Recent Articles

Open access

ISSN: 2046-0430
CN: CN31-2204/U
e-ISSN: 2046-0449

Optimized deep learning for pedestrian safety in autonomous vehicles

This study focuses on enhancing pedestrian detection for autonomous driving and intelligent surveillance systems, where challenges like complex backgrounds, obstructions, and small target sizes can...

Modeling response time and hazard identification in a video-based hazard perception test for car drivers

This study aimed to evaluate hazard perception ability of car drivers by analyzing response time and hazard identification performance measures. A video-based test method was selected to evaluate hazard...

The cooperative inspection routing problem for urban environmental management

Urban environmental management against air pollution is of critical importance to public health. Despite the proliferation of ubiquitous air quality sensors and advancement of information systems, an...

Deep charge-fusion model: advanced hybrid modelling for predicting electric vehicle charging patterns with socio-demographic considerations

This study examines electric vehicle (EV) charging behaviors across 5 898 participants from various socio-demographic backgrounds, using both statistical analysis and deep learning models. Exploratory...

Enhancing autonomous vehicle safety: an integrated ensemble learning-logit model for accident severity prediction and analysis

•Developed an Integrated Ensemble Learning −Logit Model for predicting AV accident severity.•High-level automation systems (SAE 3–5) significantly reduce accident severity compared to lower automation...

Exploring time allocation patterns for daily activities through a discrete choice modeling approach

This study examines human daily mobility patterns by analyzing activity duration choices through discrete choice models, offering insights into travel behaviors across diverse geographic and cultural...

Intelligent vehicle routing for stochastic service times: a grouping evolution strategy approach

After-sales service companies often need to transport and distribute their products, as well as provide services like installation and setup. In this paper, we study a vehicle routing problem (VRP)...

Erosion-enhanced rain optimization algorithm for efficient blood bag transport in multimodal healthcare logistics

•The Erosion-Enhanced Rain Optimization Algorithm (ROA) dynamically adapts to route degradation, optimizing logistics for blood bag transport using trucks and drones in multimodal networks.•The algorithm...

A robust deep learning-based system for pedestrian-aware collision prevention in autonomous vehicles

Pedestrian collisions remain a critical concern in road safety research due to pedestrians’ heightened vulnerability and the substantial impacts on road networks and public healthcare systems. These...

Investigating safety implications of median U-turn (MUT) intersections based on dilemma zone and critical gap analysis

Median U-turn (MUT) intersections present a distinctive configuration where certain vehicular movements, such as right-turns and crossings from the primary road or secondary crossroads, are achieved...

Stochastic multi-objective optimization for dynamic timetable and track allocation at high-speed railway hubs

Train scheduling and track allocation are crucial for minimizing passenger flow conflicts, ensuring safety, and enhancing travel experience at railway hubs. This study presents a collaborative optimization...

Adaptive federated learning framework for predicting EV charging stations occupancy

Forecasting the occupancy of electric vehicle (EV) charging stations is crucial for addressing key challenges in e-mobility, including charging inefficiency, traffic congestion, and drivers’ difficulty...

Selecting and optimizing distress feature descriptors from multi-source images for pavement distress classification

Accurate and efficient early detection of pavement distress is crucial, as it prevents further deterioration, reduces repair costs, and enhances driving safety by mitigating hazards like potholes and...

Enhancing the abrasion resistance of cement concrete pavement through in-situ precipitation of hydroxyapatite

•A bio-inspired method using diammonium phosphate (DAP) solution induces in-situ precipitation of hydroxyapatite (HAP) on Portland cement concrete (PCC) pavements, significantly improving abrasion resistance.•The...

A simulation approach for analyzing metro resilience under operational incidents

Operational incidents represent the most prevalent anomalies encountered within metro systems. This study develops a simulation-based approach for comprehensively understanding the impact of such incidents...

Passenger-flow-based decisions on cross-line and independent operations in suburban rail transit

Deciding whether to implement cross-line operation or maintain independent operation between two suburban railway lines with compatible systems requires quantitative decision-making support. This study...

Blockchain-enabled collaborative governance in dangerous goods road transportation: an evolutionary game approach

Implementing collaborative governance in the road transportation of dangerous goods encounters severe challenges due to the lack of trust among stakeholders. This study proposes a collaborative governance...

High-thermal-conductivity steel slag asphalt pavements for road cooling

High surface temperatures in asphalt pavements, primarily caused by solar radiation absorption, accelerate material degradation and increase urban heat load. Incorporating steel slag (SS), a high-thermal-conductivity...

Predicting network-wide metro passenger flow under large-scale disruptions in a mega-scale city

Accurately predicting passenger flow distribution within a metro network during large-scale disruptions is crucial for maintaining the resilience of metro systems in megacities. Such disruptions not...

Uni-Light: A unified deep reinforcement learning framework for cooperative traffic signal and connected and automated vehicles control

In recent years, deep reinforcement learning (DRL) has been widely applied to urban traffic signal control in mixed traffic environments where human-driven vehicles (HDVs) and connected and automated...

Individual weekly activity sequence generation framework based on activity pattern dynamics

Individual weekly activity patterns are essential for enhancing activity-based mobility models, yet existing methods mainly focus on single-day behaviors, while overlooking temporal dependencies across...

Repeated traffic violations: modelling and analysis of the decay effect of traffic safety education

Traffic safety education has proved to be an effective means to reduce the number of traffic violations; however, few studies have attempted to quantify how its safety effect sustains over time, that...

Multi-view spatio-temporal graph convolutional network with domain adversarial learning for traffic prediction

Deep learning methods have been widely applied in urban traffic flow prediction and have achieved promising results. However, these methods rely on large amounts of training data. In reality, due to...

Navigating the daily grind: a latent class analysis of bus commuter stress

•Latent class analysis reveals diverse bus commuter stress in Hong Kong.•Younger individuals are more susceptible to transport-related stressors.•Socio-demographic factors and life-domain stressors...

Traffic anomaly detection by fusing spatiotemporal graphs and visual perception

Traffic anomaly detection (TAD) is essential for highway operational safety but remains challenging due to limitations of single-modality visual methods or costly sensor reliance. Current systems exhibit...

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