Smarter Urban Mobility Systems Around the Pacific Rim Jerry
Walters Fehr & Peers
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Virtuous Cycles in City Planning and Operation Simulate Plan
Iterate / Implement Approve Evaluate Analyze Design Build Operate
Monitor + Manage
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How Scale Matters Urban Forms that Reduce Traffic, Energy and
Emissions
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Dimensions of Urban Form and Vehicle Use 1.Density 2.Diversity
3.Design 4.Destinations 5.Distance to Transit 6.Development Scale
7.Demographics 8.Demand Management
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National Evidence on MXD Travel Generation
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Network Data, Analytics and Simulation
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Kunming-Chenggong New Town
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2,800 acres 232,300 population 243,300 jobs Objectives Energy
efficiency Emissions and GHG reduction Economic and fiscal
performance Health and safety Kunming New Town / Sustainable
Objectives
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and Challenges Macro: Pace of development Planning and
performance mandates Car culture Lack of data and models
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Integrated Zoning, Circulation Systems
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Sesame Street Quiz
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Inter-Connected Network OptionConventional Network Plan Kunming
Urban Form / Network Form
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Network Simulation (Ignores benefits of 9% trip reduction and
traffic dispersion to parallel routes)
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Operational Comparison MeasureStandard ArterialCouplet
Pedestrian Crossing Distance 35.0 meters12.7 meters Min. Pedestrian
Crossing Time 37.3 seconds13.6 seconds Number of Signal Phases 4 to
82 to 5 # of LOS E/F Intersections 4 of 4 (100%)5 of 16 (31%)
California Legislated Mandates AB 32 Greenhouse gas reduction
targets, Cap + Trade SB 97 CEQA requirements for GHG assessment SB
375 - Linkages among: GHG targets regional transportation
sustainable communities strategies SB 732 Grant funding for
sustainable communities SB226 Approval streamlining for infill
development
Operationalizing Smarter Urban Mobility Systems Jerry Walters
Fehr & Peers
Slide 26
Goals for Smarter Mobility Systems Decisions ASAP and better
informed Better infrastructure design decisions Accurate impact
assessments of land development User-oriented transit service plans
and station designs Optimal sizing and integration of on-demand
systems Tailored mobility services to optimize TDM
effectiveness
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Lab Work Bus reliability by route segment GHG, fuel use at
traffic signals, roundabouts, stop signs Biases/inaccuracies in
self- reported journey times
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Field Work Transit ridership optimization Neighborhood parking
management enforcement Bike station analytics: opportunity
effectiveness assessment
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Leading-Edge Work Express-lane bottleneck removal through
GPS-calibrated simulation Regional traffic modeling through video
and cell O/D identification Simulation of campus operation,
expansion options
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Next Gen Studies for Smart Mobility
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Why and how people travel Longitudinal measurement Traveler
demographics, market segmentation O/D data vs built environment
(Ds) Models with complex AI objective functions Safety studies:
Road, signing and traffic conditions, driver attention
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Next Gen Studies for Smart Mobility Operational improvements
Traffic queues and delays, simulation models Cruising for parking
Traveler-weighted transit service level Un-served markets Service
availability, traveler characteristics of transit non-users
Demographics of bike-share users, demographics and journey
characteristics of non-users Comprehensive bicyclist route choice
factors, including safety and security
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Data Aggregation and Synthesis Needed
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A Dozen Data Desires 1.Higher fidelity traffic flow data
2.Complete traveler O/D movements by all modes 3.Operating flow,
interactions and incidents among modes 4.Longitudinal data:
before/after stimulus 5.Land use and employment inventories by
parcel 6.Over-the-net accessibility: time, cost, reliability,
uncertainty * calibrate/ validate
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A Dozen Data Desires 7.GPS verification of household and
workplace surveys 8.Geo-correlation of travel surveys with built
context 9.Transaction data to discern travel purpose 10.Consistent
variable definitions to allow cross-walking data 11.Consistent
sample rates by region 12.Open data from synthesizers via clients
and from big actor data sources * calibrate/ validate