00818742

Component

https://doi.org/10.3141/1752-13

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

The process of activity scheduling is crucial to the understanding of travel behavior changes. In-depth research is urgently needed to unearth this process. A new computer program, REACT!, was developed to collect household activity scheduling data for this purpose. The program is implemented as a stand-alone program with Internet connectivity for remote data transmission. It also contains a geographic information system for location identification and a special feature that traces the decisions in the scheduling process. A pilot study was conducted in Irvine, California, to evaluate the program's performance. Preliminary analysis validated the program's capability of guiding participants to complete data entry tasks on their own; thus, the objective of reducing the cost of human resources for such a computerized survey is achieved. Other positive results were obtained regarding the objectives of reducing instrumental biases and expanding program capabilities. Areas for improvement were identified in the pilot study. On the basis of the findings, REACT! represents an ideal platform for a computerized household survey that can produce data for activity-based travel models.

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

English

p. 91-99

2001

Transportation Research Record

0309072131

Figures (6) ; References (5) ; Tables (3)

Activity choices; Computer programs; Data collection; Geographic information systems; Households; Internet; Performance evaluations; Pilot studies; Travel behavior; Travel surveys

Activity scheduling; Computerized surveys

Irvine (California)

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

TRIS, TRB, ATRI

Oct 2 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
• 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