Incident management - a tunnel perspective

The consequential effects of vehicle congestion and deviant vehicle behaviour within the close confines of tunnels, has been a major concern for traffic authorities since tunnels were first promoted as a traffic engineering solution. Having entered the tunnel confines, there is little chance of alternate routing and hence the ability of a vehicle monitoring system to accurately and expediently detect traffic variations, is essential to effective traffic management and the safety of motorists using the tunnel. The performance level expectation is set according to the degree of risk associated with the application. While the desired outcome of performance based on minimising false alarms and maximising incident detection in the shortest possible time applies to a freeway, tunnel based incident management requires additional verification of vehicle behaviour. The difficulties with performance expectation arise when the system has to provide the same level of incident detection performance when the number of vehicles may vary from 5 vehicles an hour to 2500 vehicles per lane regularly within a twenty-four hour period. Volume-occupancy incident management models while satisfactory at high vehicle flow rates, perform less than satisfactorily at very low volumes. A freeway model may not be concerned with low volumes, that is, low volumes will never produce congestion; however, within a tunnel, more critical incidents associated with deviant vehicle behaviour emerge at low volumes. It is imperative, under any vehicle flow conditions in a tunnel, that a vehicle travelling contra flow, a stopped vehicle causing congestion or queued traffic beyond the visibility range and a vehicle travelling either considerably faster or slower than the preset tunnel speed cause a predetermined hazard warning response immediately.


  • English

Media Info

  • Pagination: 13p

Subject/Index Terms

Filing Info

  • Accession Number: 01394168
  • Record Type: Publication
  • Source Agency: ARRB
  • ISBN: 1876942037
  • Files: ATRI
  • Created Date: Aug 23 2012 10:04AM