00818734

Component

https://doi.org/10.3141/1752-05

http://scholar.google.com...mans&publication_year=2001

Activity-based analysis in transportation demand forecasting is one of the most promising approaches in current transportation modeling. Travel decisions are understood as the outcome of underlying scheduling activity, resulting in large-scale interviews generating a large amount of data. Traditional techniques have been shown to be inefficient in describing the dependencies between different attributes if data sets are too large. Associations between data set attributes are described by means of association rules. The discussion outlines the description of activity-based transportation data sets through association rules for identification of spatial-temporal patterns in multiday activity diary data.

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

English

p. 32-37

2001

Transportation Research Record

0309072131

Figures (4) ; References (21) ; Tables (6)

Activity choices; Operating rules; Sets; Travel diaries

Spatial-temporal patterns

Highways; Planning and Forecasting; Public Transportation; Railroads; 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
• 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
• MULTILEVEL ANALYSIS OF ACTIVITY AND TRAVEL PATTERNS: ACCOUNTING FOR PERSON- AND HOUSEHOLD-SPECIFIC OBSERVED AND UNOBSERVED EFFECTS SIMULTANEOUSLY
• 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