With work arrangements experiencing dramatic changes over the past three years due to the COVID-19 pandemic, and the possibility that altered work arrangements may persist well into the future, the implications of teleworking on activity-travel behavior are potentially profound. This paper aims to substantially add to the body of knowledge about the present and future of telework in the wake of the

This paper introduces a parallel computing framework based on the Spectral Partitioning (SP) method designed to enhance the computational efficiency of large-scale microscopic traffic simulation (LSMTS). The framework employs the SP method to partition road networks, taking into account vehicle information and road information as constitutive components for node weight determination. Micro-simulation

The optimization of airport taxi routes is crucial for increasing airport capacity and resource utilization. However, existing methods for preplanning schedules are often time-consuming. To address this, we propose a new approach that reduces the problem scale by predicting the intersection state in the airport taxiway network using a spatial–temporal graph neural network (STGNN) that incorporates

Due to variations in carrying capacity and visiting periods of vessels calling at terminals, certain transshipped containers may not be able to be transported immediately after arrival. Instead, they must be temporarily stored in the yard and scheduled for later transportation. Increased container storage time in the yard as a consequence of transit delays not only incurs additional costs for shipping

In the annual winter route maintenance, transportation agencies often deploy multiple fleets of trucks for snow control and removal activities over a vast maintenance area which creates an operational problem in determining the optimal maintenance routes and fleet size. The objective of this paper is to develop a snowplow routing optimization model to enhance the efficiency of snow removal route planning

This paper analyzes the European Commission’s (EC) climate policy package ‘Fit for 55′ and its potential impact on cargo ships calling at Swedish ports. Three scenarios are evaluated using the Swedish national freight transport model. The Main Scenario is based on the EC’s?proposal to i) include ships weighing at least 5,000 gross tons (GT) in the European Emissions Trading System (EU ETS), and to

Reconfigurable Intelligent Surface (RIS) enables precise modulation and directional transmission of signals by controlling the phase and amplitude of electromagnetic waves, thus solving the problems of signal fading, multipath effects, and interference faced by conventional wireless communication systems. In this paper, the RIS-assisted vehicle-to-vehicle (V2V) communication system under multipath

Connected and automated vehicles bring the capability to generate traffic data for intersection control applications. Unfortunately, for various reasons, such as signal blocking and interference, vehicles may experience communication failures leading to inefficiencies, e.g., unnecessarily long waiting queues, increased noise and greenhouse gas emissions or increased delays of emergency vehicles at

Risk management significantly impacts the efficiency of business operations. We examine the effects of corporate risk preference on optimal ordering and risk-hedging decisions under a value-at-risk (VaR) constraint from short-term (only demand is uncertain) and long-term (both demand and supply are uncertain) perspectives. We find that under the short-term view, the impact of the shortage cost on the

Understanding the spatial–temporal stochasticity in shared mobility is crucial for ride-sourcing demand forecasting, supply–demand management, and vehicle dispatch optimization. In contrast to conventional deep learning methods that typically provide point predictions or deterministic predictions, this paper introduces the bidirectional spatial–temporal Transformer neural processes (Bi-STTNP) prediction

Empowered by the capabilities provided by fifth generation (5G) mobile communication systems, vehicle-to-everything (V2X) communication is heading from concept to reality. Given the nature of high-mobility and high-density for vehicle transportation, how to satisfy the stringent and divergent requirements for V2X communications such as ultra-low latency and ultra-high reliable connectivity appears

Corporate Mobility as a Service (CMaaS) combines the advantages of company-exclusive and public mobility services, like carsharing, bikesharing, or taxis. Although prior research indicates that CMaaS has positive impacts on the GHG emissions and costs of corporate mobility, detailed analyses are still lacking. Against this background, we propose a methodology to quantify the potentials of CMaaS to

Publicly developed logistics parks (PDLPs) have been considered one of the measures in urban logistics policies to reduce carbon emissions. In response, this paper draws on the “pollution transfer” hypothesis, constructs a carbon emission analysis framework for PDLPs, and uses spatial econometric methods to explore their carbon emission effects. The findings suggest that from a global perspective,

Electric vehicle (EV) adoption in the U.S. will be accelerated by the historic $7.5 billion public investments in EV charging infrastructure. Careful analysis of EV charging demands plays a vital role in understanding the energy requirements, power grid impact, and smart charging management opportunities of EVs. To this end, this paper develops a data-driven trip-chaining-based modeling framework including

Cities around the world vary in terms of the structure of their transportation networks and travel demand patterns. Despite these variations significantly impacting opportunities for travelers to share trips, no metrics are available to jointly characterize a region’s transportation network and travel demand in terms of the potential for travelers to share space with each other on network links, or

With the growing demand for night travel and the development of the night-time economy, extending the operation time of metropolitan subway networks has become essential. This paper proposes a 2-population 3-strategy evolutionary game model for subway network operation extension decisions, which considers the interests of subway companies, passengers, and the government while addressing transfer failure

Park-and-ride (P&R) facilities are key components in encouraging people to use the transit system by allowing them to leave their private vehicles at certain locations. The well-known multinomial logit (MNL) model is often used to develop a random utility maximization–based mathematical programming formulation to determine P&R facility locations. According to the independently and identically distributed

High-speed rail (HSR) is frequently seen as a promising alternative for long-distance travel by air and road, given its environmental advantages whilst offering a competitive level of service. However, a European HSR-network is yet to be realised, with the current state amounting to a patchwork of poorly connected subnetworks. Consequently, this results in a suboptimal performance from a user, operator

Road accidents involving autonomous vehicles (AVs) will not only introduce legal challenges over liability distribution but also generally diminish the public trust that may make itself manifested in slowing the initial adoption of the technology and call into question the continued adoption of the technology. Understanding the public’s reactions to such incidents, especially the way they differentiate

A common practice in many transport models is to allocate all costs to the car driver meaning that car passengers are essentially free riders. This specification provides an easy way of integrating drivers and passengers and fits well with the general understanding that car drivers rarely trade passenger seats for money. However, in this paper, we question this premise and argue that cost sharing can

Owing to the pervasive interdependency among networks and the great threat of various disasters, one of the most challenging issues is the resilience evaluation of interdependent networks. Existing studies have been conducted to analyze interdependent network resilience addressing unidirectional dependency, which triggers and propagates network failures. The loss and recovery of network functionality

The occurrence of life events increases the likelihood of changes in travel behaviour and these are often discussed as windows of opportunity for interventions aimed at improving sustainable travel. Hence, theoretical knowledge of the process of change due to life events is important for enabling the development of interventions suited to these naturally-occurring situations. In this paper, the Framework

Multimodality is regarded as essential to promoting sustainable mobility because of the widely found environmental benefits, although it is unclear whether individuals experience multimodality as a benefit or a burden. This study aims to investigate the relationship between multimodality and perceived transport adequacy and accessibility in different travel contexts. Using data collected in two large

Disruptions occur frequently in railway networks, requiring timetable adjustments, while causing serious delays and cancellations. However, little is known about the performance dynamics during disruptions nor the extent to which the resilience curve applies in practice. This paper presents a data-driven quantification approach for an ex-post assessment of the resilience of railway networks. Using

Urban air mobility (UAM) is a new mode of transportation which has the potential to curb congestion in urban areas by providing a fast alternative that bypasses surface-level traffic by employing low altitude urban airspace. However, the successful adoption of this innovation among other modes of transportation remains a critical challenge, as public acceptance plays a pivotal role in the uptake of

Logit models are widely used by transport practitioners for forecasting. It is important that such models make appropriate use of existing independent base data, a process often referred to as “pivoting” and recommended by the UK Department for Transport’s Transport Appraisal Guidance. In the transport context, such base data typically relates to mode and destination shares. The general aim of pivoting

We examine the causal impact of flight ticket taxes on airline flights and derived CO2 emissions and analyse its distributional effects between airlines and travellers and within travellers. We use a dataset on flights within Europe at the airline-route level and apply a staggered difference-in-differences approach considering potential bias of the standard two-way fixed effects and the potential distorting

Achieving reliable connectivity in heterogeneous vehicular networks is a challenging task, owing to rapid topological changes and unpredictable vehicle speeds. As vehicular communication demands continue to evolve, multipath connectivity is emerging as an important tool, which promises to enhance network interoperability and reliability. Given the limited coverage area of serving access technologies

As part of a research effort towards greener aviation, this study focuses on the noise impact of aircraft operations around major airports. First, a pre-existing aircraft noise prediction platform based on a simplified (semi-empirical) approach is refined, to account for all refraction effects inherited from realistic (e.g., heterogeneous) atmospheres. To do so, the platform is enhanced with a more

The increased demand for automobile applications and connected-vehicles in the market has prompted much research into intelligent automotive antennas. Connected-vehicles are being used to change automotive technology and serve as a framework for a smart society. This paper presents a thirty-two-port hex-polarized massive multiple-input-multiple-output (MIMO) antenna that operates at GPS, Wi-Fi, and

We consider the problem of k agents using a communication channel restricted to n transmission slots. Each agent aims to broadcast its message repetitively so that at least one copy of it avoids collision, where the agent cannot observe channel status, and there is no a priori information about other agents except their approximate number. Motivated by time-sensitive vehicle coordination use cases

Managing the energy supply of electric buses (EBs) is critical to balance operational reliability and cost reduction. However, ambient temperature significantly affects energy consumption, posing challenges in providing adequate energy supply, especially in cold regions. In this study, we propose a double-battery configuration approach for EBs operating in cold regions with substantial temperature

This study discusses the possible benefits of inviting entrants for downstream retailers when facing the encroachment of their upstream manufacturers. We consider a model comprising one retailer, one manufacturer, and one potential entrant. The manufacturer decides whether to encroach or supply the retailer; The retailer decides whether to help a third-party firm overcome its entry barrier. We show

Despite decades of research on urban transportation, few researchers apply a holistic understanding of the urban transport mechanism. To address this gap, in this paper we employed a two-stage modeling approach using a system dynamics method and theory of path dependence. First, an exploratory model presents the structure, including feedback loops and underlying mechanisms of the evolution of car dependency

This paper aims to propose a novel Road Traffic Noise Model (RTNM), capable of dynamically assessing road traffic noise levels from reliable data (hourly traffic volumes and speed), supporting or replacing noise sensor networks, and addressing noise pollution concerns. RTNM is composed of two parts: i) the Vehicle Noise Specific Power model (for the assessment of the sound power level – Lw of passenger

Moving networks comprising of moving small cells (MoSCs) is an emerging technology that provide ubiquitous connectivity to the cellular users in vehicular environment. MoSCs are the small cells deployed on the top of vehicles (city buses, trains, trams etc.) to support the vehicular users with improved quality-of-service (QoS). However, the deployment of small cells in vehicular environment demands

Abstract not available

This paper develops the partial trajectory method to align the views from successive fixed cameras that are used for video-based vehicle tracking across multiple camera views. The method is envisioned to serve as a validation tool of whatever alignment has already been performed between the cameras to ensure high fidelity with the actual vehicle movements as they cross the boundaries between cameras

This paper studied the range-constrained traffic assignment problem (RTAP), where heterogeneous range anxiety is considered among the driving population by electric vehicles (EVs). In order not to get stranded en-route, each EV driver is assumed to have his/her own driving range limit for being able to complete the trip. As a result, two types of multi-class RTAP can be defined through discrete or

Abstract not available

This paper investigates an in-band full-duplex (IBFD) relaying, where a fixed-wing unmanned aerial vehicle (UAV) is dispatched as an amplify-and-forward relay to forward data from a source to a destination. By considering ideal and practical IBFD cases, new received signal-to-noise ratio (SNR) expressions at the destination are derived. Armed with the newly derived SNR expressions and the existing

The current COVID-19 virus pandemic has created massive disruptions in supply, demand, and production in global supply chains (SCs). The outbreak has revealed the deficiencies of non-resilient SCs. Business prosperity and continuity require internal resilience capabilities (IRCs) and resiliency to supply or demand fluctuations that create disruption risk situations. This paper develops a new methodology

This paper investigates bike-share activities and explores their relationships with neighborhood features, advancing our current knowledge for integrating cycle facilities into urban space to support first/last-mile mobility. To identify distinct demand patterns, bike stations are clustered based on time-series ridership. Measuring the similarity between time-series data in the transportation field

This research focuses on the profound impact of the shocks caused by the COVID-19 pandemic on the accuracy of AI-based demand forecasting in the beauty care industry. It aims to understand the key factors that led to decreased forecasting accuracy during the pandemic and employs causal mediation analysis to systematically investigate this complex issue. The empirical analysis is conducted using extensive

This study examines whether promoting electric cars (EVs) to achieve greener mobility undermines the efforts to reduce car use. It specifically explores the concept of moral licensing, wherein individuals use EVs as a way to feel good about their environmental impact while continuing to drive. The study uses travel data (n?=?1223) from Nord-J?ren, Norway, to develop a Structural Equation Model (SEM)

Urban freight emissions play a vital role in the overall CO2 emissions of the transportation sector. However, previous studies have mainly focused on the CO2 emissions of the entire transportation sector. This study addresses this gap by employing a bottom-up emission estimation model and constructing a high spatiotemporal resolution road freight emission inventory using GPS trajectory data from over

We study the problem of an Electric Vehicle (EV) having to travel from an origin to a destination in the shortest amount of time. We focus on long-distance settings, where the shortest path between the origin and the destination has energy requirements exceeding the EV autonomy. The EV may charge its battery at public Charging Stations (CSs), which are subject to unknown arrivals of exogenous vehicles

Decision making in terms of travel behavior is always dynamic; however, the future behavior of an individual is often inconsistent with their present plan. Therefore, this study aims to incorporate dynamic inconsistency into the expected utility of dynamic sequential choices with a novel structural estimation approach. The incorporation of dynamic heterogeneity into expected utility enables the illustrative

In this study, we address a dynamic network design problem pertaining to the distribution of essential supplies during the post-disaster response phase. We present a two-stage, stochastic multi-period model that minimizes both expected unmet demand and costs associated with operating emergency response facilities and distributing relief supplies, taking into account evolving road conditions as well

This study examines the equilibrium channel structure strategy in a supply chain where a manufacturer can sell products to consumers via/on an online platform, and firms may focus on both profit and consumer surplus. We consider three supply chain channel structures: a reselling channel (mode R), wherein the platform acts as the reseller; an agency channel (mode A), wherein the platform acts as the

Over the past years, the concept of ridesharing started receiving more attention to improve the sustainability of transportation systems. Although this concept has a lot of potential due to effective utilization of vehicles, there are still some challenges associated with routing and scheduling of the available vehicles, emissions produced by vehicles, and excessive delays in reaching the final destination

There is considerable interest in identifying factors of life satisfaction. However, current evidence on its relationships with the built environment (BE) and commuting has been limited to cross-sectional analyses, and few studies have identified gender differences in their links. Using two-wave survey data of 1002 pairs of spouses collected in 2014 and 2016, the study investigates the longitudinal

Despite recent advancements in the Freight Trip Generation (FTG) modelling literature, there is a lack of understanding on the effect of the choice of a regression model, measurement period (daily/weekly FTG), and spatial dependence on model fit and freight-related policies. This study addresses these research gaps by developing non-spatial and spatial autoregressive multiple linear regression and

The objective of this work is investigating on differences in pedestrians’ perceptions in terms of gender. Specifically, we want to verify differences between male and female in perceiving aspects characterizing pedestrian paths and influencing their satisfaction, perceived service quality, and behavioural intentions. We propose a methodology based on Partial Least Squares Structural Equation Modelling