Travel Time Reliability in the SLOCOG...

MOVING THINKINGFORWARD

Travel Time Reliability in the SLOCOG Region

October 27, 2014

San Luis Obispo Council of Governments

Transportation Education Series

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Transportation Education Series - Agenda

• Grab Some Free Lunch !!

• Introductions and Presentation Format

• Travel Time Reliability

– US101 Mobility Master Plan

– What is Travel Time Reliability?

– Data Collection for the Travel Time Reliability Metric

– Travel Time Reliability in the SLOCOG Region

• Conclusions and Q/A

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Presenters

• Jim Damkowitch, Kittelson & Associates, Principal Planner

• Dr. Richard Dowling, Kittelson & Associates, Senior Principal

• Darryl dePencier, Kittelson & Associates, Planner

• Jorge Aguilar, Wallace Group, Principal

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Host: San Luis Obispo Council of Governments Sponsors: Kittelson & Associates and Wallace Group

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SLOCOG Member Agencies:

• Paso Robles • Atascadero • San Luis Obispo • Pismo Beach • Arroyo Grande • Grover Beach • County of San Luis Obispo

Regional Partners:

• Caltrans District 5 • San Luis Obispo Regional Transit Authority • San Luis Obispo Air Pollution Control District


KAI - Transportation Education Series (TES)

• Promote professional development & advancement

• Wide range of topics (what’s of interest)

– Travel Time Reliability (today)

– Multi-modal LOS & Highway Safety Manual (SLO July 17, 2012)

– KAI and Wallace Group plan to co-host another TES in the Feb-March timeframe on the topic of Emerging Trends in Planning and Design

• TES counts for Continuing Education Requirement credits (2.0)

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US101 Mobility Master Plan

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Smart Mobility Framework

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US101 Corridor Mobility Master Plan

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US 101 Corridor Mobility Master Plan & Travel Time Reliability

• Incorporated as part of the freeway operational analysis

• Travel Time Reliability – first application in District 5

• Travel Time Reliability represented by “Buffer Time” – Buffer Time – added increment of time required to ensure you reach

your destination at the desired time 95% of the time.

– How much earlier do you need to leave your home to ensure arriving on time.

– Time you could spend at home (effect is assumed to be similar to when you experience delay while driving your car i.e., travel time delay)

• Buffer time reduction and delay reduction added to yield total monetary time saving benefits of US101 mainline improvement concepts

• Results? But first - what is travel time reliability?

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What is Travel Time Reliability?

• Why is Travel Time Reliability Important?

• Travel Time Reliability Concepts and definitions

• Travel Time Reliability applications for performance measurement

• Travel Time Reliability analysis tools

• Data needs for measuring travel time reliability

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Who are the Customers?

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Customer Needs - Travelers

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Customer Needs – Goods Movement

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What are the Causes of Unreliability?

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Why is Travel Time Reliability Important?

1) Our roadway networks are more frequently operating in a near or above capacity

2) Uncertainties in travel time adversely impact us in multiple ways

3) We don’t have a way to measure the benefit of many of our strategies and investments

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http://ops.fhwa.dot.gov/publications/tt_reliability/TTR_Report.htm



• Old days (Capacity-oriented)

– Network build-out and expansion

– Secure funding environment

– Traditional performance metrics

• New way (Reliability-oriented)

– How best to manage the system we have

– Financial, environmental and public perception problems

– Improvements that affect reliability more than capacity

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• Paradigms are shifting

– MAP-21 (Federal)

– SB 375 (CA)

– SB 743 (CA)

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• It will be required – MAP-21

– FHWA Notice of Proposed Rule Making – February 2015

• You miss out on many cost-effective solutions unless you consider reliability. – TSM&O – Traffic system management and operations strategies

• Ramp metering, HOV lanes, Express Lanes, signal optimization

– Active Traffic and Demand Management strategies

• Proactive traffic management (anticipating breakdowns).

• Dynamic ramp metering, Dynamic tolls, traffic adaptive controls

• Speed harmonization, advanced queue warning, Traveler Info.

– Getting longer service lives out of expensive capacity improvements

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Definition

• Travel time reliability is:

– The distribution of travel times that a traveler should anticipate if starting a trip at a given point at a given time and day.

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Alternative Definitions

• Reliability is described by the variability in travel times

• Reliability is the amount of time that the system fails to perform adequately (classical system definition)

• Reliability is the predictability of users’ travel time experience

• Reliability is the likelihood of arriving on-time

– All are valid but the underlying theme is that travel times for the same trip are not consistent from day-to-day for a variety of reasons

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Travel Time Distribution

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Characterizing Reliability

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Buffer Time

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Buffer Time


The TTI Statistic

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The Percent < 45 Mph

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Commonly Applied Reliability Measures

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Is it hard?

• It can be.

– Imagine doing HCM analysis 1,000 times.

• But many tools available or under development that will make it easier (less hard).

– FHWA NPMRDS travel time monitoring data set for NHS

– University of Florida/FDOT spreadsheet

– SHRP2-C11 Model

– HCM 2010 Update

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Tools for Reliability

• Measuring Reliability

– FHWA NPMRDS travel time monitoring data set for NHS

• Predicting or Estimating Reliability

– University of Florida/FDOT spreadsheet

– SHRP2-C11 Method

– HCM 2010 Update

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FHWA NPMRDS

• The Federal Highway (FHWA) National Performance Management Research Data Set (NPMRDS) – A vehicle-probe (cell phone tracking) travel time data base for the

National Highway System (NHS)

• Data collected by HERE (Nokia)

– Average travel times by TMC links for every 5 minutes of every day back to October 2013.

• Passenger cars and trucks (FHWA vehicle classes 7 and 8)

– Its big. Requires GIS expertise and large database tools

• MS Access and Excel not big enough

– Its Accurate – No data smoothing, No interpolation.

– Available to MPO’s and State DOT’s

• [email protected]

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University of Florida/FDOT • The UF/FDOT Reliability Spreadsheets

– Freeway

– Arterials

• How it works – Allocate AADT to each hour of year

– Compute recurring congestion using HCM capacities

– For each hour of 24 hour day compute travel times for 24 possible scenarios combining weather, incidents, work zones

– Assign probabilities to each scenario

– Compute reliability statistics

• Lots and lots of assumptions built in – Seasonal traffic variation, incident frequencies, weather

frequencies….

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SHRP2-C11 Method • Developed for estimating freeway reliability

• How it works – Estimate recurring delay based on peak hour speed.

– Estimate incident related delay based on peak hour v/c ratio.

– Compute average annual travel time with incidents.

– Compute 95th percentile travel time.

– Compute percent of trips below 45 mph.

• Sensitivities – Sensitive to regular peak hour congestion

– User must bring in outside data to estimate impacts of ATDM strategies.

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HCM Update • Under Development

• Available in 2 years

• How it works

– Create thousands of scenarios combining weather, incidents, demand, work zones.

– Select capacity adjustments for each scenario.

– Use Monte Carlo to select a few hundred for HCM analysis.

– Run HCM analyses.

– Tally statistics.

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1965-2000 HCM Methods

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HCM 2010+ Reliability Method

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• Nobody really knows.

• US Experience (Exhibit 37-1 HCM)

– 95% TTI on US Urban Freeways ranges from 1.09 to 3.60

• Median is 1.47

– 95% TTI on US Urban Arterials ranges from 1.27 to 1.98

• Median is 1.44

• Recent TRB paper

What is Good Reliability?

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• FHWA Primer on Incorporating Reliability into the Congestion Management Process (FHWA-HOP-14-034)

– Available on FHWA website (soon)

References on Reliability

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• Highway Capacity Manual

• Chapters 36 and 37 (on web)

References on Reliability (2)

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• To Predict or Estimate Reliability – Demand Variability (Seasonality)

– Weather frequencies

• Light, medium, heavy Rain, snow

– Incident and work zone frequencies

• Number of lanes blocked

• Duration

• To Measure Reliability – Hourly speeds and volumes 24/7 for 6 months to a year

– FHWA NPMRDS

Data Needs for Reliability

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Case Study – SLOCOG 101 Mobility Master Plan

• Reliability measured using Bluetooth detection

• Reliability estimated University of Florida method

• Reliability was predicted by applying UF method growth applied to measured baseline

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US 101 Reliability Measured

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£¤101

£¤101

1661

1

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46

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Paso Robles

Atascadero

San Luis Obispo

Arroyo GrandePismo Beach

OceanoGrover Beach

Morro Bay

¯• 10 detectors deployed along US 101

• 9 individual segments

• Data was collected continuously for 2 months


What is Detected?

• Any “discoverable” Bluetooth device!

– Cell phones, game systems, laptops, some cars themselves

• Unique ID number (MAC Address) for all Bluetooth devices

– Only partial address is stored to protect anonymity

• Any device seen by two or more detectors can be tracked as a trip

– Typically varies from 5 – 15 % of traffic

– Provides travel time / average speed / direction

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Roadside Detectors

• Devices placed adjacent to the roadway – mounted to existing structures when possible

• Detection range ~300’

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BlueMAC Detectors

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System Components

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• Detector / Transmitter

– Processor

– A/C or battery powered

– Solar charger / controller

– Connector ports

– Housing


Travel Time Reporting

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• Southbound – Los Osos Valley Road to Avila Beach Road

– Bi-modal PM peak observed – June 26th, 2014


Travel Characteristics

• Trip Distance

• Expected Travel Time

• Number of Trips

• Average Speed (mph)

• Average Travel Time

• Standard Deviation

• 15th Percentile

• 85th Percentile

• 95th Percentile

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4.03

202 (3:22)

1214

48.5

299 (4:59)

146.3

200 (3:20)

509 (8:29)

583 (9:43)


PM Travel Time Reliability (4PM to 6PM)

• Sunday

• Monday

• Tuesday

• Wednesday

• Thursday

• Friday

• Saturday

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(95th Percentile TT – Avg TT) / Average TT

(237s – 215s) / 215s * 100% = 10%

(247s – 217s) / 217s * 100% = 14%

(250s – 221s) / 221s * 100% = 13%

(244s – 222s) / 222s * 100% = 10%

(271s – 229s) / 229s * 100% = 18%

(320s – 260s) / 260s * 100% = 23%

(251s – 219s) / 219s * 100% = 15%


Neighborhood Studies

• Linda Vista Neighborhood – BCS National Championship Game

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Cost

• Digiwest unit cost (max - $3,525 / unit) including

– BlueMAC detector with housing and power hookups

– Initial installation (if mounting locations are accessible via ladder)

– 1 Year Cellular services for data transmission (can also communicate via Fiber Optic or other existing communications network)

– 1 Year Cloud services for data storage

– BlueMAC website for data analytics and reporting

– Leasing and project specific costing available by request

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• Objective – Incorporate Travel time reliability as a metric used in the B/C analysis – Buffer time (during typical weekday: Tuesday – Thursday)

• Approach Existing Conditions – Vehicle Operating Conditions

• Published Traffic Volumes and Counts

• Bluetooth Data (4 months)

– Incidents • Incident Inventory in PeMS (12 months)

• CHP Reports (12 months)

– Weather • Paso Robles Airport (12 months)

• San Luis Obispo Airport (12 months)

– Work zones • Caltrans Website

• Caltrans PeMS (12 months)

US 101 Case Study in Reliability

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• Approach Future Conditions – Travel Demand

• SLOCOG Travel Demand Model (NCHRP-255 Adjustments for Daily Volumes) • Caltrans K & D Factors for full 24-hour Distribution • FDOT Procedure

– Expanded procedure for bi-directional results – Validated to baseline TTI

– Incidents (same as baseline – allowed FDOT Procedure to adjust based on volume) – Weather (same as baseline – allowed FDOT Procedure to adjust based on volume) – Work zones (same as baseline – allowed FDOT Procedure to adjust based on volume)

• FDOT Procedure (recap) – Compute recurring congestion using HCM capacities – For each hour of 24 hour day compute travel times for 24 possible scenarios combining

weather, incidents, work zones – Assign probabilities to each scenario – Compute reliability statistics (buffer time, BTI, travel time, TTI etc.)

• Delta Method: (FDOT Future – FDOT Baseline) + Empirical Baseline


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• Annualize 24-hour Distribution Effects on Capacity – Weather

– Incidents

– Work zones

– Recurring congestion

• Annualize 24-hour Distribution Effects on Speeds – Weather

– Incidents

– Work zones

– Recurring congestion


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• Travel Time Reliability on US 101

– Generally good reliability corridor-wide

• < 8 minutes Southbound

• < 4 minutes Northbound

– Anticipated to not dramatically change in the future

• Weather not a significant factor

• Work zones not a significant factor

• Collision rates generally at or below statewide average for like facilities

US 101 Case Study Findings

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• Travel Time Reliability on US 101

– Where do reliability issues occur:

• Five-City Area and City of San Luis Obispo

– Southbound Direction

– Northbound Direction (Five-City Area)

• Correlates to where the greatest congestion is projected to occur

• Supports US101 Mobility Master Plan – Buffer Time Increased B/C of HOV Improvement in Segment 1 by 8%

– Buffer Time Increased B/C of HOV Improvement in Segment 2 by 4%


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• Travel Time Reliability Metric

– We did it

• Wasn’t too painful

• Learned from our experience

– More than 4-months of data (April – August)

– Would have been nice to test other reliability tools

– Expand analysis to weekend

• Consistent with MAP-21 – provides greater support US101 Mobility Master Plan Recommendations

• Supports PSR-PDS Release by SLOCOG for examining operational improvement on SB US 101 Five-City Area


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Questions?

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Questions?

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Travel Time Reliability in the SLOCOG...

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