Shuttle bus services play a vital role in public transit systems. However, conventional shuttle bus systems use the same type of buses and fixed departure timetables. They fail to meet the time-varying travel demand and do not consider the diversified characteristics of transit passengers. With the advent of the information era, communication among passengers, buses, and dispatching centers has become

Recorded aircraft trajectory data may vary significantly from predictions based on physics-informed models. This discrepancy may be attributed to inadequacies in the trajectory prediction models, including errors in modeling aircraft dynamics, and omission of inputs such as weather data, equipment malfunctions, and pilot errors. In this work, we represent model errors as additional external inputs

This work focuses on traffic parameters estimation based on trajectory data in an arterial corridor with multiple signalized intersections. We develop a general framework that can combine various traffic flow models with Bayesian Network (BN) for estimating the overall traffic parameters using partially observed vehicle trajectory data (with unknown penetration rate). The BN is formulated to establish

Connected vehicles (CVs) can considerably contribute to traffic control in the near future by providing real-time information. Such information can be exploited to identify the current traffic condition. However, challenges resulting from a high volume of data and lack of perfect knowledge in mixed traffic scenarios (consisting of CVs and conventional vehicles) have led to relatively sparse research

The Internet of Vehicles (IoV) provides an important platform for various applications in diverse vehicular sectors such as the safety, energy-saving, decision-making, routing, and entertainment, which makes vehicular transportation safer, greener, and easier. While providing convenient and efficient communications between vehicles, the wireless channel in IoV also faces an eavesdropping problem in

Transportation and inventory are essential to hazardous materials logistics, while different classes of hazardous materials are often transported over a network simultaneously. Despite their in-transit and storage incompatibility, the superimposed risks among different materials, which results from possible chemical reaction once accidents (e.g., leakage, explosion) happen, further complicate the comprehensive

This study investigates how the exercise of market power affects the economic efficiency and revenue sharing in a bi-level market, which integrates upstream contract market and downstream wholesale market. We consider price volatility and identify Nash equilibrium restricted by the data envelopment analysis (DEA)-estimated capacity constraint. This study develops stochastic mixed complementarity problems

We have witnessed the rapid growth and impact of Transportation Research Part E: Logistics and Transportation Review (TRE) in both supply chain and transportation communities since it was founded in 1997 with a particular focus on logistics and transportation. To celebrate the 25th anniversary of TRE (1997–2021), we aim to investigate impactful research topics addressed by TRE in the past 25?years

The COVID-19 pandemic has drastically impacted people’s travel behaviour and introduced uncertainty in the demand for public transport. To investigate user preferences for travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N=961). We analysed the collected data using multinomial and latent class logit models. Our discrete choice analysis

The optimal deployment of public charging infrastructure is critical to the popularisation of electric vehicles (EVs) in high-density cities. Existing studies on public EV charging facilities have rarely integrated government policy and spatial constraints into their optimisation algorithms. To address this research gap, we proposed a contextualised EV charger optimisation model that incorporates carefully

The literature about tradable credit schemes (TCS) as a demand management system alleviating congestion flourished in the past decade. Most proposed formulations are based on static models and thus do not account for the congestion dynamics. This paper considers elastic demand and implements a static TCS to foster modal shift by restricting the number of cars allowed in the network over the day while

We investigate a model in which a monopoly supplier distributes two types of its product, physical and electronic products, through a traditional/brick-and-mortar retailer with a wholesale price contract and an online retailer with an agency contract, respectively. The supplier and the online retailer negotiate the royalty rate, which is a ratio of the online retailer’s revenue to the entire revenue

The vehicle dispatching system is one of the most critical problems in online ride-hailing platforms, which requires adapting the operation and management strategy to the dynamics of demand and supply. In this paper, we propose a single-agent deep reinforcement learning approach for the vehicle dispatching problem called deep dispatching, by reallocating vacant vehicles to regions with a large demand

The optimal routing of a single vacant taxi is formulated as a Markov Decision Process (MDP) problem to account for profit maximization over a full working period in a transportation network. A batch offline reinforcement learning (RL) method is proposed to learn action values and the optimal policy from archived trajectory data. The method is model-free, in that no state transition model is needed

This paper proposes techniques to improve the efficiency of transportation activities within hospitals. Transportation is a major activity in hospitals which requires management efforts to improve its efficiency and increase the quality of patient services. One of the most powerful ways of achieving more efficiency of transportation systems in hospitals is via the labor-saving technology of logistics

Factors driving the choice of shipper firms for services of logistics service providers have long been recognized in the freight transportation literature. However, the willingness among shippers to choose flexible transportation services, where the service package can be adapted during planning and execution, has received less attention. In particular, little is known about the contextual circumstances

It is highly uncertain which zero-emissions vehicle (ZEV) drivetrains are most suitable for heavy-duty trucks and there is little exploration of how these technologies might compete in the long-term. We used a dynamic model representing technology, cost, and behavioral parameters to simulate adoption of various drivetrains, including battery electric vehicles (BEVs) and fuel cell vehicles (FCVs), in

Noise and greenhouse gas (GHG) emissions are two of the main externalities caused by road transport. At the EU and national levels, many efforts have been implemented to reduce them. Photovoltaic noise barriers (PVNBs) are a technical solution conceived for such a joint objective. This paper presents a method of calculating the efficiency of PVNBs through a cost-benefit analysis by considering current

To evaluate the effects of asphalt pavement characteristics on traffic noise reduction in different frequencies, stone mastic asphalt with crumb rubber and porous asphalt concrete were prepared. Dynamic modulus test, air voids test, standing wave tube test, improved tire acceleration method, water submerged test and voids-clogging test were utilized. The results showed that the deformation characteristics

This paper develops an infrastructure-enabled eco-approach specifically for transit systems, where a two-stage simulation approach is proposed to include the impact of bus stops, and can further quantify the effects of infrastructure-enabled eco-approach on transit operating and service. The developed system is then embedded into a well-developed simulation environment, i.e., Simulation of Urban Mobility

Cities all around the world struggle with urban air quality due to transportation related emissions. In public transport networks, replacing internal combustion engine buses by electric buses provides an opportunity to improve air quality. Hence, many bus network operators currently ask for an optimal transformation plan to integrate battery electric buses into their fleet. Ideally, this plan also

This study deals with a fundamental electric bus charging scheduling (EBCS) problem for a single public transport route by considering the nonlinear electric bus (EB) charging profile and battery degradation effect under the partial charging policy, which allows EBs to be charged any length of time and make good use of dwell times between consecutive trips. Given a group of trip tasks for an EB fleet

For evacuations, people must make the critical decision to evacuate or stay followed by a multi-dimensional choice composed of concurrent decisions of their departure time, transportation mode, route, destination, and shelter type. These choices have important impacts on transportation response and evacuation outcomes. While extensive research has been conducted on hurricane evacuation behavior, little

Recently, the International Maritime Organization (IMO) and government sectors have enacted several stringent regulations to curb the emissions of ships. Green fuel and scrubber installation are two prevailing adaptation strategies used by ships to reduce emissions. Green fuel leads to a high shipping cost with the consumption of low-sulphur but highly-priced oil, while scrubber installation is a long-term

This paper performs a novel data-driven approach to optimize electric vehicle (EV)?public charging. We translate the study area into a directed graph by partitioning it into discrete grids. A modified geographical PageRank (MGPR) model is developed to estimate EV charging demand, built upon trip origin–destination (OD)?and social dimension features, and validated against real-world charging data.?The

Deployment and management of environmental infrastructures, such as charging infrastructure for Electric Vehicles (EV), is a challenging task. For policy makers, it is particularly difficult to estimate the capacity of current deployed public charging infrastructure for a given EV user population. While data analysis of charging data has shown added value for monitoring EV systems, it is not valid

Road grade is crucial in vehicle control and emission studies but challenging to obtain in large-scale road networks due to current methods’ expensive deployment costs or limited accuracy. This paper proposed a scale-deployable and cost-efficient road grade estimation solution based on the fuel consumption rate (FCR) difference between flat and graded roads. Real-world road grades from design drawings

Merging sections on freeways are typical bottlenecks for traffic efficiency and safety. The connected and automated vehicles (CAV) technology has great capability in improving traffic performance of merging bottlenecks. Current approaches of system optimal cooperative merging control assume single fixed merging point (CMC-SMP) for on-ramp vehicles to reduce the complexity of their models. Non-fixed

A significant increase in the use of electronics control units (ECUs) in modern vehicles has made controller area network (CAN) a de facto standard in the automotive industry. CAN standard has been designed as a reliable and straightforward broadcast-based protocol for providing serial communication between ECUs without considering security aspects like authentication and encryption. Cyber attackers

This study advances prediction of population evacuation behavior during hurricanes by comprehensively comparing five different models based on their practical utility for future hurricanes. The models—participation rate (PR-S), logistic regression (LR-S), random parameter logit (RPL), time-dependent Cox (TD-Cox), and dynamic discrete choice (DDC)—were fitted using population survey and hurricane data

Considering the lack of adequate cycling infrastructure networks in many cities, decision makers must face the challenge of designing connected bicycle facility networks to ensure safe and comfortable access to urban opportunities for cyclists and the usability of infrastructure. This paper addresses the maximal covering bicycle network design problem (MCBNDP). MCBNDP involves making investment decisions

Increasing commercial vehicles are equipped with automated driving features. Adaptive cruise control, a critical longitudinal control system of commercial automated vehicles (AVs), may have significant impacts on fuel consumption. To investigate the impacts, this paper collected high-resolution trajectory data of commercial AVs with different operating scenarios, speed ranges, and headway settings

Freight delivery planning is a critical area in transportation and logistics. This paper presents a planning-level model for jointly optimizing headways and zone sizes for flexible-route freight deliveries. The model analyzes deliveries for a one-to-many demand pattern from one terminal to random destinations in a zone, which are reached through approximated travelling salesman problem (TSP) tours

This paper leverages the “Mechanism Design” theory to design the ridesharing-based transit feeder service with mixed scheduled and on-demand passenger requests. An online hybrid mechanism is proposed with four incentive objectives: promoting passengers to participate by satisfying their mobility preferences, inducing passengers to truthfully reveal their mobility preferences, incentivizing the service

Reinforcement learning (RL) can learn from past failures and has the potential to provide self-improvement ability and higher-level intelligence. However, the current RL algorithms still suffer from challenges in reliability, especially compared to the rule/model-based algorithms that are pre-engineered, human-input intensive, but widely used in autonomous vehicles. To take advantages of both the RL

Heterogeneity is widely observed in various aspects of urban transport, such as road types, vehicle dynamics, and demand patterns, which greatly complexifies transport systems and hinders the successful control and management of traffic. On one hand, intelligent strategies are required to relieve the loss of efficiency caused by the mixed traffic flow composed of vehicles with different speeds; on

Data are important components of any research; however, it is often the case that the required data are not readily available. Researchers often fuse multiple datasets to obtain the data required to complete their work. In urban simulation, spatially referencing data is of paramount importance to capture local variations in travel and preferences. Data fusion typically obfuscates the spatial reference

Max-pressure signal control has been analytically proven to maximize the network throughput and stabilize queue lengths whenever possible. Since there are many transit lines operating in the metropolis, the max-pressure signal control should be extended to multi-modal transportation systems to achieve more widespread usage. The standard max-pressure controller is more likely to actuate phases during

Electrification of transportation is an important option to reduce fossil fuels consumption and carbon emissions. However, electric vehicles (EVs) comprise less than 1.2% of New Zealand’s light vehicle fleet, and there are significant hurdles to limit EV uptake. This study uses spatial negative binomial regression models to estimate spatio-temporal factors that influence consumers’ purchase decisions

Pooled-ride services have a significant potential for reducing traffic externalities and enhancing transportation systems in the urban environment. These services and their users’ characteristics still need further inspection and exploration. We investigated factors encouraging the shift from the currently used modes to pooled-ride-services, the choice between different pooled services vehicles types

Traffic conflict techniques are a viable alternative to crash-based safety assessments and are particularly well suited to evaluating emerging technologies such as connected and automated vehicles for which crash data are sparsely available. Recently, the use of multiple traffic conflict indicators has become common in methodological studies, yet it is often difficult to determine which conflict indicators

The outbreak of SARS-COV-2 has led to the COVID-19 pandemic in March 2020 and caused over 4.5 million deaths worldwide by September 2021. Besides the public health crisis, COVID-19 affected?the global?economy and development significantly. It also led to changes in people’s mobility and lifestyle during the COVID-19 pandemic. In addition to short-term changes, the drastic transformation of the world

Alternatives to conventional diesel engines in medium/heavy-duty commercial trucks offer promising solutions to decarbonize road freight. We compare the life cycle greenhouse gas (GHG) emissions from diesel, battery electric (BEV) and hydrogen fuel cell (FCV) medium-duty urban delivery trucks (gross vehicle weight 3.5 – 7 metric tonnes) in Singapore, including the vehicle and fuel production, use phase

This paper studies the channel choice problem in an e-retailing market when a reseller and an agency seller are experimenting with a new format, i.e., a hybrid retailing strategy. Under this strategy, the reseller not only sells products to consumers directly, but also expands the market in collaboration with the agency seller who operates a platform. However, the motivation and effectiveness of this

We develop an actionable data-driven approach to a periodic-review dual sourcing inventory management system in the presence of purchase price and demand uncertainties. The two supply sources differ in their lead times and prices due to, e.g., different transportation modes. We adopt robust optimization because the limited historical data is insufficient to construct meaningful distributions to characterize

Introducing a downside risk model, this paper examines the impacts of two conflicting behavioral factors, backer warm-glow effect and creator risk aversion, on the creator’s optimal decisions of selling price and financing target of an All-or-Nothing reward-based crowdfunding project. We find that a less risk-averse creator should choose a high-price high-financing-target strategy when backer warm-glow

Although e-scooter sharing has become increasingly attractive, little attention has been paid to a comprehensive comparison of e-scooter sharing mobility in multiple cities. To fill this gap, we conduct a comparative study to reveal the similarity and difference of e-scooter sharing mobility by collecting and analyzing vehicle availability data from 30 European cities during post COVID-19 pandemic

Information perturbation is an information provision strategy which strategically alters the traffic information sent to drivers, aiming to mitigate network congestion caused by selfish routing decisions. Previous works have integrated information perturbation into coordinated routing mechanisms and theoretically proved that the system performance improvement due to information perturbation is more

With a few exceptions, public transport ridership around the world has been hit hard by the COVID-19 pandemic. Travellers are now likely to adapt their behaviour with a focus on factors that contribute to the risk of COVID-19 transmission. Given the unprecedented spatial and temporal scale of this crisis, these changes in behaviour may even be sustained after the pandemic. To evaluate travellers’ behaviour

This paper analyzes and evaluates several policies aiming to mitigate the congestion effect a Transportation Network Company (TNC) brings to bear on an idealized city that contains a dense central core surrounded by a larger periphery. The TNC offers both solo and pooling e-hail services to the users of public transport. We develop a spatial market equilibrium model over two building blocks: an aggregate

Determining the likelihood of consumers purchasing automated vehicles (AVs) is extremely important for policymakers, researchers, and automobile manufacturers. Successful penetration of AVs into the market depends on the end-user’s perception and their affinity towards these vehicles. In this study, a comprehensive state-wide data has been used to determine the factors affecting the purchase likelihood

Using modeling techniques as Ordinary Least Squares-OLS, this paper studies the main variables that affect service trip generation (STG) (production and attraction) by the service sector (e.g., maintenance, repairs) in commercial establishments located in urban areas of developing countries. Data obtained from Medellin Metropolitan Area (Colombia) origin–destination freight surveys conducted in 2017–2018

During a pandemic such as COVID-19, managing public transit effectively becomes a critical policy decision. On the one hand, efficient transportation plays a pivotal role in enabling the movement of essential workers and keeping the economy moving. On the other hand, public transit can be a vector for disease propagation due to travelers’ proximity within shared and enclosed spaces. Without strategic

This paper studies the optimal planning of public transit services with modular vehicles. In the modular service operation, the vehicle is comprised of smaller modular units/pods, which can be assembled/dissembled at some specially designed transit stations. The planning decisions are to determine the locations of the specially constructed stations enabling station-wise assembling/dissembling of modular

Time-dependent order cancellation behaviour affects ridesourcing platform operation and overall system performance. This paper models impacts of time-dependent order cancellation behaviour on the driver–rider matching efficiency and examines ridesourcing platform operation strategies, where taxi is the alternative to the ridesourcing mode. A time-dependent matching model is developed to characterize

A controller area network (CAN) is a communication protocol for in-vehicle networks. Communication between electronic control units (ECUs) is facilitated by the CAN bus. This communication protocol provides no authentication or encryption to prevent the consequences of cyberattacks. As a security measure for this protocol, we have proposed an intrusion detection system (IDS) using a convolutional neural

Online customization is very popular among consumers in current e-commerce because of its flexible customization time and diverse product attributes. This paper establishes a dual-channel supply chain composed of one manufacturer and one retailer under mass customization. The manufacturer sells standard products offline via the retailer when providing modular customized products online. Two online

In recent years, automated vehicles have attracted much attention all over the world. This paper focuses on the freeway-exiting position decision problem of automated vehicles (AVs). Specifically, the paper addresses the determination of the lane-changing initiation location in the process of exiting the freeway. The location of the freeway-exiting decision point has a significant impact on the safety