Road transportation

Our research topics on Road Transportation:

More details are here:


Closed-loop traffic simulation environment


  • Design of intelligent, adaptive traffic control algorithms.
  • “HW in the loop” framework for design :
    • SW: Vissim, Visum, Matlab, C++, Java, Vissim COM/API, QGIS, Siemens Scala traffic control client 
    • HW: Siemens signal heads, PLCs, Swarco traffic controllers, Futurit LED variable message signs
  • The closed-loop environment permits efficient testing and validation of the designed traffic control system.

Freeway traffic modeling and control

  • Macroscopic freeway traffic modeling using the analogue of gas-kinetic models.
  • Model based control to avoid traffic congestion and reduce emissions.
  • Effective traffic control measures:
    • dynamic speed control: by reducing the admissible speed, traffic flow capacity and stability can be improved.
    • ramp metering: traffic flow can be influenced through the control of entering vehicles on the ramp.

Emissions modeling and control


  • Common pollutants of road traffic (COx, HC, NOX) can be modeled using traffic measurements.
  • A complex traffic-emission model was elaborated based on the macroscopic description of traffic flow.
  • Modeling of air pollutant concentrations in residential areas.
  • Control design for the stabilization of shock waves and emission reduction on freeways.
  • The figures depicts an example of CO pollutant concentrations with and without control measures.

Automatic incident detection on freeways


  • The term "Incident on freeways" means any disturbance which influences the free flow of the traffic.
  • Incident detection process:
    • definition of discrete road sections within the observed area,
    • check certain parameters of the traffic flow (usually in every 30 seconds),
    • compare them to fixed threshold values.
  • Threshold values are calibrated and then applied in a traffic dependent way.

The Reversible Lane Systems (RLS)



  • The Reversible Lane Systems can be used:
    • Against congestions (Construction Zone Traffic / Emergency Traffic Management )
    • Temporary divertion of traffic (Event Traffic / Peak-Period Traffic Management )
  • Mathematical modelling and analysis of the Reversible Lane Systems, definition of switching functions. 
  • Comparison of data obtained from the model with the vehicle dynamic parameters, and the validation of the model.

Optimal and robust urban traffic control


  • Novel approach for urban traffic control using Robust Model Predictive Control. 
  • Minimax optimization on rolling predicted horizon.
  • The main goal is to minimize the link queue lengths waiting at the stop light by considering demand uncertainty. 
  • The controller predicts the future states (queue lengths) and calculates the optimal green light time settings.

Perimeter control of protected urban network


  • Perimeter control: an alternative traffic control concept to protect city centers and dense urban areas against increasing demands posed during rush hour.
  • The goal is to ensure stable and uncongested traffic in the protected network.
  • Application of nonlinear Model Predictive Control based on the macroscopic fundamental diagram.
  • In this concept, the control measures are performed by the traffic signal controllers at the boundary of the network.

Traffic estimation based on mobile signaling events


  • Cellular phones can be used as tools to obtain information for traffic measurements, forecasting, and even traffic control. 
  • Handover (HO) and Location Area Updates (LAU) are automatically generated by cellular phones when contact between the cellular phones and location areas occurs.
  • By measuring cellular signaling events, an origin-destination matrix can be constructed for reliable traffic assignment. 
  • The aggregated HO/LAU events can be used for travel time estimation in order to further improve macroscopic urban traffic modeling.

Data fusion for urban traffic estimation

  • Appropriate data fusion of mixed sensors may contribute to more efficient transportation systems and services.
  • Alternative traffic measurement systems:
    • FCD (Floating Car Data): GPS based information from fleet vehicles.
    • FMD (Floating Mobile Data): traveling mobile terminals (server/client side) for travel times and origin-destination (OD) matrix estimations. 
    • Bluetooth based sensing: wireless devices in vehicles applying Bluetooth technology (e.g. mobile headsets  and car audio systems) for travel times and OD matrix estimation.
  • Data fusion technology by Switched Kalman Filter: urban traffic estimation and forecasting.

Smart signal heads

  • Logic (PLC) built into the signal head which controls the signal lamp bulbs and communicates with the traffic controllers.  
  • There is no need to directly connect all bulbs to the traffic controller. Only a single logical connection is required, except for the power supply to each signal head.
  • Advantages: less cable needed, simple system setup, economical.
  • The elements of the test system: Siemens PLC, Actros VTC 3000 traffic controller, Siemens LED signal heads.
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