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L02: Establishing Monitoring Programs
for Mobility and Travel Time Reliability
Project Overview
For the:
L38 Preliminary Meeting
August 1, 2012
George List, NC State
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Main Work Products
• A guidebook that describes how to develop a travel time
reliability monitoring system (TTRMS)
• Supporting methodologies
• Data processing and management
• Data analysis
• Causal factor assessment
• Validation of the methodologies
• Illustrations of how to use a TTRMS
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Structure of the Monitoring System
• It requires new data feeds to capture data about the influencing
factors; it requires skill in statistical analysis to have greatest value
• It allows you to understand how much a system’s travel times vary,
what makes them vary, and (implicitly) what corrective actions
might help
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Analysis Methodology Overview
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• The analysis process
involves several steps
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Both Vehicles and Facilities
Distribution of tv
for 7:05 PM on
Feb 25, 2011
20 min. 19 min.
21 min.
Midnight
Noon
Time of Day
TT-PDF for the
Segment / Route
Se
gm
en
t o
r R
ou
te
Non-recurring
event impacts
Travel times for
individual vehicles
Average travel times at a specific
time of day for different days
Distribution of tavg
for 7:05 PM
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Measurement Points
• A clean topology is needed to get clean data
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Monuments,
Segments, Routes
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Imputation
• Clean and complete data are needed
• You are trying to monitor travel times at the 1-5 minute level
• You are monitoring variations across time, across distances, and
among vehicles
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AVI - Timestamps
AVL – Locations and Timestamps
Passage Times
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Extracting Travel Times
• Differentiating between trip- and travel-times is crucial
• Remove the trips with stops and side trips, or filter them out, but do
not interfere with incident detection
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Constant Transitions During Peaks
• The travel time world is richly varied
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0
5
10
15
20
25
0:00:00 0:07:12 0:14:24 0:21:36 0:28:48 0:36:00 0:43:12 0:50:24 0:57:36 1:04:48 1:12:00
Tra
vel T
ime
Relative Minutes
Bluetooth-Based Vehicle Travel Time Trends, I-5 Northbound, Sacramento
5-6PM 1/24/11
7-8AM 1/27/11
8-9AM 2/2/11
7:30-8:30AM 2/8/11
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CDF Animations
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Vehicular Variance Trends
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Route Travel Times and Rates
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τbc (sec/mi)
50 60 70 80 90 100 110
τab
(sec/mi)
60
80
100 8% 24% 5%
120 6% 21% 7% 1%
140 1% 7% 2%
160 1% 3% 2%
180 1% 2% 1%
200 2% 1%
220 1% 1%
240 1% 1%
260
280
300
>300
1
Use correlations
Use incidence matrices
Use cascading queues
Walk the time-space matrix
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Operating Regimes • Regimes help clarify the cause-effect relationships
• Regime = (congestion condition + non-recurring event condition)
• Regime = consistent system behavior
• Reflects traffic conditions
• Supports intuitive understandings
• How many regimes you need is site specific
• The impacts from non-recurring events vary widely and depend on congestion
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None Weather Incident
High
Demand
Special
Event
Work
Zone
Uncongested
Low
Moderate
High
Event
Congestion
Level
Reliability Regimes
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Congestion Condition Labeling
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22 2
1
1 n
r i r r i
i
x r and x rn
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Non-Recurring Event Data
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DataTime Visib Wind Wind Spd Gust Spd Precip Events Cond
1/28/2011 0:53 10 Calm Calm - N/A Clear
1/28/2011 1:53 10 South 3.5 - N/A Clear
1/28/2011 2:53 10 Calm Calm - N/A Clear
1/28/2011 3:53 10 South 5.8 - N/A Clear
1/28/2011 4:53 10 Calm Calm - N/A Clear
1/28/2011 5:53 10 Calm Calm - N/A Clear
1/28/2011 6:53 10 Calm Calm - N/A Clear
1/28/2011 7:53 10 Calm Calm - N/A Clear
1/28/2011 8:53 10 Calm Calm - N/A Clear
1/28/2011 9:53 10 Calm Calm - N/A Clear
1/28/2011 10:53 10 NNE 3.5 - N/A Clear
1/28/2011 11:53 10 NE 4.6 - N/A Clear
1/28/2011 12:53 10 NNE 5.8 - N/A Clear
1/28/2011 13:53 10 NNE 9.2 - N/A Clear
1/28/2011 14:53 10 Variable 4.6 - N/A Clear
1/28/2011 15:53 10 SSW 5.8 - N/A Clear
1/28/2011 16:53 10 SSW 3.5 - N/A Clear
1/28/2011 17:53 10 Calm Calm - N/A Clear
1/28/2011 18:53 10 South 3.5 - N/A Clear
1/28/2011 19:53 10 Calm Calm - N/A Clear
1/28/2011 20:53 10 South 8.1 - N/A Clear
1/28/2011 21:53 10 SSW 3.5 - N/A Clear
1/28/2011 22:53 10 Calm Calm - N/A Clear
1/28/2011 23:53 10 Calm Calm - N/A Clear
1/29/2011 0:53 10 Calm Calm - N/A Clear
Incident Id Start Time Dur (min) Freeway Abs PM Location Description
11724869 1/28/2011 3:50 41 US50-E EB US50 ON 15TH ST OFR 1182 - Collision - Non Injury
11724935 1/28/2011 5:45 7 US50-E EB US50 ON POWER INN RD OFR 1125 - Traffic Hazard
11724958 1/28/2011 6:02 27 US50-E 5.89 EB US50 ON 34TH ST OFR 1182 - Collision - Non Injury
11725029 1/28/2011 6:55 0 US50-E EB US50 JEO EL DORADO HILLS BLVD 1126 - Disabled Vehicle
11725175 1/28/2011 7:57 2 US50-E 31.755 EB US50 JWO BASS LAKE RD 1125V - Traffic Hazard - Vehicle
11725425 1/28/2011 9:33 22 US50-E 17.601 EB US50 JWO SUNRISE BLVD 1125 - Traffic Hazard
11725782 1/28/2011 12:24 22 US50-E 298.514 EB US50 JWO SB SR99 1125 - Traffic Hazard
11725927 1/28/2011 13:17 0 US50-E 64.033 EB US50 AT HAZEL VALLEY RD 1183 - Collision - No Further Details
11726010 1/28/2011 13:49 10 US50-E EB US50 AT FRONT ST 1125V - Traffic Hazard - Vehicle
11726196 1/28/2011 14:51 59 US50-E 10.488 EB US50 JWO NB WATT AV 1183H - Collision - Blocking Lane - No Details
11726269 1/28/2011 15:11 23 US50-E EB US50 JWO POWER INN RD 1126 - Disabled Vehicle
11726302 1/28/2011 15:23 0 US50-E EB US50 JWO 48TH ST 1126 - Disabled Vehicle
11726453 1/28/2011 16:03 19 US50-E EB US50 JWO POWER INN RD 1179H - Collision - Ambulance - Blocking Lane
11726532 1/28/2011 16:29 0 US50-E 10.688 EB US50 AT NB WATT AV 1126 - Disabled Vehicle
11726568 1/28/2011 16:39 0 US50-E 26.68 EB US50 JWO E BIDWELL ST 1125 - Traffic Hazard
11726655 1/28/2011 17:04 2 US50-E 8.83 EB US50 JWO HOWE AV FIRE - Fire
11726737 1/28/2011 17:29 14 US50-E 5.89 EB US50 ON 34TH ST OFR 1125V - Traffic Hazard - Vehicle
11727378 1/28/2011 22:21 60 US50-E 26.88 EB US50 AT E BIDWELL ST 1126 - Disabled Vehicle
11727377 1/28/2011 22:25 0 US50-E 29.838 EB US50 JEO LATROBE RD 1126 - Disabled Vehicle
11727559 1/29/2011 1:25 20 US50-E 298.384 EB US50 JWO NB SR99 1126 - Disabled Vehicle
11727710 1/29/2011 6:12 1 US50-E 298.514 EB US50 JWO SB SR99 1125 - Traffic Hazard
Weather
Incidents and Other Events
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Non-Recurring Event Labeling
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A
B
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Causal Factor Analysis
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Variations by Regime
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Mitigating Strategy Identification
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Portrayal and Data Storage • Working with PDFs and CDFs works great
• You can use the PDFs and CDFs to answer
every question
• Both are valuable, in different ways
• The raw CDFs and PDFs help the most with
insights
• Parametrically-based distributions aren’t really
helpful
• Non-parametric analyses are not difficult, they
lend insights that might otherwise be missed,
and they are intuitive
• You should store the CDFs
• They are easy to identify, easy to verify, and
intuitive
• The PDFs can be derived from them
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Travel Rates
• It is valuable to study travel rates (travel times / unit distance)*
• They allow comparisons among facilities
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* Not speeds
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Thanks / Questions
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