The project develops a procedure for the determination of traffic jam ends and the warning of road users. Road users should be warned for half a minute and at a distance of up to 1 km before reaching the end of the traffic jam in order to avoid rear-end collisions. The focus is on temporarily jam-prone sections on multi-lane highways, especially on construction sites. A process model is developed that covers all steps from data collection to issuing a warning. The ends of traffic jams are to be determined as well as their positions are to be predicted with the help of propagation models for jamming ends. Data sources include temporarily installed sensors, in particular Bluetooth and radar sensors, floating car data and existing cameras. For the output of the warnings, the integration in third-party applications (apps) is specified. To test the processes, it is planned to use data collected in the course of a test field at the construction site Enztalquerung on the A8 near Pforzheim.
Bluetooth and radar sensors and Floating Car Data (FCD) provide different traffic parameters such as speeds, volume, travel times. Each of these traffic data sources has its inherent strengths and weaknesses and may not accurately represent the actual state of traffic necessary for modelling and predicting traffic conditions. In this project, the data sources are used to complement each other through data fusion to provide accurate data for traffic congestion detection and end of congestion tracking.
The first part of the project involves real-time data acquisition from radar and Bluetooth sensors placed on the highway and FCD data from INRIX, HERE and TOMTOM. Spot speeds, traffic volume and road occupancy from radar sensors will then be fused with travel times and mean speeds from FCD and Bluetooth datasets. The result of this fusion process will be traffic flow rates and vehicle density characterizing the traffic conditions. The fused results will be the foundation of the end of traffic congestion detection and tracking stage.
The processed information will be uploaded to a portal regularly to create highly reliable end of traffic congestion alarms with high spatial-temporal accuracy. The alarms will be relayed to traffic users via roadside Variable Message Signs (VMS) and to app developers through an API.
|Management||Prof. Dr.-Ing. Michael Hahn|
|Team||Joseph Gitahi, Martin Storz|
|Partner||ITS-United GmbH, AVT Consult GmbH|
|Sponsor||Ministry of Transport Baden-Württemberg|
|Call for tender||MobiArch funding line|