Automotive and intelligent transportation systems

The traffic and transportation research of DCSC focusses on the control of large-scale transportation system with a main emphasis on freeway and road traffic networks. In addition, we also consider control of railway networks. The primary control strategy is model predictive control. Furthermore, we also consider distributed control of large-scale traffic networks using a distributed and/or hierarchical multi-agent control approach.

Projects

• ABS for Regenerative Braking in Electric Vehicles
• Ant Colony Optimization for Dynamic Traffic Routing
• Data-driven Methodologies for Battery Managment and Control
• Development of advanced multi-agent control strategies for multi-class traffic networks
• Global Chassis Control using Load Sensing
• Global Chassis Control using Load Sensing
• Hierarchical model predictive control for transportation systems
• Integrated control of road networks with model predictive control
• Intelligent control methods for flood and water management
• Intelligent Lane Selection Assistance System (ILSAS)
• Model-based predictive control for intelligent micro-transportation systems
• Model-Based Traffic Control for the Reduction of Emissions and Fuel Consumption
• Multi-agent control of large-scale hybrid systems
• Optimal and model predictive control of railway systems
• Passivity-Based Global Chassis Control
• Reconfigurable Fault-Tolerant Predictive Flight Control
• Reconfigurable handling and flying qualities for degrade flight systems using model predictive control
• Self-organizing moving agents for distributed sensing and control
• Traffic control for large-scale urban traffic networks via MPC

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