effectiveness of different approaches to … · 2019-02-19 · shrp2 l14 effectiveness of different...

SHRP2 L14

EFFECTIVENESS OF DIFFERENT

APPROACHES TO

DISSEMINATING TRAVELER

INFORMATION

ON TRAVEL TIME RELIABILITY

SHRP2 L14 Closeout Meeting – September 26, 2012

Meeting Agenda

Welcome

Part 1: Introduction

Part 2: Assessment of the Project

Part 3: Discussion and Comments on Deliverables

Part 4: Next Steps

Conclusion

2

Beverly Kuhn, TTI

Part 1: Introduction

Introductions

4

Meeting Objectives

REVIEW context, history, and main outcomes of

the SHRP2 L14 project.

DISCUSS comments on Guidebook/Lexicon and

Final Report.

CONCUR on completion timeline, review process

for deliverables, publication issues, and

implementation.

5

Bias / Conflict of Interest Policies

6

Beverly Kuhn, TTI

Karl Wunderlich, Noblis

Part 2: Assessment of the Project

The Elevator Speech

This project seeks to develop a

lexicon of terms that

transportation agencies can

use in messages to users

concerning the reliability of

travel times and facilities in

their systems.

8

Context

9

Uses of reliability information by transportation

profession.

Mobility performance measures.

Planning and project prioritization.

Transit system performance monitoring.

Context

10

Use of reliability information by system users.

Trip planning for habitual trips when new to an area.

Pre-trip planning information immediately prior to

departure.

En route prior to a route or mode choice point.

L-14 Project Objectives

11

Provide agencies with tools to expand the uses of

reliability information to.

Communicate with policy makers.

Communicate with system users.

Develop lexicon of terms or “phrase book”.

Update Valuation ($$) of Reliability information in

Utility Functions.

Develop Guidebook and Deployment Advisory.

Document research results.

Guidebook / Lexicon

• What is reliability information?

• How does it differ from real-time traveler information?

• How can reliability information be conveyed?

• How can the impacts of reliability information be valued?

• What forms of reliability information are most effective?

Innovation Scan, State of Practice Report, Expert Interviews

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Focus Groups/ Surveys Precursor Experiment

Field Operational Test

SHRP2 L14: GUIDEBOOK DEVELOPMENT PROCESS

5

Guidebook / Lexicon









Definition of travel time reliability information

Current forms and media for reliability information

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SHRP2 L14: CONTRIBUTIONS OF INITIAL FOUNDATIONAL RESEARCH PRODUCTS

6

Guidebook / Lexicon











Evaluation methodology

Serenity-sensitive utility function

Preferred terms

Alternative media

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SHRP2 L14: CONTIBUTIONS OF SURVEYS AND PRECURSOR EXPERIMENT

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Guidebook / Lexicon













Preferred terms

Alternative media

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SHRP2 L14: CONTIBUTIONS OF SURVEYS AND PRECURSOR EXPERIMENT

7

• Web interface outside control

of research team

• Inability to vary information

displays to test multiple

scenarios








Expanded Experimentation





Preferred terms

Alternative media

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SHRP2 L14: CONTRIBUTIONS OF EXPANDED EXPERIMENTATION

8

Guidebook / Lexicon













Preferred terms

Alternative media

Evaluated forms and terms

Valuation of reliability info

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SHRP2 L14: CONTRIBUTIONS OF EXPANDED EXPERIMENTATION

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Guidebook / Lexicon

Guidebook / Lexicon













Preferred terms

Alternative media

Evaluated forms and terms

Valuation of reliability info

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SHRP2 L14: RELIABILITY INFORMAITON GUIDEBOOK DEVELOPMENT

9

Reliability Information

19

Reliability information describes underlying trip

variability and includes other contextual data

travelers use to manage on-time performance, e.g.:

Information describing the statistical variation in travel time

dependent on departure time choice.

Data describing on-time performance and lateness risk by

route, mode and destination.

Contextual information to interpret cueing throughout the

travel experience allowing travelers to better assess travel

time and lateness risk both pre-trip and en route.

Examples of Reliability Information

as communicated “person-to-person”

20

Statistical variation in travel times.

To get to the airport at 3 PM, normally it will take 45 minutes, but you’d

better plan for 75 minutes just in case.

If you wait until 4 PM to leave, then plan for at least 2 hours.

Lateness risk descriptions.

Budgeting only 60 minutes between these two meetings? You’ve got a 50-

50 chance of arriving before we start without you.

Contextual information to interpret real-time cueing.

If you find traffic backed up to Exit 4, then you know you’ve got at least

another 30 minutes to go.

Interplay between Reliability and Real-

Time Information in Decision Making

21

My last trip was

about an hour

MY

EXPERIENCE

REAL-TIME

INFO/CUEING

The last traffic report

didn’t mention the

freeway I use

HOW LONG SHOULD I EXPECT THIS TRIP TO TAKE?

RELIABILITY

INFORMATION

Great Day: 35 min

Good Day: 40 min

Bad Day: 75 min

*XDOT 6mo archive

Reliability Information has Highest

Influence When Trip Experience is Low

22

I have never taken

this trip before

MY

EXPERIENCE

REAL-TIME

INFO/CUEING

What radio station

carries traffic

information?

HOW LONG SHOULD I EXPECT THIS TRIP TO TAKE?

RELIABILITY

INFORMATION

Great Day: 35 min

Good Day: 40 min

Bad Day: 75 min

*XDOT 6mo archive

(weak)

(weak) (strong)

Beverly Kuhn (TTI)

Phase 1: Foundational Research

Beverly Kuhn (TTI)

Literature Review

Literature Review

25

Travel time reliability metrics.

Importance of travel time reliability for highway travel, transit, and freight.

State of the practice.

Real-time travel information.

Language used by lay people to talk about range, standard deviation, confidence intervals.

Language from other fields.

Washington State DOT

26

San Francisco Bay 511.org

27

FlightStats.com

28

Beverly Kuhn (TTI)

Expert Interviews

Interview Topics

30

Current methods and experiences related to use of travel reliability information.

State DOTs.

Private sector.

Value of reliability information.

The public.

Transportation operations staff

Public officials.

Potential impacts, goals, challenges.

Little dissemination of reliability information currently.

Key Findings

31

Value to the public.

Believe has value to the public.

Gives an idea of “riskiness”.

Value to operations staff and public officials.

Used to assess performance of the system.

Help determine where improvements are needed.

Used to manage networks and justify programs to improve performance.

Help understand the impact of non-recurring congestion on system performance.

Potential Impacts

32

Highly dependent upon whether or not the public

understands the information provided.

Information accuracy important.

Dependent upon the actual number of travelers who

will use the information for trip planning.

Inrix Traffic!

33

Challenges to Dissemination

34

Inability to quickly collect and analyze data.

Limited staffing.

Determining a format that will be accepted and

understood by users.

Need for quality data.

Implementations in multi-jurisdictional areas.

Short and Long-term Goals

35

Most agencies beginning to discuss the idea of providing reliability information to the public.

Potential media.

Internet.

511 systems.

Mobile phone applications.

Agencies already providing information.

Improve data quality.

Expand coverage.

Provide customizable reports and statistics.

Provide new media options.

Beverly Kuhn (TTI)

Technology and Innovation Scan

Technology and Innovation Scan

37

Innovations in the marketplace.

In-vehicle systems changing and

expanding.

Safety implications.

Market forces.

Crowdsourcing, web-based

innovations.

Consolidation and integration.

Better Data to Come

38

Innovative Media

39

Navigon 5100 3.5-Inch

Portable GPS Navigator with Text-to-Speech and Lifetime Traffic

Magellan Maestro 4050

4.3-Inch Widescreen Bluetooth Portable GPS

Navigator

Garmin nüvi 650 4.3-

Inch Widescreen Portable GPS

Navigator

TomTom GO 920

Portable GPS Vehicle Navigator

Beverly Kuhn (TTI)

Develop Avenues of Investigation

Develop Avenues of Investigation

41

Assessment of results.

Literature review.

Expert interviews.

Technology scan.

Identified key research issues.

Direct the remaining activities.

Key Research Issues

42

Do travelers want this information?

Do they understand reliability separate from real-time information?

Do they understand concepts of average and variability?

What terms can be used to communicate these concepts?

Can travelers assign a dollar cost value to reliability information?

Is there a role for reliability information in real-time systems?

Key Research Issues

43

Do travelers want this info pre-trip or en route?

Does their desire for info change as function of trip

purpose, route, constraints?

Can travelers safely use an en route in-vehicle

system?

Do they want push or pull information systems?

How can multiple data source be displayed?

Will travelers change their habitual travel patterns

based on reliability info?

Key Research Issues

44

Do travelers want this info pre-trip or en route?

Does their desire for info change as function of trip

purpose, route, constraints?

Can travelers safely use an en route in-vehicle

system?

Do they want push or pull information systems?

How can multiple data source be displayed?

Will travelers change their habitual travel patterns

based on reliability info?

Beverly Kuhn (TTI)

Focus Groups

Focus Groups – Purpose

46

Assess understanding of reliability concepts.

Identify terms / determine desire for travel

time reliability information.

Assess desired system features.

Assess willingness to pay.

116 people.

Seattle, Minneapolis, Atlanta, Houston,

Washington DC.

Focus Groups – Script Development

47

Initial scripts contained more analog cases to elicit

discussion of reliability concepts.

E.g. Online Order Shipping Time.

Initial scripts contained more examples of web

graphs.

Much confusion among reliability and real-time

systems.

Examples of Graphics Used in Initial

Focus Groups to Elicit Reliability Terms

48

Example Web Graphic Used in Initial

Focus Groups

49

Final Focus Group Discussion Guide

Topics

50

Constrained

Arrival Time

Constrained

Departure Time

Unconstrained

Unfamiliar

Destination

Appointment

with new

doctor

Weekend evening party

Weekend getaway 3 hours away

Familiar

Destination

Regular

commute

Choosing Day of

the Week for

Class After Work

Pick up produce from farm co-op

anytime Saturday

Task Insertion Stop by neighbors to feed cat

Focus Groups – Findings

51

General interest in using information and felt it could be helpful.

Route options and mobile alerts.

Pre-trip tool, not en route.

Occasional use, especially for unfamiliar trips, cities.

Not seen as beneficial for unconstrained trips.

Difficult to convey reliability concept.

Generally unwilling to pay.

How Focus Group Results Affected

Subsequent Work

52

Inclusion of additional questions to elicit more

lexicon terms.

Addition of open-ended survey.

Addition of Noblis precursor experiment.

Reduced emphasis on graphical displays.

Beverly Kuhn (TTI)

Karl Wunderlich (Noblis)

Usability Testing, Survey, Experiment

Scope & Purpose

54

Determine comprehension and preference of

reliability terms.

Elicit additional terms for Lexicon.

Test user acceptance of reliability terms.

Determine information use, serenity benefits,

willingness to pay, swiftness of personal historical

framework.

Beverly Kuhn (TTI)

Computer Survey

Computer Survey – Purpose

56

More multiple choice questions on concepts and terms.

Preference for departure or arrival time input.

Hypothetical website

Term preferences

Input

Output

Screen titles and labels

N=300: San Jose, Dallas, Hartford, Denver, Miami.

Sites selected based on mobility report rankings, presence of transit and HOV/HOT lanes.

Survey Website

57

Key Findings

58

Most have a desire for information that a planned trip has a chance of taking longer than average.

“Average” and “95th percentile” not clearly understood by many participants.

Most participants will add time to a total trip time estimate, even if it already includes a buffer time.

Mode reliability information needs to be provided to have any effect on mode choice.

Showed preference for various terms for website interface (future trip, predict/plan trip, best route, recommended departure time, etc.).

Beverly Kuhn (TTI)

Open-ended Survey

Open-ended Questions

60

Comprehension of reliability and associated terms.

Preference of terms and reliability information.

Presented trip planning situations for an arrival time-

constrained motorist that included either.

The normal trip time and an uncertainty component.

The normal trip time and the overall trip time to plan for.

Normal Trip Time + Uncertainty of Conditions During Trip

= Trip Time to Plan For

Open-ended Survey

Open-ended Survey Terms

62

Normal Trip Time Uncertainty Component Trip Time to Plan for

Average Travel Time Added Time 95th Percentile Travel Time

Expected Travel Time Extra Time Travel Time for Planning

Typical Travel Time Cushion Time Most of the Time Less Than

Estimated Travel Time Recommended Cushion Time Majority of the Time Less Than

Open-ended Survey

63

Testing conducted in January in Hartford, San Jose,

and Dallas.

N = 190

Manual data entry and scoring required.

Key Findings

64

Buffer Time

No clear preference when assessing how participants determined trip time.

Terms “recommended cushion time” and “cushion time” selected most frequently.

May be difficult to get people to accept trip uncertainty less than they are used to experiencing.

Total Trip Time

“Majority of the time” yielded the best selection of a time to represent the 95th percentile time.

“Most of the time” also fared well.

Lower the uncertainty time, the less trusted by participants.

Decreases workload of driver – don’t have to calculate.

Key Findings

65

Comparison of Travel Time Uncertainty.

Most recognize “buffer time” or “total trip time” as an

upper limit.

Slight preference for “total trip time” over the use of

buffer terms.

Normal Travel Time

No clear preference among various terms tested –

estimated, expected, average, typical.

Any may be use to convey normal travel time.


Precursor Experiment – Utility Function

Precursor Experiment Hypotheses

67

1. Provision of accurate reliability information will result in improved on-time performance and lower generalized travel disutility

2. The perceived value of the reliability information will lag realized benefit.

3. Benefits of reliability information will decline as subjects become familiar with travel time variability

4. There is a “serenity benefit” to traveler information

Precursor Experiment Parameters

68

80 participants in 5 cities

Conducted in conjunction with computer surveys

3 levels of additive information: DMS, real-time, reliability

Each participant uses one level of traveler information throughout experiment

10 commute days, each with 3 departure times

Two decision points for route diversion

Report completed Sep 2011

RELIABILITY, REAL-TIME, AND DMS INFORMATION

SCREEN SHOT OF PRECURSOR EXPERIMENT

Participants with reliability

information on average left

earlier more often than those

without it.

Implication:

Reliability information

does influence departure

time decisions.

70

Experiment Outcomes

Findings – Hypothesis #1

Provision of reliability info results in on-time performance

improvement, and lower generalized travel disutility

Implication: Reliability information quantitatively benefits

unfamiliar time-constrained travelers

71

*schedule offset costs defined within the experiment


72

Perceptions of benefit as measured through value of

information and trip stress do not differ statistically by

level of information whereas trip outcomes do.

Implication: Providers of reliability information may

face an uphill battle in measuring perceptional

impacts of reliability information impacts even when

such information is useful in improving trip outcomes.

Findings – Hypothesis #3 & #4

73

Decline in reliability information benefits not

observed while participants’ willingness to pay for

reliability information declined over time

Traveler do place a value on knowing they will be

late even if the trip outcome cannot be changed.

Implication-It may be that 2 weeks is insufficient for

travelers without reliability information to internalize

trip variability and perform at par with counterparts


Vaishali Shah (Noblis)

Phase 2: Focused Experiment

Experiment Hypotheses

1. Provision of reliability information improves on-time performance versus a control group that receives no reliability information

a. Some forms will be more effective than others

b. Perceived benefit will trail actual benefit

2. The provision of reliability signposts in real-time information will improve on-time performance

3. Benefits of reliability information will decrease over time as participants build a larger experience base

Expanded Experiment Changes…

Only qualitative real-time info provided, previously

quantitative & qualitative real-time info provided

Seven rather than 3 departure options

Eliminate alternate route option

Seven ‘types’ of reliability info instead of one

4-5 weeks instead of 2 weeks of simulated commute

240 participants rather than 80 participants

Two distinct sets of experiments

76

Two Distinct Experiments

Experiment #1 –Compare different forms and content of data to unfamiliar travelers

5 sets of reliability information tested by each participant through 5 weeks of simulated commuting, each week in a different city.

Experiment #2 – Compare the learning curve for unfamiliar travelers with or without reliability information

Half of participants receive simulated reliability information over a 4 week period in one city

Other half do not receive any reliability information.

Experiment #1: Test 7 Reliability Terms (based on terminology document)

78

A. Baseline radio information presented textually

B. Text-based 95th percentile

C. Text-based average plus 95th percentile

D. Text-based 20th, average, and 95th percentile

E. Reliability Signposting

F. Graphical “C” G. Graphical “D”

H. Auditory “B”

Experiment Implementation

Pre-experiment survey, commuting game, and mini

post-experiment survey for Exp#1 users

Often experiment completed within 60-70 minutes

in Washington DC, while we ‘had’ participants for

90 minutes.

Consequently, paper survey added in Chicago and

Houston requests participants rank six of seven

types of info (auditory was excluded)

Expanded Experiment Design

80

1 2 3 4 5 6

90 30 30 30 30 30

98 29 25 33 30 30

A. Control (no reliability info) P P P P P

B. Textual 95TH

P P

C. Textual Avg + 95TH

P P P P

D. Textual 20TH

+ Avg + 95TH

P P P

E. Visual and Textual signposting P

F. Graphical presentation of "C" P P

G. Graphical presentation of "D" P P P

H. Auditory presentation of "B" P P

*city refers to travel in simulated city for participants and not city of experiment implementation

Re

liab

ility

Da

ta C

on

ten

t

#1

5 cities, 1 week each city*

#2

1 city*, 4 wks.

Implementation Version

Planned Participant Count

Two Distinct Experiments:

Valid "good" Participant Count

Participant Characteristics

81

More educated sample than population at large

Older sample population than population at large

Definition of Late Arrival

Exp#1 Schedule Offset Costs

82

Schedule offset savings are statistically and practically

significant for simpler forms of reliability information

No Reliability Info

Reliability Info

*lighter shades are not statistically significant

Exp#1 Late Arrival Frequency

83

When offered simpler forms of reliability information,

participants were late less often

*lighter shades are not statistically significant No Reliability Info

Reliability Info

Exp#1 Perceived Benefits

End-of-week difference in willingness to pay often

not statistically significant between trips with and

without reliability information

End-of-week usefulness higher for ‘simple’ reliability

information but not for ‘complex’ reliability data.

Post-trip usefulness and stressfulness levels often not

statistically significant or lower for reliability terms

84

Exp#1 Comparing Delivery Media

85

Text v. Auditory 95th Percentile Info

Generally no statistically significant differences for trip

outcomes or valuation

Text rated slightly more difficult to understand compard

to auditory

Text v. Graphic Average + 95th Percentile Info

Generally no statistically significant differences for trip

outcomes and valuation with the exception of reducing

stress

Exp#1 Comparing Delivery Media

86

Text versus Graphic 20th, Average and 95th Percentile

Text data resulted in lower schedule offset costs

Text data allowed participants to better manage their

trip decisions.

Exp#2 Late Arrival Frequency

87

Benefits of reliability info decrease over time

Participants using reliability info perform on week 1

as well as their counterparts at week 4

Exp#1 Post Survey

88

Survey replies on

reliability info

usefulness and

complexity mirrors

what is observed in

the experiment.

Benefits reflects

difference between

usefulness and

complexity.

Paper Post-Experiment Survey

89

Different ratings from paper survey on the usefulness of reliability information compared to the quantified valuation observed in the first experiment.

Complex graphic rated equivalent to text 95th with regard to usefulness.


1. Provision of reliability information does improves on-

time performance versus a control group that

receives no reliability information

a. Some forms are more effective than others

Provision of simple forms of reliability information had similar

results whether provided in text, graphic or auditory forms.

More complex graphical & signposting concepts not effective.

b. Perceived benefit do trail actual benefit

Perceived benefits unclear in presence of quantitative benefits.


Benefits of reliability information do decrease over time

as participants build a larger experience base

The decrease is not as “quick” as expected

The gap between reliability info users and others

does not narrow.


92

The provision of reliability signposts in real-time

information does not improve on-time performance

The signposting concept was not successful for

participants in the management of trip outcomes and

stress reduction.

To some degree, this was because of the complexity of

the presentation and the brevity with which participants

were required to learn and interpret information

content.

Potential Future Research Directions

93

Reliability information in the context of more complex

multi-modal trip, trip chain and tour planning.

Impact of reliability information on broader range of

travel-related choices.

Mechanisms of reliability information under-valuation

by users.

Beverly Kuhn, TTI

Part 3: Discussion and Comments on

Deliverables

Lexicon

95

Phrase book to be used across platforms.

Potential uses.

Public outreach.

Performance measure reports.

TMC pre-trip planning websites.

Commercial traffic routing systems.

Guidebook Chapters

96

1 – Introduction

2 – The Concept of Travel Time Reliability

3 – Key Messages

4 – Relevant Travel Time Reliability Terms

5 – Methods of Communicating Travel Time Reliability

6 – Measuring Information Effectiveness

7 – Emerging Trends

8 – Final Remarks

9 – References

Lexicon Terminology

97

95th Percentile

Arrival Time

Average Travel Time

Buffer Time

Departure Time

Recommended Departure Time

Recommended Route

Reliability

Lexicon – 95th Percentile

98

Technical Term 95th Percentile Definition The point on a travel time frequency distribution at which 95% of the trips made would be at or less than the identified time.

Usage To describe the longest time a driver can expect a trip to take.

Recommendation Alternate Phrase Wording Context / Additional

Information

Information Technology Platforms

Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best

Majority of the time

“The majority of the time, your trip will take X minutes or less.”

√ √ X √+ √+

MAJORITY OF TIME TRIP TO [DESTINATION]

X MIN OR LESS

√ √ √> √ √

Graphical representation of the average + 95th percentile. √ √ X X √

Adequate

Most of the time

“Most of the time, your trip will take X minutes or less.”

√ √ X √+ √+

MOST OF THE TIME TRIP TO [DESTINATION]

X MIN OR LESS

√ √ √> √ √

Travel time for planning

“Travel time for planning is X minutes or less.”

√ √ X √+ √+

95th percentile trip time

“The 95th percentile trip time is X minutes or less.” Provide description such as “19 out of 20 days”.

√ √ X √+ √+

Avoid

Maximum trip time Agency concerns regarding liability and credibility.

N/A N/A N/A N/A N/A Most common trip time

Worst case trip time

Lexicon – Arrival Time

99

Technical Term Arrival Time Definition The time at which a traveler would arrive after a trip.

Usage To tell the driver when they can expect to arrive at their destination.


Information


Web Mobile

Web

Dynamic

Message Sign

Text Mobile Applica

tion

Best Arrive by “Arrive by X:XX am / pm.” √ √ X √ √

ARRIVE BY X:XX AM/PM √ √ √>% √ √

Adequate

Arrive at “Arrive at X:XX am / pm.” √ √ X √ √

ARRIVE AT X:XX AM/PM √ √ √>% √ √

What time do you want to get there?

This question would be used by a traveler to enter a preferred arrival time into a travel time calculator to receive a recommended departure time.

√ √ X X √

What’s the earliest you can arrive


√ √ X X √

What’s the latest you can arrive?


√ √ X X √

Avoid

99

Lexicon – Average Travel Time

10

0

100

Technical Term Average Travel Time Definition An average of historical travel times calculated over a specified time interval for a specified trip or roadway segment.

Usage To describe the typical travel time a driver can expect a trip will take.


Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best

Estimated travel time

“Estimated travel time is X minutes.” √ √ X √+ √+

“It is estimated that your trip will take X minutes.”

√ √ X √+ √+

EST THAT TRIP TO [DESTINATION] WILL TAKE X MIN

√ √ √> √ √

Approximate travel time

“It will take approximately X minutes to make your trip.”

√ √ X √+ √+

APPROX X MIN

TO [DESTINATION] √ √ √> √ √

Adequate

Typical travel time “Typical travel time is X minutes.” √ √ X √+ √+

Graphical representation of the average + 95th percentile (typical day and bad day).

√ √ X X √

Graphical representation of the 20th percentile + average + 95th percentile (good, typical, and bad day).

√ √ X X √

Average travel time “Average travel time is X minutes.” √ √ X √+ √+

Expected travel time “Expected travel time is X minutes.” √ √ X √+ √+

Avoid

Historical Travel Time

Difficult to determine relevance with no comparison to real-time information.

N/A N/A N/A N/A N/A

Lexicon – Buffer Time

10

1

101

Technical Term Buffer Time Definition The average travel time multiplied by the buffer index.

Usage To describe how much extra time a driver should plan for a trip they wish to take.

Recommendation Alternate Phrase Wording Context / Additional Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best Extra time

“Extra time for trip is X minutes.” √ √ X √+ √+ Extra time to [destination] is X min

√ √ X √ √

Adequate

Added time

“Added time for trip is X minutes.” √ √ X √+ √+

Added time to [destination] is X min √ √ X √ √

Recommended cushion

“Recommended cushion for trip is X minutes.”

√ √ √ √+ √+

Avoid Cushion

Preference shown for other terms. N/A N/A N/A N/A N/A

Lexicon – Departure Time

10

2

102

Technical Term Departure Time

Definition The time at which a traveler would depart for a trip. Usage To indicate the time a traveler departs for a trip. For DMS applications, message would need to be set in context with other

information, such as destination, travel time, or route.


Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best Departing at “Departing at X:XX am / pm.” √ √ X √ √

Leave at “Leave at X:XX am / pm.” √ √ X √ √

Adequate

What time will you start your trip?

This question would be used by a traveler to enter a start time into a travel time calculator to receive an arrival time.

√ √ X X √

Leave by “Leave by X:XX am / pm.” √ √ X √ √

Departing by “Departing by X:XX am / pm.” √ √ X √ √

What’s the earliest you can start your trip?


√ √ X X √

What’s the latest you can start your trip?


√ √ X X √

Avoid

Lexicon – Recommended Departure Time

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3

Technical Term Recommended Departure Time

Definition A time of departure displayed to a traveler which is calculated by a traveler information system and would ensure an on-time arrival for a given level of added delay.

Usage To indicate the time a driver should depart for a trip to ensure they arrive at their destination on time. For DMS applications, would need to be set in context with other information, such as destination, travel time, or route.


Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best Recommended departure

time

“Recommended departure time is X:XX am / pm.”

√ √ X √+ √+

Adequate

Suggested departure time “Suggested departure time is X:XX am / pm.”

√ √ X √+ √+

Estimated departure time>

“Estimated departure time is X:XX am / pm.” >>

√ √ X √+ √+

95th percentile departure time

“The 95th percentile departure time is X:XX am / pm.” Provide description such as “19 out of 20 days”.

√ √ X √+ √+

Avoid

103

Lexicon – Recommended Route

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4

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Technical Term Recommended Route

Definition A route between two points calculated by a traveler information system which would provide the best probability of on-time arrival to a specific destination.

Usage To describe the route a driver should take for a planned trip to ensure he/she arrives on time to his/her destination.


Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best Best route

“Best route is via [facility].” √ √ X √+ √+

BEST ROUTE

TO [DESTINATION] TAKE [FACILITY]

√ √ √> √ √

Adequate

Forecasted trip “Forecasted trip is via [facility].” √ √ X √+ √+

FORECASTED TRIP TIME

VIA [FACILITY] X MIN

√ √ √> √ √

Most reliable trip “Most reliable trip is via [facility].” √ √ X √+ √+

MOST RELIABLE TRAVEL TIME


√ √ √> √ √

Most predictable trip “Most predictable trip is via [facility].” √ √ X √+ √+

MOST PREDICTABLE TRAVEL TIME


√ √ √> √ √

Most consistent trip “Most consistent trip is via [facility].” √ √ X √+ √+

MOST CONSISTENT TRAVEL TIME


√ √ √> √ √

Avoid

Historical trip conditions Difficult to determine relevance with no comparison to real-time information. Preference shown for other terms.

N/A N/A N/A N/A N/A Least variable time

Lexicon – Reliability

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5

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Technical Term Reliability

Definition A consistency or dependability in travel times between two points, as measured from day to day or across different times of day.

Usage To describe the variability of travel times to drivers so they can plan their trip with more robust information.

Recommendation Alternate Phrase Wording Context /

Additional Information


Web Mobile

Web

Dynamic Message

Sign

Text Mobile

Application

Best Predictable “Most predictable trip” √ √ X √ √

Adequate

Reliable “Most reliable trip.” √ √ X √ √

Consistent “Most consistent trip.” √ √ X √ √

Vary “Trip varies.” √ √ X √ √

Avoid

Differ

Preference shown for other terms.

N/A N/A N/A N/A N/A

Fluctuate

Change

Go up or down

Increase or decrease

Deviate

Lexicon Not Provided

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Buffer Index

Not tested in the human factors studies.

Metric unlikely to be used by roadway users.

Delay Time

Not tested in human factors studies.

Terms tested for the related concept “buffer time”.

Free Flow Travel Time

Not tested in focus groups or surveys.

Phrase “great day” used in enhanced laboratory study along with corresponding “typical” and “bad” days.


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Peak Travel Time


Terms tested for similar concept “95th percentile travel time”.

Planning Time


Terms tested for similar concept “95th percentile travel time”.

“Travel time for planning” was one of the alternatives tested to represent 95th percentile travel time.

Planning Time Index


Metric unlikely to be used by roadway users.


108

Total Trip Time


A commonly-used phrase and few synonyms exist.

Travel Time Savings


A commonly-used phrase and few synonyms exist.

Travel Time Range

In computer survey, subjects more often felt a single trip time (typical/avg or 95th percentile) was reliable when compared to a travel time range.

Trend Information


Final Report

1 – Introduction

2 – Literature Review

3 – Expert Interviews

4 – Technology and Innovation Scan

5 – Develop Avenues of Investigation

6 – Focus Groups

7 – Usability Surveys

8 – Travel Behavior Laboratory Experiment

9 – Enhanced Laboratory Experiment

10 – Lexicon Development

11 – Final Remarks

12 – References

109

Beverly Kuhn, TTI


Part 4: Next Steps

Project Timeline

111

Project Closeout Meeting with TETG Sep 26, 2012

Discuss comments on Draft Guidebook & Deployment Advisory

Discuss comments on Final Report

Address TETG Comments & Submit Final Documents Oct 15, 2012

Draft Guidebook & Deployment Advisory

Final Report

Review Process Oct-Jan 2013

Project Conclusion Jan 31, 2013

Product Review Process

112

Publication Issues

113

Implementation

114

How can the main outcome of this project – the

Guidebook and Deployment Advisory – be used by

an operating agency?

Who are the potential first users?

Questions

Beverly Kuhn, TTI

[email protected]

979-862-3558


[email protected]

202-488-5707

Vaishali Shah, Noblis

[email protected]

202-488-5715

115