Urban rhythms and travel behaviour: spatial and temporal phenomena of daily travel
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Farnham [u.a.]
Ashgate
2010
|
| Series: | Transport and society
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. [197] - 220 |
| Physical Description: | XIV, 230 S. graph. Darst., Kt. 24 cm |
| ISBN: | 9780754675150 0754675157 |
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| adam_text | Titel: Urban rhythms and travel behaviour
Autor: Schönfelder, Stefan
Jahr: 2010
Contents
List of Figures vii
List of Tables xi
List of Abbreviations xiii
Notes on Authors xv
Acknowledgements xvii
1 Introduction 1
PART I FOUNDATIONS
2 Theoretical Framework 7
3 Definitions 19
4 Time, Space and Travel Analysis: An Overview 29
5 A Conceptual Model of Non-Response 49
6 The Multi-Day Data Sets Employed 57
PART II THE TEMPORAL ASPECTS OF DAY-TO-DAY
TRAVEL BEHAVIOUR
7 Current Patterns of Travel Behaviour 75
8 Scheduling 87
9 Modelling the Rhythms of Activity Demand:
An Explanatory Approach, Modelling Details and Results 93
vi Urban Rhythms and Travel Behaviour
PART III HUMAN SPATIAL BEHAVIOUR AND THE ANALYSIS
OF ACTIVITY SPACES
10 Destination Choice and Activity Spaces:
A Review of Concepts and a Framework for Analysis 117
11 Analysing Activity Space Using Longitudinal Data:
Methods and Results 129
PART TV CONCLUSIONS
12 Concluding Remarks 181
Appendix 191
Bibliography 197
Index 221
List of Figures
2.1 Conceptual model of the links between wages, degree of
specialization and activity space 9
2.2 Conceptual model between the cost of contact and the structure
and spatial dispersion of the social networks of the travellers 12
2.3 Conceptual model of variety seeking, social networks and personal
activity space 13
4.1 Activity and travel from the activity-based analysis standpoint 31
4.2 Variability in travel behaviour: Components 34
4.3 Time geography: Concept and application (right: example of a 3-D
space-time path) 39
4.4 Degree of spatial and temporal freedom in travel represented by a
prism and the impact of constraints on the space-time path 40
4.5 Human activity patterns in the city: Model of decision-making
processes 40
4.6 Socio-ecological model of space-time behaviour (basic approach) 41
5.1 Participation versus response burden in recent self-administrated
paper-and-pencil surveys 53
5.2 Web versus self-administered paper-and-pencil surveys 53
6.1 Schematic overview: Clustering observed trip ends (crosses) to
unique activity locations (boxes) 62
6.2 Sensitivity analysis of the Borlange GPS data: Effects of varying
clustering and cleaning thresholds for GPS data 63
7.1 Distribution of the number of trips per day 76
7.2 Distribution of the trip durations 77
7.3 Distribution of the trip distances 77
7.4 Mobility tool availability as function of gross monthly income 80
7.5 Number of trips by age and car availability (without immobiles) 82
7.6 Number of trips by age, sex and mobility tool availability (without
immobiles) 82
7.7 Number of trips by mode and mobility tool availability
(Switzerland) (without immobiles) 83
7.8 Modal shares by mobility tool availability (Switzerland) (without
immobiles) 83
viii Urban Rhythms and Travel Behaviour
8.1 The networked traveller in the dynamic social context 88
8.2 Modelling the individual s day-to-day dynamics 89
8.3 Modelling the individual s longer-term dynamics 90
8.4 Cumulative distribution of the planning horizons by scheduling
action 91
9.1 Time and the probability of trips to different activity locations 95
9.2 Periodicity in travel demand: An explanatory approach 95
9.3 Survival analysis: Functions 98
9.4 Possible shapes of hazard functions based on different
distributional assumptions for the baseline 100
9.5 Example of activity demand over time 103
9.6 Empirical survival and hazard rates based on life tables
(Mobidrive, Karlsmhe subsample) 108
10.1 Example of a space-time prism 122
10.2 Travel probability fields in the Nuremberg region 124
10.3 Daily potential path area (DPPA): Three-dimensional
representation and map 125
11.1 Exemplary list and graphical representation of destination choice
over six weeks of reporting (Thurgau survey): Destinations
according to coordinates, purpose and frequency of visits 130
11.2 Transforming an activity-point pattern into a continuous
representation of space usage 131
11.3 Measuring human activity space: Overview of methods 132
11.4 Human activity space over time by 95% confidence ellipses 135
11.5 Aggregate activity density patterns 13 6
11.6 Transformation of surfaces into raster grids (left) and GIS-based
density visualisation (here: rail accessibility in Switzerland, 1950) 136
11.7 The principle of kernel density estimation 13 8
11.8 Kernel density visualization example (Borlange GPS data):
Human activity space by days of the week 139
11.9 The minimum spanning tree of a planar graph 140
11.10 Visualization examples of shortest-path network measure
(Mobidrive) 141
11.11 Mean number of trips per week (based on unweighted samples):
Distributions by mode 143
11.12 Relationship between the number of trips and the number of
unique locations 145
11.13 Mean ratio of the number of trips and number of unique locations
over the course of the travel-diary survey periods 147
11.14 Mean shares of trips to the ten most-frequented locations
(excluding home) 148
List of Figures ix
11.15 Mean shares of trips to the ten most frequented locations
(excluding home): Distances and durations 150
11.16 Comparison of studies: Mean number of new locations per day of
survey (home excluded) 151
11.17 Mean number of previously unobserved locations per day and
mobile person, and share of actual visiting frequency: Thurgau
data 152
11.18 Innovation in location choice: Leisure study results 153
11.19 Individual characteristics of variety seeking in location choice:
Two examples (Thurgau sample) 154
11.20 Number of new , previously unobserved locations per monitoring
day, by week of monitoring (Atlanta survey) 154
11.21 Development of activity-space size: Average distances of locations
from home (Atlanta survey) 156
11.22 Distribution of activity-space sizes measured by confidence
ellipses: Histograms 161
11.23 Median confidence-ellipse size by purpose: Mobidrive and
Thurgau surveys 163
11.24 Enumeration and calculation of activity densities: Example 166
11.25 Distribution of activity-space sizes measured by kernel densities:
Cells with positive kernel densities and their distribution 168
11.26 Distribution of activity-space sizes measured by kernel densities:
Sum of kernel densities (volumes* 103) and their distribution 169
11.27 Activity space represented by kernel densities: Measures of
activity space versus number of trips, number of unique locations
visited, number of days and versus each other 169
11.28 Kernel densities by day of the week (Mobidrive) 170
11.29 Distribution of activity-space sizes measured by shortest-path
networks: Length of network used (km) 171
11.30 Shortest-path network measurement versus number of trips and
number of unique locations 171
11.31 Mean values of measurements by selected socio-economic groups
and day of the week (Mobidrive, Halle sub-sample) 173
List of Tables
3.1 Movement defined: English, German and French 20
3.2 Movement defined: An example day 25
3.3 Examples of possible survey object definitions 26
4.1 Selected studies on temporal aspects in individual
and household travel 32
4.2 Variety seeking: Motives 36
5.1 Underreporting of car driver trips: Comparison of travel diary
versus GPS traces 55
5.2 Underreporting in the Melbourne metropolitan VATS survey
1994-1996 (%) 55
6.1 Cross-sectional, time-series, and longitudinal data in comparison 57
6.2 Overview of the data sources 64
6.3 Selected comparative characteristics of the data sets (mobile days
only; GPS: after cleaning ) 65
6.4 Data-use and analysis concept 66
7.1 Mean characteristics of the trips 78
7.2 Trips by purpose and socio-economic status 79
7.3 Share of immobiles by socio-economic status 79
7.4 Mode shares by purpose and survey 84
8.1 Activities by planning horizon (%) 91
8.2 Activities by planning horizon and frequency of previous visit (%) 92
9.1 Characteristics of selected activity types (unweighted; Mobidrive:
main study, Thurgau: total sample) 106
9.2 Share of interval lengths between two activities of the same type in
days (unweighted; Mobidrive: MD, Thurgau: TH) (%) 107
9.3 Selected covariates: Means (Std.) 109
9.4 Exemplary ordered logit model results (Mobidrive) 110
9.5 Exemplary ordered logit model results (Thurgau) 111
9.6 Overview of covariate effects of the Han and Hausman model
(Mobidrive) 113
xii Urban Rhythms and Travel Behaviour
9.7 Overview of covariate effects of the Han and Hausman model
(Thurgau) 114
11.1 Enumeration approach: Indicators of destination choice over time 130
11.2 Trips per week (details for Figure 11.11) 142
11.3 Relationship between the number of trips and the number of
unique locations in all surveys (details for Figure 11.12) 144
11.4 Ratio between the number of unique places reported and the
number of trips made over the six-week reporting period: Out-of-
home travel only (Mobidrive [MD]/Thurgau [TH] surveys) 146
11.5 Five most important trip purposes by occupational status and
location (Thurgau) 149
11.6 Share of survey respondents with spatial clusters (%) 157
11.7 Internal structure of activity spaces: Activity-cluster cores 157
11.8 Activity demand in the vicinity of home and workplace
(maximum distance from location: 1,000 m; Mobidrive,
Karlsruhe sub-sample) 159
11.9 Pearson correlation coefficients between selected home-based
shopping opportunities and shopping-trip demand (Mobidrive,
Karlsruhe sub-sample) 160
11.10 Distribution of activity-space sizes measured by confidence
ellipses 162
11.11 Confidence ellipses: Basic characteristics and correlation with the
amount of travel 164
11.12 Correlation coefficients between selected activity-space
characteristics of two consecutive (three-week) subperiods in the
Borlange and Copenhagen surveys 165
11.13 Distribution of activity-space sizes measured by kernel densities 167
11.14 Distribution of activity-space sizes measured by shortest-path
networks (km) 172
11.15 GLM by data source, activity-space indicator and model: Variables 174
11.16 Summary of the GLM results by data source, activity-space
indicator and model: Significance levels 176
|
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| author | Schönfelder, Stefan Axhausen, Kay W. 1958- |
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| id | DE-604.BV036501450 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:41:45Z |
| institution | BVB |
| isbn | 9780754675150 0754675157 |
| language | English |
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| physical | XIV, 230 S. graph. Darst., Kt. 24 cm |
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| spelling | Schönfelder, Stefan Verfasser (DE-588)1162515953 aut Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel Stefan Schönfelder ; Kay W. Axhausen Farnham [u.a.] Ashgate 2010 XIV, 230 S. graph. Darst., Kt. 24 cm txt rdacontent n rdamedia nc rdacarrier Transport and society Literaturverz. S. [197] - 220 Verhalten (DE-588)4062860-7 gnd rswk-swf Verkehrsaufkommen (DE-588)4187799-8 gnd rswk-swf Verkehrsstatistik (DE-588)4204658-0 gnd rswk-swf Verkehrsteilnehmer (DE-588)4187838-3 gnd rswk-swf Stadt (DE-588)4056723-0 gnd rswk-swf Origin and destination traffic surveys. Travel--Statistics. Stadt (DE-588)4056723-0 s Verkehrsaufkommen (DE-588)4187799-8 s Verkehrsteilnehmer (DE-588)4187838-3 s Verhalten (DE-588)4062860-7 s Verkehrsstatistik (DE-588)4204658-0 s DE-604 Axhausen, Kay W. 1958- Verfasser (DE-588)112305938 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020423866&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schönfelder, Stefan Axhausen, Kay W. 1958- Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel Verhalten (DE-588)4062860-7 gnd Verkehrsaufkommen (DE-588)4187799-8 gnd Verkehrsstatistik (DE-588)4204658-0 gnd Verkehrsteilnehmer (DE-588)4187838-3 gnd Stadt (DE-588)4056723-0 gnd |
| subject_GND | (DE-588)4062860-7 (DE-588)4187799-8 (DE-588)4204658-0 (DE-588)4187838-3 (DE-588)4056723-0 |
| title | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel |
| title_auth | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel |
| title_exact_search | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel |
| title_full | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel Stefan Schönfelder ; Kay W. Axhausen |
| title_fullStr | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel Stefan Schönfelder ; Kay W. Axhausen |
| title_full_unstemmed | Urban rhythms and travel behaviour spatial and temporal phenomena of daily travel Stefan Schönfelder ; Kay W. Axhausen |
| title_short | Urban rhythms and travel behaviour |
| title_sort | urban rhythms and travel behaviour spatial and temporal phenomena of daily travel |
| title_sub | spatial and temporal phenomena of daily travel |
| topic | Verhalten (DE-588)4062860-7 gnd Verkehrsaufkommen (DE-588)4187799-8 gnd Verkehrsstatistik (DE-588)4204658-0 gnd Verkehrsteilnehmer (DE-588)4187838-3 gnd Stadt (DE-588)4056723-0 gnd |
| topic_facet | Verhalten Verkehrsaufkommen Verkehrsstatistik Verkehrsteilnehmer Stadt |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020423866&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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