Center for Activity Systems Analysis
Parent: UC Irvine Institute of Transportation Studies
eScholarship stats: Breakdown by Item for March through June, 2026
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 0r75311t | The Four Step Model | 955 | 189 | 766 | 19.8% |
| 7j0003j0 | The Four Step Model | 569 | 152 | 417 | 26.7% |
| 86h7f5v0 | The Activity-Based Approach | 393 | 89 | 304 | 22.6% |
| 354750t4 | Estimation of Vehicular Emissions by Capturing Traffic Variations | 208 | 74 | 134 | 35.6% |
| 9pk298qc | Measuring Physical Accessibility with Space-Time Prisms in a GIS: A Case Study of Access to Health-Care Facilities | 196 | 58 | 138 | 29.6% |
| 5cc9w7pp | Impact Of Real-World Driving Characteristics On Vehicular Emissions | 190 | 47 | 143 | 24.7% |
| 0j04f7gv | Land Use Influences on Trip Chaining in Portland, Oregon | 181 | 60 | 121 | 33.1% |
| 4nk4q801 | An Empirical Investigation of the Dynamic Processes on Activity Scheduling and Trip Chaining | 179 | 44 | 135 | 24.6% |
| 56t8j1n6 | Structural Equation Modeling for Travel Behavior Research | 177 | 58 | 119 | 32.8% |
| 08z0p3v3 | How Households Use Different Types of Vehicles: A Structural Driver Allocation and Usage Model | 172 | 47 | 125 | 27.3% |
| 9gn7265f | The Built Environment as a Determinant of Walking Behavior: Analyzing Non-Work Pedestrian Travel in Portland, Oregon | 153 | 56 | 97 | 36.6% |
| 06j9p6t3 | Consumer E-Commerce, Virtual Accessibility and Sustainable Transport | 151 | 44 | 107 | 29.1% |
| 0r28t441 | Toward Dynamic, Longitudinal, Agent-Based Microsimulation Models of Human Activity in Urban Settings | 150 | 57 | 93 | 38.0% |
| 5qq985sv | Does Neighborhood Design Influence Travel? A Behavioral Analysis of Travel Diary and GIS Data | 149 | 45 | 104 | 30.2% |
| 0xr3w1n5 | Putting Behavior in Household Travel Behavior Data: An Interactive GIS-Based Survey via the Internet | 146 | 60 | 86 | 41.1% |
| 4xf6r519 | Comparing the Influence of Land Use on Nonwork Trip Generation and Vehicle Distance Traveled: An Analysis using Travel Diary Data. | 144 | 56 | 88 | 38.9% |
| 951343hf | A Simultaneous Model of Household Activity Participation and Trip Chain Generation | 143 | 37 | 106 | 25.9% |
| 2496s5nm | Application of Space-Time Prisms for the Measurement of Accessibility | 138 | 36 | 102 | 26.1% |
| 15x0v29d | Evaluation of a Shared-Use Electric Vehicle Program: Integrating a Web-Based Survey with In-Vehicle Tracking | 129 | 57 | 72 | 44.2% |
| 7rb0h6gd | Why Do People Drive to Shop? Future Travel and Telecommunications Tradeoffs | 129 | 39 | 90 | 30.2% |
| 3826k93v | The Tracer Data Collection System: Implementation and Operational Experience | 126 | 36 | 90 | 28.6% |
| 4zv467qv | TRACER: In-Vehicle, GPS-Based Wireless Technology for Traffic Surveillance and Management. | 125 | 56 | 69 | 44.8% |
| 1596c2wb | An Activity-Based Microsimulation Model for Generating Synthetic Activity-Travel Patterns: Initial Results | 119 | 48 | 71 | 40.3% |
| 3bg4h82g | Can Land Use Policy Really Affect Travel Behavior? A Study of the Link between Non-Work Travel and Land Use Characteristics | 118 | 30 | 88 | 25.4% |
| 2js9554x | The Potential for Integrating GIS in Activity-Based Forecasting Models | 117 | 33 | 84 | 28.2% |
| 68t9d9m4 | An Assessment of the Interaction of the Land Use-Transportation System and Travel Behavior | 117 | 43 | 74 | 36.8% |
| 1mb5w3p2 | A Model of Activity Participation and Travel Interactions Between Household Heads | 116 | 58 | 58 | 50.0% |
| 3tm4q252 | A Latent Factor Model of Observed Activities | 115 | 37 | 78 | 32.2% |
| 9tc6f64c | Shopping without Travel or Travel without Shopping? An Investigation of Electronic Home Shopping | 115 | 43 | 72 | 37.4% |
| 0r21q5jw | iCHASE: An Internet Computerized Household Activity Scheduling Elicitor Survey | 114 | 36 | 78 | 31.6% |
| 9730g8tn | An Activity-Based Travel Pattern Generation Model | 114 | 33 | 81 | 28.9% |
| 5sv5v9qt | The Activity-Based Approach | 111 | 30 | 81 | 27.0% |
| 4z11d19q | An Activity-Based Microsimulation Model for Travel Demand Forecasting | 105 | 48 | 57 | 45.7% |
| 40w6z879 | The Design and Implementation of an On-Line Travel and Activity Survey | 102 | 37 | 65 | 36.3% |
| 62c2h8qr | Incorporating Yellow-Page Databases in GIS-Based Transportation Models | 102 | 28 | 74 | 27.5% |
| 6nb6d6wx | An Activity-Based Approach to Accessibility | 99 | 29 | 70 | 29.3% |
| 95p732sh | Measuring the Impact of Efficient Household Travel Decisions on Potential Travel Time Savings and Accessibility Gains | 99 | 32 | 67 | 32.3% |
| 3vv5s6jk | An Empirical Investigation of the Underlying Behavioral Processes of Trip Chaining | 98 | 20 | 78 | 20.4% |
| 8dp3172d | GPS/GIS Technologies for Traffic Surveillance and Management: A Testbed Implementation Study | 98 | 40 | 58 | 40.8% |
| 5nj1b37b | A Model of Household Demand for Activity Participation and Mobility | 97 | 29 | 68 | 29.9% |
| 3867z3s9 | A GPS Enhanced In-Vehicle Extensible Data Collection Unit | 95 | 34 | 61 | 35.8% |
| 9zd6c7dh | Land Use, Urban Design, and Non-Work Travel: Reproducing for Portland, Oregon, Empirical Tests from other Urban Areas | 94 | 25 | 69 | 26.6% |
| 7w59p200 | TravelBehavior.com: Activity Approaches to Modeling the Effects of Information Technology on Personal Travel | 90 | 26 | 64 | 28.9% |
| 8j85r8qm | The Household Activity Pattern Problem: General Formulation and Solution | 90 | 43 | 47 | 47.8% |
| 1vn7958m | On the Structure of Weekly Activity/Travel Patterns | 89 | 28 | 61 | 31.5% |
| 44h6f48x | A Bridge between Travel Demand Modeling and Activity-Based Travel Analysis | 89 | 44 | 45 | 49.4% |
| 5z12433b | Accessibility and Auto Use in a Motorized Metropolis | 89 | 22 | 67 | 24.7% |
| 7jm9c08m | New Highways, Urban Development and Induced Travel | 89 | 30 | 59 | 33.7% |
| 1zf82002 | Conducting an Interactive Survey of Household Weekly Activities via Internet: Preliminary Results from a Pilot Study | 88 | 43 | 45 | 48.9% |
| 47f366f3 | Experimenting with a Computerized Self-Administrative Survey: Evaluating a Pilot Study | 86 | 26 | 60 | 30.2% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.