TPAC | Columbus, OH | May 2013 Transit Beyond Travel Time and Cost Incorporation of Premium Transit Service Attributes in the Chicago Activity-Based Model

Project Team 2  Chicago Metropolitan Agency for Planning (CMAP)  Kermit Wies & Matt Stratton  Parsons Brinckerhoff (PB)  Peter Vovsha, Joel Freedman, Ben Stabler, Binny Paul, Roshan Kumar  Resource Systems Group (RSG)  Maren Outwater, Bill Woodford, & Jeff Frkonja

Sources of Inspiration 3  TCRP H-37  SANDAG, MAG, SACOG  Chicago New Starts Model  Portland Metro  LACMTA/FTA

Model Improvements 4 Model ComponentPhase 1Phase 2 Advanced “non-labeled” mode choiceXX Transit access / spatial resolutionX Station characteristicsXX In-vehicle characteristicsXX Capacity constraintsX Crowding effectsX Service reliabilityX Transit frequency / wait timeXX Fare / cost structuresXX Individualized transit path choiceX Mobility attributes and modalityX

Non-Labeled Mode Approach 5  Refer to actual service characteristics and understand traveler perceptions  Limit mode & geography-specific constants

Mode Choice Alternatives 6 Previous (Labeled) >>Phase 1 (Interim) >>Phase 2 (Final) Walk to busWalk to conventional transit Walk to transit Walk to railWalk to premium transit Drive to railPNR Drive to busKNR

Spatial Resolution 7  17K MAZs nested in 2K TAZs  All transit trip ends at MAZ geography  Transit Access Points (TAPs)  Virtual path building  Access/egress time (Python) 12 threads  Station-to-station time (EMME)  Access/egress + Station-to-station time (Java)

Transit Virtual Path Building 8 CharacteristicOrigin TAPTAP-to-TAPDest. TAP Station typeXXX Real-time informationXXX Formal parking capacityXX Informal parking capacityXX Parking costXX Parking lot walk timeXX KNR convenience categoryXX Buffered area crime rateXX Buffered retail densityXX First boarding fareX Boarding (traversal) timeX Ease of boardingX Station cleanlinessX

Transit Stop Types Pole 2. Bus Shelter 3. Bus Plaza 4. Rail Station 5. Major Terminal

Transit Stop Parameters 11  Additional variables considered  Proximity to commercial services  Stop/station environment (wait convenience)  Ease of paying (fare policy & media)  Ease of boarding (in combination with vehicle type)  Cleanliness  Security

Transit Stop Wait Time 12 Schedule headway Wait time fraction Effective multiplier Extra unreliability wait Physical time Perceptional multiplier × × × Station-specific wait convenience Station cleanliness

Extra Average Wait Time 13 Scheduled headway × Time-of-day impact Inverse impact of headway Crowding impact Cumulative route distance effect

In-Vehicle Parameters 14  Additional variables considered  Seating comfort  Unreliability  Crowding  Productivity (work, sleep, socialize)  Cleanliness  On-board amenities  Socio-economic compatibility between riders

In-Vehicle Time 15 Physical time Base perceptional multiplier Additional perceptional multiplier Average time × Unreliability Comfort Convenience Temperature Amenities × 1 Crowd. for seat. Prob. seat × Crowd. for stand. Prob. stand × Productivity Prob. seat × Social environment On-board cleanliness

In-Vehicle Crowding 16 Volume Total Capacity Seated Capacity Max. Convenience Crowd. factor Standing Seating

In-Vehicle Social Environment 17 IVT multiplier component for Class X = × Proportion of Class 1 Proportion of Class 2 Proportion of Class 3 Perception of Class 1 by X Perception of Class 2 by X Perception of Class 3 by X × × Modeled passenger Perception of other passengers as additional IVT weight Class 1Class 2Class 3 Class Class Class

In-Vehicle Productivity 18 Mode-vehicle typeFixed IVT productivity bonus User class 1User class 2User class 3 Local Bus0.00 Express Bus Metro0.00 Commuter Rail

Conclusions 19  ABM is a better platform for testing a variety of transit attributes  ABM required little modification  Lots of data development  Final Tasks  Finalize measurable transit service attributes  Estimate individual path choice preferences  Incorporate in operational ABM & transit network procedures

20 Questions? Matt Stratton, Peter Vovsha, Ben Stabler, Maren Outwater,