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The Use of IPASS to Improve Mobility and Safety Through Traveler Information April 2004

The Use of IPASS to Improve Mobility and Safety Through Traveler Information April 2004. Background. The Illinois State Toll Highway Authority (ISTHA) has 274 Miles of Toll Highways 24 Mainline and 43 Entrance / Exit Ramp Plazas IPASS Automatic Toll Collection

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The Use of IPASS to Improve Mobility and Safety Through Traveler Information April 2004

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  1. The Use of IPASS to Improve Mobility and Safety Through Traveler InformationApril 2004

  2. Background • The Illinois State Toll Highway Authority (ISTHA) has 274 Miles of Toll Highways • 24 Mainline and 43 Entrance / Exit Ramp Plazas • IPASS Automatic Toll Collection • Over 2 million transactions per day 50% of which are IPASS

  3. Incident Management Fully Integrated 2 Way CAD CCTV DMS Incident Response Plans Travel Times Safety Messages Weather Data Queue Detection Center to Center Interface Open Architecture UNIX Servers / PC Workstations IPASS Travel Times Traffic & Incident Management System (TIMS)2004 Best of ITS Public Safety Award Winner

  4. Travel Times

  5. Point Travel Time Algorithms Detector Station (s) Provides Speed Data Extrapolation TT = L/S Interpolation TT = 2L/(S1+S2)

  6. IPASS Travel Time Data • When a vehicle arrives at a Plaza the following origin and destination data are transmitted to the TIMS • Date • Time • Plaza ID • Lane

  7. AF AE BE IPASS Basic TT Algorithm AB BF 182

  8. Data Flow

  9. Lessons Learned EF Revised Link Equations When two TDLS are used Vi = num Tag Reads TDLi Si = Speed TDLi Avg Speed = V1S1+V2S2/(V1+V2) TT = SegLen/(Avg Speed)

  10. Lessons Learned Standard Deviation Method All Data Near Minimum Method

  11. Algorithm Validation • Floating Car Runs Throughout the System during Peak and Off Peak Periods • Overall - Expected Results were Closely Correlated to Actual

  12. Validation Results • The calculated travel times for long sections of roadway are less accurate during times of unstable flow. • The availability of data for the segment travel times vary significantly. • The impact that variable delays at exit ramp plazas have on computations can be significant. • The sample size for computations and the number of actual tag reads affect the overall quality of the data.

  13. Travel Time Usages

  14. User Dialogs

  15. GCM Travel Web Page

  16. DMS

  17. PROS Uses Existing Infrastructure Actual data is very accurate Over one million daily tag reads CONS Existing Infrastructure Optimized for Toll Collections not Traffic Data Where plazas are widely separated (up to 30 miles) TT can lag significantly Only 25% pass the tests for validity Conclusions

  18. Future Efforts • Addition IPASS Readers are planned at the endpoints in conjunction with IDOT • 34 new DMS are being added • Additional IPASS Readers are being planed at more frequent intervals to further improve data resolution • AVL for maintenance, police, and money trucks may be added • Currently through a Federally Funded Program RTMS data is being added in the urban areas to improve data resolution and to add a new incident detection algorithm

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