000133643 001__ 133643
000133643 005__ 20190316234458.0
000133643 037__ $$aPOST_TALK
000133643 245__ $$aTravel time prediction on urban network by integrating stop-line detector data, signal controller data and probe information
000133643 269__ $$a2009
000133643 260__ $$c2009
000133643 336__ $$aTalks
000133643 520__ $$aIn urban network, detectors are generally used for signal control. If the data from detectors are also used for travel time estimation and fed back to the traffic management and information systems then it will be a significant contribution for managing urban network. For instance: the model can be applied for performance evaluation of the system and Level of Service of different intersections. It can also be applied for ITS applications such as, Advanced Traveler Information Systems and Public Transport Priority System. This paper presents the methodology for real-time travel time estimation on signalized urban network which is based on the classical principle of cumulative plots at the entrance and exit of the link. In urban environment there are potential sources of deviations in the cumulative plots, for instance: a) mid-link sources and sinks (e.g. parking) b) detector counting error c) unknown proportion of counts for the study link from detector on shared-use lane at the upstream intersection, etc. The deviations in cumulative plots are accumulative and if such issues are ignored then deviations can grow exponentially with time. In the proposed model, cumulative plots are accurately estimated through analytical modeling and above mentioned issues are addressed by developing the following techniques for different traffic flow conditions. Detector data and signal controller data is integrated with the following constraints at the stop-line detector location: a) Detector counts aggregated over signal cycle period are less than the lane capacity for under-saturated condition; and are close to lane capacity for saturated and oversaturated conditions; b) Cumulative arrival at the end of each signal green interval is equal to cumulative departure for under-saturated condition; and is more than cumulative departure for over-saturated condition. For saturated or over-saturated conditions, accuracy is enhanced by data fusion with probe vehicle. Probe vehicle provides time when the vehicle is at upstream and downstream intersections. This information is used as a reference for adjusting cumulative plots generated by the integration of detector data with signal controller data. The result from model testing under control environment for scenarios with 10% demand for midlink source indicates that, the 5th percentile of the accuracy for travel time estimation is generally more than 95% for under-saturated condition with no probe; and for saturated or over-saturated conditions with 3% probe. This model has overcome the issues related to models solely based on cumulative plots or probe vehicles with significant improvement in accuracy and has the potential for real-time travel time estimation on urban network. The model is to be validated with the real data obtained from a study site with 12 consecutive intersections along 1.5 km area at Lucerne city. Signal controller and detector data is obtained from VS-PLUS controllers installed in the area. Actual travel time is obtained from manual number plate survey. The final paper will contain the results of the validation.
000133643 6531_ $$aUrban network
000133643 6531_ $$aTravel time estimation
000133643 700__ $$0240569$$aBhaskar, A.$$g168612
000133643 700__ $$aChung, E.
000133643 700__ $$0241970$$aDumont, A.-G.$$g105012
000133643 7112_ $$a8th STRC Swiss Transport Research Conference$$cMonte Verità, Ascona, Switzerland$$dOctober 15-17, 2008
000133643 8564_ $$uhttp://www.strc.ch$$zURL
000133643 909C0 $$0252146$$pLAVOC$$xU10259
000133643 909CO $$ooai:infoscience.tind.io:133643$$ppresentation$$pENAC$$qGLOBAL_SET
000133643 937__ $$aLAVOC-PRESENTATION-2009-001
000133643 973__ $$aEPFL$$sPUBLISHED
000133643 980__ $$aTALK