Qiming Ye
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View article: Risk-Aware Stochastic Vehicle Trajectory Prediction With Spatial-Temporal Interaction Modeling
Risk-Aware Stochastic Vehicle Trajectory Prediction With Spatial-Temporal Interaction Modeling Open
Autonomous vehicles need to continuously analyse the driving context and establish a comprehensive understanding of the dynamic traffic environment. To ensure the safety and efficiency of their operations, it would be beneficial to have ac…
View article: Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach
Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach Open
Mobile parcel lockers (MPLs) have been recently proposed by logistics operators as a technology that could help reduce traffic congestion and operational costs in urban freight distribution. Given their ability to relocate throughout their…
View article: Demand forecasting of online car‐hailing by exhaustively capturing the temporal dependency with TCN and Attention approaches
Demand forecasting of online car‐hailing by exhaustively capturing the temporal dependency with TCN and Attention approaches Open
With the development of the car‐hailing industry, it has become an indispensable way of travel in our lives. Accurate prediction of online car‐hailing demand can provide the basis for real‐time vehicle dispatch and dynamic pricing for onli…
View article: Route Planning for Last-Mile Deliveries Using Mobile Parcel Lockers: A Hybrid Q-Learning Network Approach
Route Planning for Last-Mile Deliveries Using Mobile Parcel Lockers: A Hybrid Q-Learning Network Approach Open
Mobile parcel lockers have been recently proposed by logistics operators as a technology that could help reduce traffic congestion and operational costs in urban freight distribution. Given their ability to relocate throughout their area o…
View article: Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions Using Reinforcement Learning
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions Using Reinforcement Learning Open
The deployment of Autonomous Vehicles (AVs) poses considerable challenges and unique opportunities for the design and management of future urban road infrastructure. In light of this disruptive transformation, the Right-Of-Way (ROW) compos…
View article: Spatial-Temporal Flows-Adaptive Street Layout Control Using Reinforcement Learning
Spatial-Temporal Flows-Adaptive Street Layout Control Using Reinforcement Learning Open
Complete streets scheme makes seminal contributions to securing the basic public right-of-way (ROW), improving road safety, and maintaining high traffic efficiency for all modes of commute. However, such a popular street design paradigm al…
View article: A Reinforcement Learning-based Adaptive Control Model for Future Street Planning, An Algorithm and A Case Study
A Reinforcement Learning-based Adaptive Control Model for Future Street Planning, An Algorithm and A Case Study Open
With the emerging technologies in Intelligent Transportation System (ITS), the adaptive operation of road space is likely to be realised within decades. An intelligent street can learn and improve its decision-making on the right-of-way (R…
View article: A Reinforcement Learning-based Adaptive Control Model for Future Street\n Planning, An Algorithm and A Case Study
A Reinforcement Learning-based Adaptive Control Model for Future Street\n Planning, An Algorithm and A Case Study Open
With the emerging technologies in Intelligent Transportation System (ITS),\nthe adaptive operation of road space is likely to be realised within decades.\nAn intelligent street can learn and improve its decision-making on the\nright-of-way…
View article: Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm
Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm Open
Mobile parcel lockers (MPLs) have been recently introduced by urban logistics operators as a means to reduce traffic congestion and operational cost. Their capability to relocate their position during the day has the potential to improve c…
View article: Demand Forecasting of Online Car-Hailing with Combining LSTM + Attention Approaches
Demand Forecasting of Online Car-Hailing with Combining LSTM + Attention Approaches Open
The accurate prediction of online car-hailing demand plays an increasingly important role in real-time scheduling and dynamic pricing. Most studies have found that the demand of online car-hailing is highly correlated with both temporal an…
View article: Load Prediction and Control of Capillary Ceiling Radiation Cooling Panel Air Conditioning System Based on BP Neural Network
Load Prediction and Control of Capillary Ceiling Radiation Cooling Panel Air Conditioning System Based on BP Neural Network Open
Compared with traditional air conditioning system, capillary ceiling radiation cooling panel (CCRCP) air conditioning system has the characteristics of low energy consumption, low noise and can provide comfortable indoor thermal environmen…
View article: A Reinforcement Learning-based Adaptive Control Model for Future Street Planning An Algorithm and A Case Study
A Reinforcement Learning-based Adaptive Control Model for Future Street Planning An Algorithm and A Case Study Open
With the emerging technologies in Intelligent Transportation System (ITS), the adaptive operation of road space is likely to be realised within decades. An intelligent street can learn and improve its decision-making on the right-of-way (R…
View article: On the Selection of Charging Facility Locations for EV-Based Ride-Hailing Services: A Computational Case Study
On the Selection of Charging Facility Locations for EV-Based Ride-Hailing Services: A Computational Case Study Open
The uptake of Electric Vehicles (EVs) is rapidly changing the landscape of urban mobility services. Transportation Network Companies (TNCs) have been following this trend by increasing the number of EVs in their fleets. Recently, major TNC…
View article: Application of BP Neural Network for Pre-Dehumidification Time Prediction of Capillary Ceiling Radiant Cooling Panel Air Conditioning System
Application of BP Neural Network for Pre-Dehumidification Time Prediction of Capillary Ceiling Radiant Cooling Panel Air Conditioning System Open
Pre-dehumidifying the room is generally needed before the capillary ceiling radiant cooling panel (CCRCP) air condition system is turned on. Accurate pre- dehumidification time is critical for condensation prevention and energy usage. The …
View article: Demand Forecasting of Online Car-Hailing With Stacking Ensemble Learning Approach and Large-Scale Datasets
Demand Forecasting of Online Car-Hailing With Stacking Ensemble Learning Approach and Large-Scale Datasets Open
With the rapid development and convenient service of online car-hailing, it has gradually become the preferred choice for people to travel. Accurate forecasting of car-hailing trip demand not only enables the drivers and companies to dispa…
View article: Short-Term Prediction of Available Parking Space Based on Machine Learning Approaches
Short-Term Prediction of Available Parking Space Based on Machine Learning Approaches Open
Reliable short-term prediction of available parking space (APS) is the basic theory of parking guidance information system (PGIS). Based on the Intelligent parking system at the Eastern New Town, Yinzhou District, Ningbo, China, this study…