Improvements in European air traffic management (ATM) constitute one of the key levers to reduce aviation emissions in the future to reach ambitious goals. In this paper, we evaluate the benefits of improved network-centric ATM with coordinated optimisation of capacity, delays, re-routings and emissions vs the present fragmented ATM which has generated high delays and extensive re-routing due to sub-optimal

Intelligent vehicular network is one of the popular paradigms for sixth-generation (6G) networks. With the growth in vehicular traffic density, it is essential to ensure safety and security by providing ultra reliable low latency (URLL) services for vehicular communication. Moreover, along with the URLL services, it is also essential that these services are energy-efficient. These requirements can

Climate change exacerbates natural hazards and continuously challenges the performance of critical infrastructure. Thus, climate resilience and sustainable adaptation of infrastructure are of paramount importance. This paper puts forward a novel framework and metrics for optimising sustainability (Greenhouse Gas emissions - GHG), climate resilience (restoration time), and cost. The framework aims to

The unique relationship between the value capture mechanism (VCM) and transit-oriented development (TOD) stations and their peripheral areas, which progressively develops an expanded multimodal network, is well acknowledged in the transport industry. However, in regards to the location of TOD stations, insufficient attention has been paid to user travel behaviours and the operating mechanism of the

The speed of recovery from supply chain disruption has been identified as the predominant factor in building a resilient supply chain. However, COVID-19 as an example of an evolving crisis may challenge this assumption. Infection risk concerns may influence production resumption decision-making because any incidents of infection may lead to further shutdowns of production lines and undermine firms’

Maritime Autonomous Surface Ships (MASS) are deemed as the future of maritime transport. Although showing attractiveness in terms of the solutions to emerging challenges such as carbon emission and insufficient labor caused by black swan events such as COVID-19, the applications of MASS have revealed problems in practice, among which MASS navigation safety presents a prioritized concern. To ensure

We construct a new unified panel dataset that combines route-year-level freight rates with shipping quantities for the six major routes and industry-year-level newbuilding, secondhand, and scrap prices from 1966 (the beginning of the industry) to 2009. We offer detailed instructions on how to merge various datasets and validate the data’s consistency by industry experts and former executives who have

This study aims to investigate attendees’ trips to venues before special events considering pre-event activities. We focus on how pre-event activities change attendees’ departure-time choices and affect traffic congestion near a venue. By describing attendees’ pre-event utility and the attractiveness of the venue, a bottleneck model is proposed to model attendees’ departure times with heterogeneous

Characterizing the integrated traffic and parking dynamics in a coupled road-parking system is challenging due to the interactions between parking and non-parking vehicles and the presence of cruising-for-parking. In this paper, we propose a new trip-based macroscopic model of parking considering various sources of user heterogeneity that are key to modeling parking. The macroscopic or network fundamental

This paper studies the Feeder Network Design Problem (FNDP), which considers the design of a minimum cost liner shipping network for the transportation of cargo (containers) between a given hub port and a set of feeder ports. In addition to determining the services to operate (i.e., the routes), the FNDP deals with deciding the fleet of vessels to deploy on these services. In contrast to most FNDPs

This work concerns the estimation of recursive route choice models in the situation that the trip observations are incomplete, i.e., there are unconnected links (or nodes) in the observations. A direct approach to handle this issue could be intractable because enumerating all paths between unconnected links (or nodes) in a real network is typically not possible. We exploit an expectation–maximization

In recent years, planners have started considering Machine Learning (ML) techniques as an alternative to discrete choice models (CM). ML techniques are primarily data-driven and typically achieve better prediction accuracy compared to CM. However, it is hypothesized that since the ML techniques do not have the strong grounding to economic theory as the CMs, they may not perform well in contexts that

Highway traffic state data collected from a network of sensors can be considered as a high-dimensional nonlinear dynamical system. In this paper, we develop a novel data-driven method–anti-circulant dynamic mode decomposition with sparsity-promoting (circDMDsp)–to study the dynamics of highway traffic speed data. Particularly, circDMDsp addresses several issues that hinder the application of existing

We investigate upstream coopetition and competition in a supply chain in the context of a high-quality brand manufacturer’s strategy on upstream outsourcing and e-commerce platform’s strategy on downstream information disclosure. The high-quality brand manufacturer outsources production and sells through an e-commerce platform, where a low-quality manufacturer also sells. The high-quality manufacturer

Modular vehicles (MV) possess the ability to physically connect/disconnect with each other and travel in platoon with less energy consumption. A fleet of demand-responsive transit vehicles with such technology can serve passengers door to door or have vehicles deviate to platoon with each other to travel at lower cost and allow for en-route passenger transfers before splitting. A mixed integer linear

The high-level maintenance plan is the train-set overhaul arrangement that is scheduled annually and manually in China. Previous studies have investigated this issue based on deterministic daily mileages. However, future daily mileages are difficult to predict, which may cause existing plans to be inaccurate and unfeasible in practice. Therefore, this study only considers the historical daily mileages

This study aims a more thorough understanding of individuals’ motivations and determinants of working from home (WFH) at various phases of the pandemic. To achieve this research goal, we analyze attitudes towards WFH, the profiles of various types of workers engaged in WFH, and the determinants of the current and future expected frequency of WFH among 816 workers in Hong Kong. We identify four types

Deep neural networks have been adopted to recognize human car-following behaviors under the assumption that data would be all that was needed. These attempts, however, are inefficient because the knowledge accumulated by previous theory-based car-following studies is not utilized. In order to combine both approaches, we investigated the potential for using coefficients in a theory-based car-following

In recent years, governments have successively introduced a variety of policies to promote the development of the autonomous vehicle (AV) industry and technology. Existing research sheds light on individuals’ decision process regarding their willingness to purchase AVs or legislation and policy design from the perspective of policymakers, regulators and experts. Little research has been conducted to

Vehicular edge computing (VEC) uses the computing resources of edge devices to complete tasks for complex calculations and time-sensitive requirements in vehicular networks. However, there are some problems with the current task offloading, such as simplifying the communication mechanism at the media access control (MAC) layer and ignoring the traffic characteristics at the application layer. To address

Resource allocation optimization (RAO) is a crucial design issue for providing green communications in the sixth generation (6G) of underwater acoustic (UWA) sensor networks (SNs). To have a suitable convergence speed in the machine learning (ML)-based algorithms used for finding the solution of the online RAO problems, the optimal or suboptimal solution of the offline form of the online problem should

Historical data suggest that when a severe tropical storm or hurricane impacts a community, the vulnerable segment of the population suffers the most severe consequences. With an increased aging population, it is crucial to understand how vulnerability alters evacuation behavior. Emergent variables such as fear of COVID-19 require additional exploration. People afraid of COVID-19 exposure may refuse

It is widely recognized that human-driven vehicles (HVs) and connected and autonomous vehicles (CAVs) are expected to coexist and share the urban traffic infrastructure in the transportation network for a long time. To fully utilizes CAVs’ potential to reduce congestion in the transitional period, this study proposes and addresses the intersection design and signal setting problem in the transportation

The construction of China’s extensive high-speed rail (HSR) network is driven by various motives of different participants. This study employs an improved spatial econometric model to examine the motivation of local officials behind the construction of HSR stations. We employ a comprehensive dataset consisting of information about HSR station construction, the promotion of officials, the economic growth

Traffic safety is a critical factor that has always been considered in policy making for urban transportation planning and management. Accurately predicting crash risk hot spots allows urban transportation agencies to better implement countermeasures towards enhancing traffic safety. Considerable efforts have been devoted to investigate crash risk hot spots in many previous studies. We hereby identify

Accessibility assessment of High-speed rail (HSR) should not be limited to station-to-station analysis, since “first and last mile” transport is crucial. Economic costs, time value, and travel time volatility significantly impact travel decisions but are underexplored. We conducted a multidimensional analysis of the spatial and temporal distribution characteristics of the accessibility of HSR stations

This paper presents the results of route choice models for cyclists in the city of Zurich. The data includes approx. 4400 cycling trajectories, including approx. 850 from e-bikes. The network is sourced from Open Street Map (OSM) and the choice set generation is based on the breadth-first search on link elimination (BFSLE) algorithm. We present descriptive statistics and model results which specifically

The recently accentuated features of augmenting conventional wireless networks with high altitude platform systems (HAPS) have fueled a plethora of applications, which promise to offer new services to ground users, as well to enhance the efficiency and pervasion of existing applications. Cloud-enabled HAPS, which aims to create HAPS-based datacenters that offer cloud services to users, has particularly

Trade imbalances and global disturbances generate mismatches in the supply and demand of empty containers (ECs) that elevate the need for empty container repositioning (ECR). This research investigated dry ports as a potential means to minimize EC movements, and thus reduce costs and emissions. We assessed the environmental and economic effects of two ECR strategies via dry ports—street turns and extended

Capacity analysis of the pure connected automated vehicle (CAV) traffic remains a challenging problem due to the high-dimensional factors involved in the control design. Especially, the communication loss and communication topology greatly impact the headway variation of CAVs and hence capacity with stochastic properties. This study provides a stochastic framework to mathematically derive multiple

Over the last years, the evolution of Vehicle-to-Everything (V2X) services from basic safety-related to enhanced V2X (eV2X) applications prompted the development of the 5G New Radio (NR)-V2X technology. Standardized by the Third Generation Partnership Project (3GPP) in Release 16, NR-V2X features a distributed resource allocation mode, known as Mode 2, that allows vehicles to autonomously select their

Shipment size and freight transport mode choice have been modeled previously in many studies. There are several studies on the road transport level of this subject as well. This study investigates shipment size and road freight vehicle choice from a geographical point of view. An industrial region in a province may be neighboring another province, a large metropolitan area. Then, freight vehicle choice

Due to emission reduction pressure and supply chain changes, this paper analyzes the development trend of the marine supply chain based on the competition and cooperation incentives of carriers, considering the impact of the government’s carbon tax policy. We consider multi-stage Stackelberg games with different power structures consisting of a government, hub port, and two carriers. Equilibrium solutions

While the trend towards building resilience in infrastructure systems for disaster risk reduction is accelerating, the application of infrastructure resilience is largely conceptual or an embellishment to established modelling techniques. In response, this paper sets out the theoretical foundations of infrastructure resilience, which broadly applies across critical infrastructure networks. This is

Sustainable urban road alignment planning should provide functional, economical, people-friendly, and eco-friendly schemes to meet traffic-related demands and promote social development. However, how to realise it is unclear. This research systematically develops a framework for it from the perspective of factors that should be considered, digitalisation and parsing methods, factor evaluation, and

Urban Air Mobility (UAM) is a transformative concept that must operate harmoniously within the constraints imposed by societal impacts. Noise-aware flight trajectory planning can address UAM’s community noise concerns. However, the traditional trajectory optimization paradigm requires repetitive computations of a flight’s noise footprints in complex urban environments and is computationally expensive

Autonomous vehicles are to revolutionize the way urban mobility demands are served, and they are most likely to be powered by electricity. To accurately quantify the benefits of replacing existing mobility services with autonomous electric vehicles, electric autonomous mobility-on-demand (EAMoD) systems need to be evaluated and designed with the congestion effects they may cause taken into account

Abstract not available

In last-mile delivery, drivers frequently deviate from planned delivery routes because of their tacit knowledge of the road and curbside infrastructure, customer availability, and other characteristics of the respective service areas. Hence, the actual stop sequences chosen by an experienced human driver may be potentially preferable to the theoretical shortest-distance routing under real-life operational

Epidemics have been posing significant challenges to health, existence, and continuity. From the emergence of an outbreak to its elimination, managing an epidemic/pandemic entails many operations and supply chain management decisions that can contribute to a lessening of its impact. With these decisions, epidemic-/pandemic-imposed challenges related to forecasting, planning, supply, manufacturing,

In this paper, we examine the effect of various agreements between a socially concerned airport and an environmentally conscious airline regarding their profitability and channel coordination to decarbonize the aviation sector under two distinct settings. First, we consider no government interventions, and second, we explore government-imposed taxation to curb emissions. Our analysis shows that the

Lane-changing is a routine but difficult driving task with important implications on traffic flow characteristics. Despite significant progresses in lane-changing decision modeling, lane-changing models are often improperly calibrated due to two issues related to trajectory data processing. First, the time of insertion (i.e., the time instant where a vehicle crossed the lane marking) is incorrectly

The traffic density of small aerial vehicles operating within urban environments is expected to increase significantly in the near future. This urban environment is highly constrained due to being limited to the low-altitude airspace directly above the existing road network. Multiple studies have addressed factors influencing the capacity of urban airspace. These have used simulations of aircraft,

Perimeter control involves monitoring network-wide traffic and regulating traffic inflow to alleviate hypercongestion. Implementation of transit priority with perimeter control measures, which allow transit into a controlled area without queuing at the perimeter boundary, is an effective strategy in bimodal transportation systems. However, travelers’ behavior changes in response to perimeter control

Autonomous vehicles (AVs) are the next-generation driver-less vehicular entities with advanced technologies. Overtaking is an important and challenging maneuver that needs to be frequently performed in diverse environments during the run. The maneuvering of AVs, in present scenarios, improves driving precision, fuel efficiency, and travel time and minimizes road accidents caused by human error, waiting

Freight carriers’ behavior greatly varies given the number of parties involved in the process from the origin end to the destination end and the heterogeneity of commodities. Accordingly, their reaction to transportation policies including road pricing is composed of multidimensional choices, e.g., they can take a series of actions in multiple stages in response to policies, which have been overlooked

Nowadays, containerized freight transport is one of the most important transportation systems that is undergoing an automation process due to the Deep Learning success. However, it suffers from a lack of annotated data in order to incorporate state-of-the-art neural network models to its systems. In this paper we present an innovative methodology to generate a realistic, varied, balanced, and labelled

Maritime transport faces new safety challenges in an increasingly complex traffic environment caused by large-scale and high-speed ships, particularly with the introduction of intelligent and autonomous ships. It is evident that Automatic Identification System (AIS) data-driven ship trajectory prediction can effectively aid in identifying abnormal ship behaviours and reducing maritime risks such as

Supplying store brands (SBs) to retailers is a strategic decision for national brand (NB) manufacturers in response to the prevalence of retailers introducing SBs. This study proposes a game-theoretical model to examine the manufacturer’s supply strategy when facing the retailer’s store-branded product, which could have lookalike packaging that confuses consumers about their quality preferences regarding

In actual bike-sharing services, an operator can adopt any of three pricing strategies, namely, pay-per-use (Strategy P), flat-fee (Strategy F) and a hybrid of pay-per-use and flat-fee (Strategy H). When the operator launches the mode of picking up and returning bikes at designated shared bike parking points, users often perceive the inconvenience cost because of having to go to the designated parking

In a battery electric bus (BEB) network, buses are scheduled to perform timetabled trips while satisfying time, energy consumption, charging, and operational constraints. Increasing research efforts have been dedicated to the integrated optimization of multiple planning tasks to reduce system costs. At a high integration level, this study determines the BEB scheduling and charging planning with flexible

Unmanned aerial vehicles (UAVs) are widely used for surveillance in both civilian and military scenarios. The utilization of UAVs provides an opportunity for monitoring landslide-prone areas by automatically collecting geological information, thereby reducing the risks and the time required to be working in harsh environments. Due to the maximum travel time limit of UAVs and the geographical dispersion

Sustainability is one of the main challenges the aviation industry is currently facing. In a global context of energy transition towards cleaner and renewable sources, the sector is developing technologies to fly more efficiently and mitigate its environmental impact. Innovative propulsion alternatives such as biofuels, electric aircraft and hydrogen engines are already a reality or are close to becoming

Democratizing access to charging infrastructure is a prerequisite for equitable electric vehicle (EV) adoption and use. Residential EV charging is the most prevalent and convenient option. However, multi-unit dwelling (MUD) residents have limited access to home charging, leading to higher operating costs and less flexibility. We introduce the concept of community charging hubs for shared charger use

Airport Slot Allocation (ASA) is a multi-objective, multi-stakeholder decision process that aims to maximise airport capacity utilisation and mitigate delays. Existing ASA studies have considered objectives associated with the slot scheduling process per se without considering the implications of the alternative schedules, represented by the generated efficient frontier, on the operational delays,

This paper addresses the congestion management issues of a bottleneck-constrained highway system with manned vehicles (MVs) and autonomous vehicles (AVs). A novel model that incorporates the in-vehicle activity utilities and activity type choices of AV commuters is presented for analyzing the equilibrium of the bi-modal bottleneck system with MVs and AVs. Time-varying and step tolling schemes accounting