Toward the Understanding of Urban Travel Behavior Through the Classification of Daily Urban Travel/activity Patterns |
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Page 5
... transportation energy usage will become increasingly important . However , the various complexities of travel behavior discussed above should be taken into account , in order to obtain such estimates . Transportation planners and ...
... transportation energy usage will become increasingly important . However , the various complexities of travel behavior discussed above should be taken into account , in order to obtain such estimates . Transportation planners and ...
Page 224
... Transportation , 1972 . Charles River Associates . Review and Implications of the Life Cycle , Lifestyle and Role Literature for Transportation Planning . Paper prepared for the National Cooperative Highway Research Program Project 8-14 ...
... Transportation , 1972 . Charles River Associates . Review and Implications of the Life Cycle , Lifestyle and Role Literature for Transportation Planning . Paper prepared for the National Cooperative Highway Research Program Project 8-14 ...
Page 227
... Transportation Science , 1 ( November , 1967 ) , pp . 261-285 . Keck , C. A. Effects of the Energy Shortage on Reported Household Travel Behavior Patterns in Small Urban Areas . Preliminary Research Report 67 , Department of Transportation ...
... Transportation Science , 1 ( November , 1967 ) , pp . 261-285 . Keck , C. A. Effects of the Energy Shortage on Reported Household Travel Behavior Patterns in Small Urban Areas . Preliminary Research Report 67 , Department of Transportation ...
Common terms and phrases
activity behavior activity patterns Activityd analyzed approach Burnett and Hanson Chapter Charles River Associates classes of daily classification cluster centroids conceptual framework considered contingency table daily travel daily travel/activity behavior daily travel/activity patterns defined described differential weighting eigenroots eigenvectors employed employment status equation examined explanatory variables Figure gender group of representative home-based household hypothesized identified individual information explained inter-object linear logit model linkages log-linear model mean square difference measure method of principal mode mode choice multinomial logit number of clusters number of groups number of stops objects obtained parameters positive semi-definite primary sample real Euclidean space relationships response variable results reported roles root mean square secondary attributes secondary sample selected sequence set of travel/activity similarity index similarity matrix single representative pattern small number socio-demographic characteristics step sum of squares Table traffic analysis zone travel patterns travel/activity pattern types trip urban travel behavior urban travel demand Ward's algorithm Σ Σ