Bo Du

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Verified

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• PhD
• Senior Lecturer at Griffith University

Assessment of the resilience of an urban rail transit (URT) network under natural disasters is of practical importance, especially with the intensification of global warming. This study develops a train schedule-based resilience assessment model to assess the resilience of a URT network under natural disasters, addressing a critical gap in existing...

Effective traffic signal control (TSC) is crucial in mitigating urban congestion and reducing emissions. Recently, reinforcement learning (RL) has been the research trend for TSC. However, existing RL algorithms face several real-world challenges that hinder their practical deployment in TSC: (1) Sensor accuracy deteriorates with increased sensor d...

Unlike most urban rail transit (URT) resilience studies on URT lines or networks under major disturbances, this paper focuses on the resilience assessment of URT stations under high‐frequency daily disturbances with minor impacts. A resilience assessment metric with different resilience levels is proposed, which is calculated based on multiple crit...

This study tends to investigate pedestrian injury risk by combining density peak clustering (DPC) with familiar Bayesian spatial-temporal epidemiological models. The dataset was collected from 2019 to 2022 in the Chicago Metropolitan area. First, the DPC method was employed to cluster all the pedestrian crash injuries; Second, after preprocessing a...

With their inherent attributes such as mobility, flexibility, and adaptive altitude, Unmanned Aerial Vehicles (UAVs) can potentially enable Intelligent Transportation Systems (ITS) to be more efficient by playing the role of aerial base stations for data collection, data analysis, and communication networks. Their ability to access hard-to-reach lo...

Dynamic ridesharing has gained significant attention in recent years. However, existing ridesharing studies often focus on optimizing order dispatching and vehicle repositioning separately, leading to short-sighted decisions and underutilization of the ridesharing potential. In this paper, we propose a novel joint optimization framework called JODR...

Unmanned Aerial Vehicles (UAVs) have immense potential to enhance Intelligent Transport Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and infrastructure inspection, leading to rich data collection, lower response times, and efficient urban mobility management. Machine learning (ML) is a crucial component in UAV-assist...

With the rapid development of shared e-scooters, it is essential to understand their usage patterns for formulating informed e-scooter fleet management policies. This study first analyzes the usage pattern of shared e-scooters in Indianapolis, USA, by mining big e-scooter trip data. The analysis reveals an oversupply of shared e-scooters relative t...

div>Accurate prediction of the demand for shared bicycles is not only conducive to the operation of relevant enterprises, but also conducive to improving the image of the city, facilitating people’s travel, and solving the balance between supply and demand of bicycles in the region. To precisely predict the demand of shared bicycles, a model combin...

The knowledge development of the influence mechanism for the operational performance of large passenger railway stations (OPLPRS) is of great significance for station managers in making comprehensive management decisions, particularly in determining the decision direction under limited allocatable resources. Hence, this paper is dedicated to conduc...

Cryo-Electron Tomography (cryo-ET) is a 3D imaging technology facilitating the study of macromolecular structures at near-atomic resolution. Recent volumetric segmentation approaches on cryo-ET images have drawn widespread interest in biological sector. However, existing methods heavily rely on manually labeled data, which requires highly professio...

In the public transportation system, punctuality benefits both bus operation and passengers’ travel experience. However, uncertainty exists due to complex traffic conditions and heterogeneous driving behaviors. To analyze bus operational uncertainty, transport planners and bus operators need a tool that supports multi-granular modeling, spatio-temp...

The COVID-19 pandemic has caused major disruptions to people’s daily life and travel. This paper aims to reveal the impact of the COVID-19 pandemic on people’s travel in New South Wales (NSW), Australia, and to explore potential measures to recover public transport patronage in the new normal. Research data is collected from a survey of 1,045 resid...

Vehicle re-identification (v-reID) is a crucial and challenging task in the intelligent transportation systems (ITS). While vehicle re-identification plays a role in analysing traffic behaviour, criminal investigation, or automatic toll collection, it is also a key component for the construction of smart cities. With the recent introduction of tran...

Disruptions occurring at an urban rail transit (URT) system can severely affect its normal operations, and an effective bus bridging service (BBS) is able to help to reduce the negative effects. Transit operators usually arrange BBS to depart from the disrupted stations to evacuate the stranded passengers. However, the overload of passengers at the...

Adding new links to an existing urban rail transit (URT) network helps improve its operations by shortening passenger travel time under normal operations and disruptions. However, only a few studies have considered the impact of uncertain disruption occurrence stations on URT network design. This paper addresses this gap by proposing and solving a...

Metro systems play an important role in reducing urban traffic congestion and promoting the sustainable development of urban transport in megacities. With the expansion of a metro network, transfer stations are necessary for increasing the service connectivity of a metro network. An accurate estimation of transfer passenger flow can help improve th...

As the advancement of driverless technology, together with information and communication technology moved at a fast pace, autonomous vehicles have attracted great attention from both industries and academic sectors during the past decades. It is evident that this emerging technology has great potential to improve the pedestrian safety on roads, mit...

The rapid evolution of technology in connected automated and autonomous vehicles offers immense potential for revolutionizing future intelligent traffic control and management. This potential is exemplified by the diverse range of control paradigms, ranging from self-routing to centralized control. However, the selection among these paradigms is be...

Interactions and conflicts between vulnerable road users, mainly pedestrians and cyclists, are frequently observed on crosswalks, especially in urban areas with relatively high traffic volume. To alleviate the potential safety risks, one possible measure is to adopt the segregated crosswalk to provide separate crossing space for pedestrians and cyc...

The resilience of an urban rail transit (URT) network when faced with disruptions is affected by the locations of stations equipped with turn-back (TB) tracks. However, limited studies have enhanced the resilience of a URT network by setting new TB tracks. The present work addresses this gap by proposing and solving a scenario model for improving t...

In daily operation, urban rail transit (URT) systems often experience disturbances that result in a partial reduction in transport capacity (partial disturbances, PDs) rather than disturbances leading to a complete reduction in transport capacity. However, research that assesses the resilience of URT networks under PDs remains limited. This paper a...

With the increasing severity of global warming, rainstorms are occurring more frequently and severely affect the normal operation of transportation systems. Therefore, the ability of a highway-railway complementary (HRC) network to cope with rainstorms is examined. A resilience assessment model was used considering the rainfall intensity and its sp...

Traffic signal control (TSC) systems are one essential component in intelligent transport systems. However, relevant studies are usually independent of the urban traffic simulation environment, collaborative TSC algorithms and traffic signal communication. In this paper, we propose (1) an integrated and cooperative Internet-of-Things architecture,...

The advancement of technologies for autonomous vehicles (AVs) provides great potential for intelligent traffic control and management in the future. The deployment of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) communications enable traffic control on road segments, intersections or regional road networ...

Existing studies estimate the economic value (EcV) of network reliability and robustness separately. In this study, a model is proposed for estimating the EcV of reserve capacity in a rail transit network (RTN), which consists of: (1) the reduction of passengers' total generalized travel cost (GTC) in normal operations, (2) the EcVof reliability en...

The significance of intelligent transportation systems and artificial intelligence in Road transportation networks has made the prediction of traffic flow a subject of discussion among transportation engineers, urban planners, and researchers in the last decade. However, limited research has been done on traffic flow modelling of long and short tru...

Cruising of electric ride-sourcing vehicles (ERVs) when waiting for trip orders can create additional vehicle miles, which increase congestion and waste electricity. Reducing cruising is an important issue. This study investigates the strategy of allocating a portion of road space as parking for ERVs. Considering ERVs cruising for parking/charging,...

The COVID-19 pandemic has affected people's lives worldwide. Among various strategies being applied to addressing such a global crisis, public vaccination has been arguably the most appropriate approach to control a pandemic. However, vaccine supply chain and management have become a new challenge for governments. In this study, a solution for the...

Bus passengers and cyclists often interact with each other at bus stops, which causes potential conflicts and safety risks. However, the safety impact of different types of bus stops on vulnerable road users has received limited attention. This study measures the safety impact of different types of bus stops on the interactions between passengers a...

Road safety has long been considered as one of the most important issues. Numerous studies have been conducted to investigate crashes with significant progress, whereas most of the work concentrates on the lifespan period of roadways and safety influencing factors. This paper undertakes a systematic literature review from the crash procedure to ide...

Micro-mobility vehicles (MMVs), including a range of small-size and light-weight vehicles such as (e-)bicycles and (e-)scooters, are becoming more popular and widely used, which also brings a challenge to the efficient and safe utilisation of road infrastructure. Especially, the coexistence of pedestrians and MMVs in a space sharing context raises...

Joint deployment of solar photovoltaic (PV) systems and electric vehicles (EVs) offers a sustainable option for decarbonisation. However, the possible influence of solar PV on EV uptake within a spatial-temporal framework is often overlooked in the literature. Based on a unique dataset at a detailed spatial level in Auckland, New Zealand, this stud...

Joint deployment of solar photovoltaic (PV) systems and electric vehicles (EVs) offers a sustainable option to decarbonise the economy. However, the possible influence of solar PV on EV uptake within a spatial-temporal framework is often overlooked in the literature. Based on a unique dataset at a detailed spatial level in Auckland, New Zealand, th...

The rapid urbanisation in cities, and its associated complexities demand that sophisticated decision support tools such as the LUTI models be employed to assist the balanced and sustainable development of transport and land use. It is evident from literature studies that the majority of LUTI models need extensive data, making them expensive and tim...

Deep reinforcement learning (DRL) is becoming increasingly popular in implementing traffic signal control (TSC). However, most existing DRL methods employ fixed control strategies, making traffic signal phase duration less flexible. Additionally, the trend of using more complex DRL models makes real-life deployment more challenging. To address thes...

As an emerging innovative public transit service, the app-based demand-responsive feeder transit (DRFT) incorporated with a mobility-as-a-service (MaaS) platform provides on-demand, customized and flexible travel service. It serves as a good alternative for providing the first- and last-mile transport service. The study addresses the routing design...

With the development of charging technology, chargers with dropped price and increased charging power make fast charging more applicable and competitive to provide efficient and effective charging solution to electric vehicles. Compared to normal chargers, fast chargers can top up battery in a short time, which enables battery electric buses to get...

Forecasting return and profit is a primary challenge for financial practitioners and an even more critical issue when it comes to forecasting energy market returns. This research attempts to propose an effective method to predict the Brent Crude Oil return, which results in remarkable performance compared with the well-known models in the return pr...

Operational disturbances within 30 min, namely, short-term operational disturbances (STODs), occur frequently during the daily operation of an urban rail transit (URT) system. Therefore, there is an urgent need to assess a network’s ability to respond to STODs to improve its operational level. The resilience of a URT network jointly considering tur...

The continuous improvement of charging technologies makes fast charging applicable to overcoming the limited driving range of electric vehicles by providing en-route opportunity charging. Fast chargers can be deployed at bus stops to top up the battery for an electric bus during its dwelling time when passengers board and alight, which allows the u...

Many studies confirmed that a proper traffic state representation is more important than complex algorithms for the classical traffic signal control (TSC) problem. In this paper, we (1) present a novel, flexible and efficient method, namely ad- vanced max pressure (Advanced-MP), taking both running and queuing vehicles into consideration to decide...

Calculating trips from each traffic zone is one of the essential steps in the four-step model. Multiple linear regression (MLR) is the most popular among the various methods available for calculating trips. The main limitation of this method is its reliance on independent variables related to the zone. Due to the assumptions in this method, future...

Dedicated cycleway is usually used to keep cyclists away from motorised vehicles in some countries like China. As a result, potential traffic conflicts between bus passengers and cyclists are frequently observed, which lead to potential safety issues for both passengers and cyclists. To our best knowledge, such conflicts and potential safety risk a...

Traffic signal control (TSC) is an established yet challenging engineering solution that alleviates traffic congestion by coordinating vehicles' movements at road intersections. Theoretically, reinforcement learning (RL) is a promising method for adaptive TSC in complex urban traffic networks. However, current TSC systems still rely heavily on simp...

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...

Stochastic demands can impact the quality and feasibility of a solution. Robust solutions then become paramount. One way to achieve robustness in the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD) is to add a measure of the second-stage (recourse) distance to the objective function of the deterministic problem. We adopt varian...

Different from the existing train delay studies that had strived to explore sophisticated algorithms, this paper focuses on finding the bound of improvements on predicting multi-scenario train delays with different machine learning methods. Motivated by the observation of deep learning methods failing to improve the prediction performance if the de...

With advanced artificial intelligence and deep learning techniques, a growing number of data sources are playing more and more critical roles in planning and operating transportation services. The General Transit Feed Specification (GTFS), with standard open-source data in both static and real-time formats, is being widely used in public transport...

As supplying adequate blood in multiple countries has failed due to the Covid-19 pandemic, the importance of redesigning a sensible protective-resilience blood supply chain is underscored. The outbreak-as an extensive disruption-has caused a delay in ordering and delivering blood and its by-products, which leads to severe social and financial loss...

Recently, finding fundamental properties for traffic state representation is more critical than complex algorithms for traffic signal control (TSC).In this paper, we (1) present a novel, flexible and straightforward method advanced max pressure (Advanced-MP), taking both running and queueing vehicles into consideration to decide whether to change c...

Since conventional approaches could not adapt to dynamic traffic conditions, reinforcement learning (RL) has attracted more attention to help solve the traffic signal control (TSC) problem. However, existing RL-based methods are rarely deployed considering that they are neither cost-effective in terms of computing resources nor more robust than tra...

In many big cities, train delays are among the most complained-about events by the public. Although various models have been proposed for train delay prediction, prior studies on both primary and secondary train delay prediction are limited in number. Recent advances in deep learning approaches and increasing availability of various data sources ha...

Electric Vehicles (EVs) are regarded as a feasible solution to achieving decarbonisation in the transportation sector. However, EVs powered by fossil dominated energy sources may offer a discounted solution. This paper presents a comparative study of Australian and New Zealand’s vehicle markets on Greenhouse Gas (GHG) emissions and energy consumpti...

Proper vehicle scheduling and charging scheduling play an essential role in an efficient, effective and economical (3E) operation of electric bus fleet. An optimal vehicle scheduling can minimise the number of required electric buses and deadhead trips. Compared to normal plug-in charging at depot, fast charging at stops can reduce the required bat...

This paper studies the empty container repositioning (ECR) problem considering the exchange of slots and empty containers among liner shipping companies. It is common for an individual shipping company to seek an optimal solution for ECR and cargo routing to maximize its own benefits. To achieve cooperation among shipping companies, a multi-stage s...

As a common phenomenon, overtaking behaviour is frequently observed on pedestrian flow, which not only reshapes pedestrian flow but also generates adverse impacts on pedestrian safety to some extent. Prior research focused on unidirectional pedestrian modelling, especially with overtaking behaviour, is limited. Moreover, pedestrian behaviour in the...

Eco-driving has attracted great attention as a cost-effective and immediate measure to reduce fuel consumption significantly. Understanding the impact of driver behaviour on real driving emissions (RDE) is of great importance for developing effective eco-driving devices and training programs. Therefore, this study was conducted to investigate the p...

Electrification of transport fleet is considered one of the most viable options to reducing the reliance on fossil fuels and carbon emissions. However, there are still significant hurdles associated with electric vehicle (EV) uptake. Electric fleet only make up to less than 1.2% of the total vehicle fleet in New Zealand. Based on spatial negative b...

Access to transport for older people is inherently related to the right to lead an independent life and to participate in social and cultural life with dignity. Yet often transport planning strategies prioritise the smooth flow of urban commuters, while people over the age of 60 are at risk of experiencing marginalisation and inequality. In this pa...

This study develops a methodology to determine the optimal allocation position to deploy the bikes in a competitive dockless bike sharing market. The community structure approach in complex network theory is utilized to offer the bike allocation strategies to the market leader in two specific market regimes, with a potential competitor, and without...

This research presents a comparative study of Internal Combustion Engines (ICEs), Hydrogen Electric Vehicles (HEVs), Battery Electric Vehicles (BEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) from an economic and environmental perspective based on a Well-To-Wheel (WTW) analysis. The vehicle is simulated to run on a standard European Community E...

With the aid of advanced information technology, car parking space management is evolving dramatically toward an automatic way. The most efficient approach for parking-spot detection is based on embedded sensors, which can cause a significant cost of equipment purchasing, installation, and maintenance. Therefore, a growing number of studies have be...

50 FREE online copies are available via the link below: https://www.tandfonline.com/eprint/UZDJ4KJYGQUCPWZNIXPU/full?target=10.1080/03088839.2020.1803431 [ABSTRACT] Repositioning empty container and leasing container from leasing company are mainly the outcomes of imbalance in trade flows. How to make decision on repositioning or leasing remains a...

Bus bunching, a phenomenon due to the failure of headway or timetable adherence, often causes low level of public transit service with poor bus on-time performance and excessive passenger waiting time. To mitigate bus bunching, an accurate and real-time prediction method plays an important role. In this paper, we propose a supply-demand seq2seq mod...

This article introduces a solution approach for the Stochastic Capacitated Vehicle Routing Problem (SCVRP) with uncertain demands, called Robust Simulation-Based (RoSi) approach. RoSi aims at designing route plans that can be more or less robust based on a decision-maker weight, i.e. solutions that resist demand changes with marginal additional (re...

Bus bunching is a result of sophisticated traffic condition, unstable bus operation and dynamic travel demand, which not only causes passengers' dissatisfaction, but also degrades the bus service performance. To tackle the bus bunching issue, multiple steps are usually adopted, from bus bunching identification to solution development. This paper se...

Because of the expected shift from ordinary to autonomous vehicles, the role of public transport (PT) will have to be enhanced, and thus there is a need to pay more attention to its design procedures and evaluation processes. This study compares previous models and methodologies by creating a quality-evaluation platform that enables a comparison of...

Consider a travel corridor with a multi-modal transport system (highway and railway) that connects continuous residential locations to city center. All commuters travel along the corridor from home to work in the morning peak hour. The spatial dynamics of the traffic congestion on both transportation systems are determined by the trip-timing condit...

This paper studies on modelling and solving spatial and dynamic equilibrium travel pattern in a travel corridor. Consider a travel corridor connecting continuously distributed commuters to the city centre. The traffic is subject to flow congestion and the commuter heterogeneity is captured. The traffic flow dynamics is described by flow continuity...

To satisfy growing travel demand and reduce traffic congestion, the continuous network design problem (CNDP) is often proposed to optimize road network performance by the expansion of road capacity. In the determination of the equilibrium travel flow pattern, equilibrium principles such as deterministic user equilibrium (DUE) and stochastic user eq...