passenger accessibility. This study investigates a train timetabling problem for the end-of-service period, which concentrates on the coordination of the service ending time on different

Petroleum is the foundation of the oil industry and many transportation systems. As a typical hazardous material, transportation of petroleum products by road trucks will create an explosion risk and pose a potential threat to safety. The petrol distribution system with economic viability and safety calls for a well-designed distribution network and effective transportation management. In this paper

This paper investigates a robust optimization problem concerning the integration of fleet deployment and empty container repositioning in a shipping line network, where a fleet of vessels is dispatched to transport both laden and empty containers, aiming to fulfill a predetermined set of requests over a defined time horizon. The sizes of customer demands are uncertain and are characterized by a budgeted

A convoy represents a collection of vehicles traveling with a spacing of 50–100 m between them for tactical purposes. The convoy movement problem is a variant of the vehicle routing problem, an NP-hard problem aimed at determining the paths and schedules of convoys. Given the uncertainties in travel times during wartime, attributable to various factors such as road conditions and enemy threats, it

In a railway shunting yard, the transformation of inbound trains into properly composed outbound trains is a complex task because it involves decisions of multiple operations processes. This study addresses the integrated optimization of hump sequencing, train makeup, and classification track assignment problem in a railway shunting yard. Several key practical yard operation constraints are considered

How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue of a Laplacian network matrix. Based on the equal

With the prosperity of sharing economy, more part-time and freelance suppliers (i.e., drivers) join on-demand mobility services. Because of suppliers’ autonomy and behavioural heterogeneity, the platform cannot ensure that suppliers will accept a dispatch order. One approach to mitigate this supply uncertainty is to provide suppliers with personalized menus of dispatch recommendations. A key issue

Recently, instant delivery has been growing rapidly, with numerous platforms emerging to offer such services. Requestors dynamically arrive at the platform to place delivery service requests that detail their pickup locations, recipient locations, package weights, departure times, and willingness-to-pay (WTP). The platform then uses its dedicated riders, scattered in different places, to fulfill these

Passively-generated mobile data has grown increasingly popular in the travel behavior (or human mobility) literature. A relatively untapped potential for passively-generated mobile data is synthetic population generation, which is the basis for any large-scale simulations for purposes ranging from state monitoring, policy evaluation, and digital twins. And yet, this significant potential may be hindered

This paper presents an Aggregate Matching and Pick-up (AMP) model to delineate the matching and pick-up processes in mobility-on-demand (MoD) service markets by explicitly considering the matching mechanisms in terms of matching intervals and matching radii. With passenger demand rate, vehicle fleet size and matching strategies as inputs, the AMP model can well approximate drivers’ idle time and passengers’

This paper presents a study on traffic flow models in one-dimensional (1D) and two-dimensional (2D) lattices. The models incorporate generalized look-ahead rules that consider nonlocal slow-down effects. The proposed cellular automata (CA) models use stochastic rules to determine the movement of cars based on the traffic configuration ahead of each car. Specifically, a look-ahead rule is used that

Flexible bus is a class of demand-responsive transit that provides door-to-door service. It is gaining popularity now but also encounters many challenges, such as high dynamism, immediacy requirements, and financial sustainability. Scientific literature designs flexible bus services only for reservation demand, overlooking the potential market for immediate demand that can improve ride pooling and

This study introduces the novel concept of local detouredness, i.e. detours on subsections of a route, as a new phenomenon for understanding and modelling route choice. Traditionally, Stochastic User Equilibrium (SUE) traffic assignment models have been concerned with judging the attractiveness of a route by its total route cost. However, through empirical analysis we show that considering solely the

Numerous studies have compared machine learning (ML) and discrete choice models (DCMs) in predicting travel demand. However, these studies often lack generalizability as they compare models deterministically without considering contextual variations. To address this limitation, our study develops an empirical benchmark by designing a tournament model to learn the intrinsic predictive values of ML and

This paper explores short duration disturbances in the traffic stream that are large enough to impact the traffic dynamics and disrupt stationarity when establishing the fundamental diagram, FD, but small enough that they are below the resolution of conventional vehicle detector data and cannot be seen using conventional methods. This empirical research develops the Exclusionary Vehicle Aggregation

Vehicle-based mobile sensing, also known as drive-by sensing, efficiently surveys urban environments at low costs by leveraging the mobility of urban vehicles. While recent studies have focused on drive-by sensing for fleets of a single type, our work explores the sensing power and cost-effectiveness of a mixed fleet that consists of vehicles with distinct and complementary mobility patterns. We formulate

Electric aircraft represent a major technological breakthrough with a promise of revolutionizing aviation systems towards more sustainable and accessible services. Prominent electric aircraft prototypes feature limited seating capacity and short ranges, which make them well-suited for efficiently operating thin routes—particularly, regional routes serving remote regions—in the near future. To capitalize

This study investigates the starting point of parking search, presenting new findings through empirical and theoretical approaches. It introduces a probabilistic model that describes the transition from normal driving to actively searching for parking, aiming to minimize journey costs. The model is tested using real-world data collected via a smartphone app that tracks the start of parking searches

This paper presents a novel multi-agent deep reinforcement learning (MADRL) approach for real-time rescheduling of rail transit services with short-turnings during a complete track blockage on a double-track service corridor. The optimization problem is modeled as a Markov decision process with multiple control agents rescheduling train services on each directional line for system recovery. To ensure

The combination airlines operate both passenger aircraft and freighter aircraft to meet passenger and cargo demand. At present, combination airlines employ a sequential approach to allocating their capacity for passenger and cargo demand. Nevertheless, implementing an integrated resource allocation procedure has the potential to improve overall resource allocation efficiency. In this paper, we introduce

In this paper, we present a new sensor location model that aims to maximize observability of link densities in a dynamic traffic network described using a piecewise linear system of ordinary differential equations. We develop an algebraic approach based on the eigenstructure to determine the sensor location for achieving full observability with a minimal number of sensors. Additionally, a graphical

The notorious phenomenon of bus bunching prevailing in uncontrolled bus systems produces irregular headways and downgrades the level of service by increasing passengers’ expected waiting time. Modular autonomous vehicles (MAVs), due to their ability to split and merge en route, have the potential to help both late and early buses recover from schedule deviation while providing continuous service. In

Sustainable aviation fuel (SAF) serves as a critical short-term measure for reducing aviation's carbon footprint. Two main policy tools, subsidy and quota, have been developed to support its usage. We build an economic model to compare the environmental and welfare impacts of these two policies. First, we find that if an airline uses the same portion of SAF under both policies, the subsidy approach

This paper explores the impacts of a novel business model termed , which enables passengers to simultaneously request on-demand rides from multiple ride-sourcing platforms via a third-party integrator. In particular, we employ an equilibrium model where passenger demand and driver supply are endogenously dependent on the prices and wages that emerge from the competitive interaction between two platforms

We investigate the value of time as a resource (VOTR) and the value of childcare time saving (VOCTS) for a married couple with children by life cycle stage. Extending the framework of DeSerpa (1971), we develop a novel intertemporal utility-maximization model that can represent trade-offs within an individual and within a couple between different activities in their life stages based on a household

Container ports serve as crucial logistics hubs in global supply chains, but navigating ships within such ports is complex due to restricted waterways. Tugboats play a critical role in ensuring safety and efficiency by escorting and towing ships under these conditions. However, the tugboat deployment and scheduling problem has received little attention. To fill the research gap, we propose a new research

We consider a ride-hail system in which a third-party integrator receives ride requests and allocates them to ride service platforms. The ride allocation problem (RAP) is modeled as a Stackelberg game. The integrator, as the leader, chooses the allocation that maximizes its profit, by pricing the rides such that no platform (i.e., follower) can find a more profitable allocation. In pursuit of self-interest

Mobility-as-a-Service (MaaS) systems are two-sided markets, with two mutually exclusive sets of agents, i.e., travelers/users and operators, forming a mobility ecosystem in which multiple operators compete or cooperate to serve customers under a governing platform provider. This study proposes a MaaS platform equilibrium model based on many-to-many assignment games incorporating both fixed-route transit

The phenomenon of transportation service providers (TSPs) engaging in both competition and cooperation, commonly referred to as coopetition, has become increasingly prevalent in the transportation market. This is driven by the rapid advancements in information technology and sharing economy. In practice, competitive TSPs can engage in a resource exchange scheme to share their resources to improve their

In practice, road disruptions occur frequently, interrupting multiple bus routes at the same time and causing widespread passenger delays. Typically, these disrupted roads are repaired sequentially and then gradually put into service. In response to such time-varying road disruptions, this paper aims to assist bus operators in developing effective alternative service networks for passengers. The proposed

Connectivity and digitalization will enable new control measures in urban air mobility operations and open new ways for integrating these measures in real-time traffic management. Hence, new control strategies can be designed to regulate both demand and supply of Low-Altitude Air city Transport (LAAT) systems. This can be achieved by adjusting aircraft departure times, and manipulating transfer aircraft

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

Based on Wardrop’s first principle, the perfectly rational dynamic user equilibrium is widely used to study dynamic traffic assignment problems. However, due to imperfect travel information and a certain “inertia” in decision-making, the boundedly rational dynamic user equilibrium is more suitable to describe realistic travel behavior. In this study, we consider the departure time choice problem incorporating

This paper addresses the sustainable design of hub networks under uncertainty in the context of less-than-truckload transportation, taking into account factors related to carbon pricing. The problem is modeled to maximize profits in a stochastic demand environment, where a portion of the demand may remain unserved depending on the trade-off between profits, costs, and carbon emissions. The model explicitly

The majority of the past research dealing with lane-changing controller design of autonomous vehicles (s) is based on the assumption of full knowledge of the model dynamics of the and the surrounding vehicles. However, in the real world, this is not a very realistic assumption as accurate dynamic models are difficult to obtain. Also, the dynamic model parameters might change over time due to various

In this paper, a class of single-allocation hub location problems is investigated from the perspective of upgrading. The latter is understood as an improvement of a set of edges to increase their individual performance, e.g., a decreased unit transportation cost. The goal is to obtain an improved optimal solution to the problem compared to that obtained if upgrading was not done. A budget constraint

Due to the inherent safety concerns associated with traffic movement in unconstrained two-dimensional settings, it is important that pedestrians’ and other modes’ movements such as bicyclists are modeled as a risk-taking stochastic dynamic process that may lead to errors and thus contacts and collisions. Among the existing models that may capture risk-taking behaviors are: 1) the social force models

We study a variant of dynamic pickup and delivery crowd-shipping operation for delivering online orders within a few hours from a brick-and-mortar store. This crowd-shipping operation is subject to a high degree of uncertainty due to the stochastic arrival of online orders and crowd-shippers that impose several challenges for efficient matching of orders to crowd-shippers. We formulate the problem

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

This paper introduces an inverse optimization method to uncover commuters’ schedule preference and crowding perception based on aggregated observations from smart card data for an urban rail corridor system. The assessment of time-of-use preferences typically involves the use of econometric models of discrete choice based on detailed travel survey data. However, discrete choice models often struggle

This paper develops models of a bus route in which (i) stop spacing can vary; (ii) trip lengths are heterogeneous; (iii) demand is elastic; and (iv) passengers delay the bus. Since wider spacings make sufficiently long trips faster, and sufficiently short trips slower, they induce long trips and repel short trips. We explore two continuum-approximation models: one with fixed headways and another in

The technological progress in the recent decade has greatly facilitated the large-scale implementation of dynamic enroute ridepooling services, such as Uber Pool and DiDi Pinche. To sustain a profitable enroute ridepooling service, a well-designed discounting scheme is crucial. This paper focuses on the optimization of up-front discounting strategies for enroute ridepooling service, under which passengers

Random utility maximization-based discrete choice models involve utility functions that are typically specified with explanatory variables representing alternative-specific attributes. It may be useful to specify some alternative-specific attributes as stochastic in situations when the analyst cannot accurately measure the attribute values considered by the decision maker. In addition, the parameters