00818733

Component

https://doi.org/10.3141/1752-04

http://scholar.google.com...+Kim&publication_year=2001

Activity and travel demand analysis can be greatly improved by a more realistic description of the relationship between activity engagement and trip-making behavior when person and household variation are accounted for jointly. Four activity pattern groups and four travel pattern groups, obtained in the past using cluster analysis and applied to behavioral indicators (e.g., activity frequency and duration), are analyzed using multinomial logit and multilevel multinomial logit (multi-MNL) models. All models include temporal, spatial (residence and workplace), household, and person effects. The multilevel models, designed for hierarchical data structures, also include correlated random components among the pattern options at the household and person levels. First, past research results are confirmed that contextual variables (e.g., household, neighborhood, time) are important explanatory variables for these activity and travel patterns and that temporal effects are much stronger for activity pattern groups than for travel pattern groups. Then, using the multi-MNL models, a complex structure in unobserved heterogeneity is identified in which choices are correlated among some patterns at the household level and among other patterns at the person level. Both travel and activity pattern analyses, however, indicate that unobserved heterogeneity should be accounted for at both levels when regression models are estimated.

This paper appears in Transportation Research Record No. 1752, Travel Patterns and Behavior; Effects of Communications Technology.

English

p. 23-31

2001

Transportation Research Record

0309072131

References (23) ; Tables (7)

Activity choices; Households; Multinomial logits; Persons and personal characteristics; Travel patterns

Highways; Planning and Forecasting; Public Transportation; Society; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Oct 1 2001 12:00AM

• ASSESSING URBAN CONTEXT-INDUCED CHANGE IN INDIVIDUAL ACTIVITY TRAVEL PATTERNS: CASE STUDY OF NEW RAILWAY STATION
• ASSOCIATION RULES IN IDENTIFICATION OF SPATIAL-TEMPORAL PATTERNS IN MULTIDAY ACTIVITY DIARY DATA
• COEVOLUTIONARY APPROACH TO EXTRACTING AND PREDICTING LINKED SETS OF COMPLEX DECISION RULES FROM ACTIVITY DIARY DATA
• DIRECT FORECASTING OF FREEWAY CORRIDOR TRAVEL TIMES USING SPECTRAL BASIS NEURAL NETWORKS
• DRIVERS' ROUTE CHOICE RULES AND NETWORK BEHAVIOR: DO DRIVERS BECOME RATIONAL AND HOMOGENEOUS THROUGH LEARNING?
• DYNAMIC TRAFFIC ANALYSIS WITH STATIC DATA: GUIDELINES WITH APPLICATION TO PARIS
• ESTIMATING TIME-DEPENDENT ORIGIN-DESTINATION TRIP TABLES WITH TRIPS ORIGINATING IN MULTIPLE TIME SLICES
• EXPERIMENTS WITH COMPUTERIZED SELF-ADMINISTRATIVE ACTIVITY SURVEY
• INDUCTIVE LEARNING APPROACH TO EVOLUTIONARY DECISION PROCESSES IN ACTIVITY-SCHEDULING BEHAVIOR: THEORY AND NUMERICAL EXPERIMENTS
• MODELING AUTOMOBILE DEMAND AND DRIVER POPULATION IN PALESTINIAN TERRITORIES: SIMULTANEOUS-EQUATION ESTIMATION METHOD
• MODELING EFFECTS OF ANTICIPATED TIME PRESSURE ON EXECUTION OF ACTIVITY PROGRAMS
• MODELING ROUTE CHOICE BEHAVIOR WITH STOCHASTIC LEARNING AUTOMATA
• PATTERN RECOGNITION IN COMPLEX ACTIVITY TRAVEL PATTERNS: COMPARISON OF EUCLIDEAN DISTANCE, SIGNAL-PROCESSING THEORETICAL, AND MULTIDIMENSIONAL SEQUENCE ALIGNMENT METHODS
• REAL-TIME VARIABLE MESSAGE SIGN-BASED ROUTE GUIDANCE CONSISTENT WITH DRIVER BEHAVIOR
• SAMPLING ALTERNATIVES FROM COLOSSAL CHOICE SET: APPLICATION OF MARKOV CHAIN MONTE CARLO ALGORITHM
• STOCHASTIC USER EQUILIBRIUM FORMULATION FOR GENERALIZED NESTED LOGIT MODEL
• TELECOMMUTING IMPLICATIONS FOR TRAVEL BEHAVIOR: CASE STUDIES FROM MINNESOTA
• TIMETABLE-BASED TRANSIT ASSIGNMENT USING BRANCH AND BOUND TECHNIQUES
• TRAVEL BEHAVIOR IMPLICATIONS OF INFORMATION AND COMMUNICATIONS TECHNOLOGY IN PUGET SOUND REGION
• WITHIN-HOUSEHOLD ALLOCATION OF TRAVEL: CASE OF UPPER AUSTRIA