Intelligent Real-Time Modelling of Rider Personal Attributes for Safe Last-Mile Delivery to Provide Mobility as a Service

Social Sciences

• Infrastructure 100%
• Mobility 80%
• Learning 60%
• Age 60%
• Service Industries 60%
• Age Groups 60%
• Planning 40%
• Time 40%
• Consumers 40%
• Transport 40%
• Bicycles 40%
• Understanding 20%
• UK 20%
• Work 20%
• Region 20%
• Research 20%
• Design 20%
• Buildings 20%
• Literature 20%
• Feature 20%
• Machines 20%
• Practice 20%
• Statistics 20%
• Influence 20%
• Case Studies 20%
• Diversity 20%
• Comparison 20%
• Scenarios 20%
• Knowledge 20%
• Forecasting 20%
• Parameter 20%
• Traffic 20%
• Flow 20%
• Intention 20%
• Model Learning 20%
• Transport Safety 20%
• Road User 20%
• Externality 20%
• City Planning 20%
• Standard Deviation 20%

Computer Science

• Simulation Mode 80%
• User 60%
• Service 60%
• Learning Systems 40%
• Case Study 20%
• Networks 20%
• Standards 20%
• Learning Framework 20%
• Intents 20%
• Statistics 20%
• Machine Learning Technique 20%
• Design Phase 20%
• Hybrid Approach 20%
• Prediction Accuracy 20%
• Personal Attribute 20%
• Deep Learning Model 20%
• Transport Mode 20%
• Flow Condition 20%