Activity-Travel Trends An Exploratory Approach Utilizing Multiyear NHTS/NPTS Data and Sequence Alignment Technique Jingyue Zhang Department of Civil & Environmental Engineering University of Connecticut Karthik Konduri Prepared for NEITE 12/4/2017

Outline Motivation and objectives Sequence alignment method Data Result Conclusion and future studies

Motivation Activity-travel behaviors changed over last two decades An increasing portion of households choose to live without a car and use alternative modes for traveling Passenger travel in the United States slightly less reliant on private cars Limitations of current studies Focus on univariate dimension of travel Focus on certain group of people Ignore the temporal dimension of activity-travel behavior

Objectives Identify representative activity-travel patterns by considering multiple attributes of travel Explore how the patterns vary over time

Categorizing Activity-Travel Pattern Individual’s daily activity-travel pattern is represented as an alphabetical sequence Each one or more alphabets represent a certain activity in a certain time interval Temporal dimension of activity-travel is embedded in the sequence Talks about how people describe activity-travel pattern: used sequence to describe it.

Sequence Alignment Method Three steps of sequence alignment approach: Pairwise alignment Exact match of all three attributes: 10 points Match of activity type: 6 points Match of mode/accompaniment: 2 points Mismatch: 0 point Multiple sequence alignment Taxonomic Tree

Data Four waves of National Person Travel Survey (NPTS) and National Household Travel Survey (NHTS) 1990, 1995, 2001, 2009 Samples are selected from New York Metropolitan area Diverse of activity-travel patterns can be observed Experienced the impact of various technological, economic and cultural disruptions over the last 20 years A weighted random sample of 300 individuals was drawn from each of the chosen waves of data

Attributes for Defining Activity-Travel Sequence Example: AAAAAAAAAAGGGGGSSSSSSSSSSSSSSS A: Traveled alone to conduct a discretionary activity by car G: Traveled with others to conduct a maintenance activity by public transit S: Traveled alone home by car Attributes Categories Activity Type Mandatory Maintenance Discretionary Home Travel mode Car Non-motorized mode Public transit Accompaniment Travel alone Travel with others

Taxonomic Tree Talks about ClustalG

Travel Characteristics Pattern 3 has lower average trip rate Greatest proportion of activities in pattern 1 is home activities followed by maintenance activities 36% of activities in pattern 2 are maintenance activities 32% of activities in pattern 3 are mandatory activities

Travel Characteristics Majority of trips in pattern 1 were made by car Majority of trips in pattern 3 were made by taking public transit Majority of trips in pattern 1 and 3 were made alone 63% of trips in pattern 2 were made with others

Demographic Characteristics Pattern 1 has slightly fewer young adults but more persons from 55 to 64 years old Pattern 2 has more persons 65 years old or above Pattern 3 has more young adults and fewer elders Pattern 1 has more males Pattern 2 and 3 have more females

Demographic Characteristics Majority of people in Pattern 1 and 3 are workers 44% of workers in Pattern 2 did not conduct mandatory activity

Representative Travel Patterns There are three types of activity-travel patterns: Pattern 1: Auto Oriented Employed Individuals with a Work Episode (AOE) Pattern 2: Other Employed and Unemployed Individuals (OEU) Pattern 3: Non-Auto Oriented Employed Individuals with a Work Episode (NOE)

Variations within Pattern Number of Sampled Persons 1990 1995 2001 2009 AOE 152 127 138 137 OEU 101 115 118 111 NOE 47 58 44 52 Change pattern 1,2,3 to acronym Number of sampled people who fall into AOE decreased from 1990 to 1995 Number of sampled people who fall into OEU increased from 1990 to 2001

Variations in Average Trip Rate Average trip rate dropped for all three patterns since 2001

Variations in Activity Type Percentage of home activity decreased for AOE and OEU Percentage of discretionary activity increased for AOE and OEU Percentage of mandatory activities decreased for OEU and NOE

Variations in Travel Mode Automobile remains as the predominant mode for AOE Percentage of vehicle trips increased from 2001 to 2009 for OEU For NOE, percentage of transit trips increased from 1990 to 2009

Conclusion & Future Studies Three activity-travel patterns are identified over last 20 years The number of persons fall into each pattern varied over time but not in a large magnitude For each pattern, some variations of travel characteristics are observed over time Limitation and future studies: Computational intensive Apply other sequential data clustering algorithms Incorporate other attributes (i.e. generational cohorts) Talks about that there are so many stuffs going on over last 20 years, we observed three activity-travel patterns. The number of persons fall into each pattern varies over time(number) because of the changes. This is kind of the first step that we predict how the travel pattern changes in the unknown future. We thought that the travel patterns will remain, especially the number of trips that people make everyday for certain types of activity, but how they executed for example the mode might be changed.

Questions?

Appendix: Household Characteristics Persons fall into pattern 3 have smaller household size Persons fall into pattern 2 have fewer workers in household Persons fall into pattern 1 have more drivers and vehicles in household

Appendix: Variations in Household Level Characteristics Household size decreased since 1990 Number of drivers increased from 2001 to 2009 Number of vehicles increased from 2001 to 2009 in pattern 1 and 2, but decreased in pattern 3

Appendix: Variations in Gender Distribution Percentage of female fall into OEU decreased since 1990

Appendix: Variations in Employment Distribution Show both female and male distribution, show workers and non-workers Percentage of employed persons in AOE and OEU increased from 1995 to 2001 and then decreased from 2001 to 2009