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Travel demand model updates for the Parkersburg/Marietta metro area :. 2 counties, 2 states, 90,000 UZA, 150,000 MSA NCHRP 365 structure for trip generation, modifications to better match field study totals Inverse power functions for trip distribution by purpose, trial and error to match VMT
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Travel demand model updates for the Parkersburg/Marietta metro area : • 2 counties, 2 states, 90,000 UZA, 150,000 MSA • NCHRP 365 structure for trip generation, modifications to better match field study totals • Inverse power functions for trip distribution by purpose, trial and error to match VMT • Transit ridership (1000 rides/day regionwide) far less than sampling error in counts, not modeled • MSA assignment w/feedback to distribution after every iteration, few iterations needed due to undersaturated conditions
New or updated model features: • Peak hour (w/PHFs) and truck (multi-class) assignments • Zones placed in 7 different hour of day trip patterns by purpose & direction (school bell times, Census journey to work) • ODME used for trucks and “hard to locate” employment • Validation includes travel times vs WWW field surveys on 7 urban arterials • Design Hour modeling changes
Elements of truck modeling: • SU & Combination trucks begin with QRFM trip generation rates and distribution to match VMT estimate, then trip tables adjusted re ODME. • Separate truck speeds on network indirectly applied via time penalties based on observed speed differences (waived for state highways and local truck routes shown below to reflect geometric and legal restrictions). • Slower accel/decel rates at intersections (old Green book charts)
Travel time validation • Focus on 7 urban arterials (AM and PM peak by direction), where travel time is the measure of LOS • 75% of time model error less than field study’s actual CV (half within 95% C.I.) • Few other agencies to provide comparables, results far superior to volume/delay curves
My traditional system of “independent” static model runs (Deterministic MSA w/elastic demand) (Spring weekday now used for AADT)
Design hour factors changed • The design hour and the PHF are modeled directly, not a post-process • Design hour now based on “typical Friday” from review of Ohio ATR data, which has 15-20% higher volumes than the average weekday • Slightly higher work & school absenteeism rates on Friday compensated for with 20-25% higher non-work trips (from field studies) and higher % for external stations (from count data)
Peak hour factor (PHF) • Factoring of trip generation (via HOD rates by purpose), used for LOS • Study “guidance” of 0.90 (ODOT), .88-.92 (HCM) or exp (f)volume (Synchro) • Direct assignment allows PHF on all links to be a function of land use served and *relative* degree of congestion • On urban streets (FFC 14-19), average value of .901 and r-square with peak hour counts=0.07 (Special count program in Dayton found average of .897 and r^2 of 0.11)
Plan update issues: • Reconciling population decline with growth in employment and thru traffic • Change in model focus reveals shift in forecasted future problem areas • Half of VMT growth absorbed by 2 freeways (I-77 and new US50 corridor), urban street VMT, average speeds, and % with poor LOS change little • Travel speed changes had minor impact on air quality – within safety margin
Other Plan issues: • Financial crunch for new projects, more TSM needed • “Innovative” project alternatives
Model work still to be done: • Dynamic assignment • Network and zone updates, tied to digital e911 networks (WV SAMB, OhSIP, LBRS)