Presentation For Incorporation of Pricing in the Time-of-Day Model “Express Travel Choices Study” for the Southern California Association of Governments.

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Presentation transcript:

Presentation For Incorporation of Pricing in the Time-of-Day Model “Express Travel Choices Study” for the Southern California Association of Governments (SCAG) 13 th TRB National Transportation Planning Application Conference Reno, Nevada May 8-12, 2011 For Kazem Oryani, WSA Cissy Kulakowski, WSA Liren Zhou, WSA Lihe Wang, WSA Tom Adler, RSG Mark Fowler, RSG

Outline of Presentation Objective Model Steps Data Analysis a) Year 2001 Household Survey b) Year 2003 SCAG Model c) Year 2010 Stated Preference Survey Time-of-Day Model Model Replication Scenario Analysis Prototype Test Results Future Steps 2

To update and enhance the existing trip-based SCAG regional travel demand model to allow it to be used for the analysis of different pricing alternatives. Objective: 3

Model Steps: Enhancements by WSA Enhancements by PB 4

Ventura Co. San Bernardino Co. Riverside Co. Orange Co. Note: All trips shown in thousands Source: SCAG 2003 Model Validation and Summary, January, Pacific Ocean Los Angeles Co. Intracounty Travel Intercounty Travel LEGEND 92 5, , Year 2003 Home-based County to County Work Trip Flows 5 Imperial Co. Riverside Co.

Los Angeles Co Ventura Co. San Bernardino Co. Orange Co. Los Angeles Co. Pacific Ocean Riverside Co. 6,345 1,063 2,094 1, Note: All trips shown in thousands Source: SCAG 2003 Model Validation and Summary, January, Intracounty Travel Intercounty Travel LEGEND Year 2020 Home-based County to County Work Trip Flows 6 Imperial Co. Riverside Co.

Data Analysis: Year 2001 SCAG Household Travel Survey  Person trip: 84,000  Activity episodes: 190,000  Distribution of survey trips by trip purpose  Home-based trips - Direct work trips: 15 percent - “Other” home-based trips: 12 percent Work-based Other Trips: 10 percent Non-Home-based Trips: 30 percent 7

Data Analysis: Distribution of Survey Trips by Trip Purpose 8

Data Analysis: Departure Time Distribution by Purpose Home-based Auto From-Home Trips Time of Day Percentage of Daily Trips Home-based other (Sample: 4,980) Home-based school (Sample: 1,465) Home-based shopping (Sample: 2,868) Home-based serve passenger (Sample: 3,483) Home-based social/recreational (Sample: 2,668) Home-based university (Sample: 443) Home-based work (direct) Sample: 7,368) Home-based work ( strategic (includes a stop)) (Sample: 1,679) 9 Home-based school Home-based work (strategic) Home-based work (direct)

Data Analysis: Departure Time Distribution by Purpose Home-based Auto To-Home Trips Time of Day Percentage of Daily Trips Home-based other (Sample: 4,312) Home-based school (Sample: 1,084) Home-based shopping (Sample: 3,555) Home-based serve passenger (Sample: 2,973) Home-based social/recreational (Sample: 3,043) Home-based university (Sample: 387) Home-based work (direct) Sample: 6,437) Home-based work (strategic (includes a stop)) (Sample: 2,546) 10 Home-based school Home-based work (strategic) Home-based work (direct)

Data Analysis: Travel Time (minute) Distribution by Purpose Home-based Auto From-Home Trips Home-based other Home-based school Home-based shopping Home-based serve passenger Home-based social/recreational Home-based university Home-based work (direct) Home-based work ( strategic (includes a stop)) Time of Day Percentage of Daily Trips 11 Home-based school Home-based work (strategic) Home-based work (direct)

Data Analysis: Year 2003 SCAG Model: Congested and free-flow travel times Distance Zonal population density Zonal employment density 12

Year 2010 Stated Preference Survey: Stated Preference Survey to Support Model Changes  3,600 survey record for all six SCAG counties  Discrete choice model by trip purpose: work, business trips, non-work  Time-of-day: peak, off-peak $2.00$3.00$4.00$3.00$

Year 2010 Stated Preference Survey: Hypothetical Reaction to Pricing For Range of Fees 14

Year 2010 Stated Preference Survey: Change in Tripmaking (Trip Suppression / Inducement) (Negative = Suppression, Positive = Inducement) Peak Non-work Trip 15

Year 2010 Stated Preference Survey: Ability to Shift Time of Travel - Current Peak Period Travelers 16

Year 2010 Stated Preference Survey: Travel Time Shift Model - Work Commute Trips 17

Time-of-Day Model: Time-of-Day Model Variables Origin zone characteristics (such as CBD, density, other) Destination zone characteristics (such as CBD, density, other) Trip purpose Mode Traveler’s household size Traveler’s household income Number of household workers Number of household vehicles Traveler’s age Traveler’s employment industry type Each time-of-day choice model includes a combination of the following variables: 18

Time-of-Day Model: 1. Home-based work direct trips (HBWD) from home 2. Home-based work direct trips (HBWD) to home 3. Home-based work strategic trips (HBWS) from home 4. Home-based work strategic trips (HBWS) to home 5. Home-based shopping trips (HBSH) from home 6. Home-based shopping trips (HBSH) to home 7. Home-based other (including social and recreational) trips (HBSR) from home 8. Home-based other (including social and recreational) trips (HBSR) to home 9. Other-based other (OBO) trips Model Estimated 19

Time-of-Day Model: HBWD From-Home Trip Time-of-Day Choice Model Summary 20

21 Model Replication: Time-of-Day by 31 Time Slices Home-based Work Direct Trips (HBWD) From Home

Model Replication: Time-of-Day Home-based Work Direct Trips (HBWD) From Home 22

23 Model Replication: Time-of-Day by 31 Time Slices Home-based Work Direct Trips (HBWD) To Home

Model Replication: Time-of-Day Home-based Work Direct Trips (HBWD) To Home 24

Model Replication: Time-of-Day Scenario Analysis Flow Chart D/MC:Destination/Mode Choice TOD MNL:Multi-Nominal Logit Time-of-Day Model Base Run with No Pricing Price/User Fee MNL:Multi-Nominal Logit Time Shift Model including Pricing Priced TOD:Time-of-Day Matrices With Pricing Impacts Base TOD:Base Time-of-Day Matrices Without Pricing Impacts ShiftShifted Trips Due to Pricing Shift Adj.:Adjusted Amount of Shifted Trips Adj. Price TOD:Adjusted Time-of-Day Matrices Before Trip Suppression Positive Adj. Shift:Shifted Trips not Subjected to Trip Suppression TS (0.1):Trip Suppression (Factor to be determined for each Origin-Destination Pair based on Trip Suppression Model) 25

HOT Lane Projects 26

27 Improvement of Volume / Count Match (RMSE Statistics)  AM Peak - 2.2%  Midday - Similar  PM Peak - 4.3%  Night - 4.8% Prototype Test Results - Comparison of Diurnal and TOD Method

Count Locations 28

29 Comparison of Diurnal and TOD Method Assignment Summary Statistics Using Diurnal Method Assignment Summary Statistics Using Time-of-Day Method

30 Regional Screenline Locations

Prototype Tests Priced Cases VMT Charge $0.05 Per Mile, 3 Hour AM, 4 Hour PM Peak Periods Trip Table Effects Reduction of 6.0 Percent in AM Peak Trip Reduction of 5.8 Percent in PM Peak Trip Increase of 5.0 Percent in Midday Trips Increase of 7.3 Percent in Night Trips 31 VMT Charges vs. No Toll Pricing Assumptions - $0.05 Per Mile for AM and PM Peak Periods (Trip Table)

VMT Charge $0.05 Per Mile, 3 Hour AM, 4 Hour PM Peak Periods Screenline Effects Reduction of 6.2 Percent in AM Peak Trip Reduction of 8.0 Percent in PM Peak Trip Increase of 8.2 Percent in Midday Trips Increase of 6.8 Percent in Night Trips 32 Prototype Tests Priced Cases (cont’d) VMT Charges vs. No Toll Pricing Assumptions - $0.05 Per Mile for AM and PM Peak Periods (Screenline Comparison)

Regional Freeway Pricing Cordon Pricing Parking Pricing 33 Prototype Tests Priced Cases (cont’d)

1.Use of TOD Improves Model Calibration / Validation Status 2.The Higher / Vaster Application of Pricing, the Higher Impacts in AM and PM Peak Trip Reduction 3.Targeted Cordon and Parking Pricing in Hypothetical Downtown LA Pricing: Affected Trips About 2.0 Percent Trip Reduction for AM and PM Peak From -1.0 to -0.3 Percent 34 Summary of Prototype Tests Future Steps: Tests and Scenario Analysis With Integrated Model

Acknowledgement: Contributions of Annie Nam, Guoxiong Huang, Wesley Hong and Warren Whiteaker of Southern California Association of Governments, Linda Bohlinger of HNTB Corporation, Edward Regan of Wilbur Smith Associates, Thomas Adler, Mark Fowler of RSG are greatly appreciated. Contact: Kazem Oryani Phone: