2013 Session: 829

• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Abstract: Recent travel demand modeling practices focus on micro, disaggregate, and activity level travel behavior and patterns. The application of such practices requires detailed population information in socio-economic and demographic data. For example, in a four-step travel demand model total household and employment at Traffic Analysis Zone (TAZ) level are sufficient for trip generation. However, in an activity based model more detailed information in the small area (TAZ), such as population by different age categories and employment type, is required to produce trip chaining and other details in the population synthesis step. Conventionally many studies have used Iterative Proportional Fitting (IPF) to generate such detailed information. But, IPF suffers from severe drawbacks and is blind to detailed synthesis of variables. In this paper, a novel approach is presented where population by age category evolves over time period using logistic regression technique. The methodology is presented in three steps: coefficient estimation, forecast and validation. First, the 1990 census data is used to model population by age group in 2000 at the TAZ level. The model result is applied to forecast 2010 data for validation. The methodology is applied to Baltimore Metropolitan Council (BMC) region and the results show that the proposed model produces and forecasts reasonably well. The experiences gained from this study are: (1) population evolution pattern in city area should be treated separately from other, e.g., Baltimore City has a special population structure from other surrounding counties; (2) this model provides a good estimation and prediction for the age group 0-24 and 35-64 and the problems occurs in 25-34 and 65+ groups, whose migration trend is not consistent over time and cannot be captured by the current parameters alone. Though in this paper population by age is considered for demonstration, the proposed methodology can be used for other variables of interest such as household type, householder’s age, employment type, occupation, etc. The proposed tool can be adapted by small and large scale planning agencies for preparing detailed socio economic and demographic input data for travel demand modeling practices.
  Authors: Zhu, Xiaoyu; Mishra, Sabyasachee; Welch, Timothy F.; Pandey, Birat; Baber, Charles
  Authors: Zhu, Xiaoyu; Mishra, Sabyasachee; Welch, Timothy F.; Pandey, Birat; Baber, Charles
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Investigating Microsimulation Error in Activity-Based Travel Demand Forecasting Using Confidence Intervals
  Abstract: Activity-based models of travel demand using micro-simulation approach inevitably include stochastic error that is caused by the statistical distributions of random components. As a result, running a traffic micro-simulation model several times with the same inputs will obtain different outputs. In order to take the variation of outputs in each model run into account, a common approach is to run the model multiple times and to use the average value of the results. The question then becomes: what is the minimum number of model runs required to reach a stable result (i.e., with a certain level of confidence that the obtained average value can only vary within an acceptable interval). In this study, systematic experiments are carried out by using the FEATHERS framework, an agent-based micro-simulation model particularly developed for Flanders, Belgium. Six levels of geographic detail are taken into account, which are Building block level, Subzone level, Zone level, Superzone level, Province level, and the whole Flanders. Three travel indices, i.e., the average daily number of trips per person, the average daily distance travelled per person, and the average daily number of activities per person, as well as their corresponding segmentations, are estimated by running the model 100 times. The results show that the more detailed geographical level is considered, the larger the number of model runs is needed to ensure confidence of a certain percentile of zones at this level to be stable. In addition, based on the time-dependent origin-destination table derived from the model output, traffic assignment is performed by loading it onto the Flemish road network, and the total vehicle kilometres travelled in the whole Flanders are computed subsequently. The stable results at the Flanders level provides model users with confidence that application of the FEATHERS at an aggregated level only requires limited model runs.
  Authors: Bao, Qiong; Kochan, Bruno; Bellemans, Tom; Janssens, Davy; Wets, Geert
  Authors: Bao, Qiong; Kochan, Bruno; Bellemans, Tom; Janssens, Davy; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2528
• Spatial Transferability of Person-Level Daily Activity Generation and Time-Use Models: Empirical Assessment
  Abstract: This paper presents an empirical assessment of the spatial transferability of person-level daily activity generation and time-use models among different regions in Florida and between Florida and California. The empirical models are for unemployed adults based on the multiple discrete-continuous extreme (MDCEV) structure. An examination of the prediction properties of the MDCEV model is provided first. The results shed new light on the prediction properties of the MDCEV model that have implications to transferability, as well as provide insights into how the model structure can potentially be improved. Transferability was evaluated for two approaches to transferring models – naïve transfer and updating model constants – using different measures such as log-likelihood based metrics, aggregate predictive ability, and model sensitivity to changes in demographic characteristics. Results suggest that accurate prediction of aggregate observed patterns is not an adequate yardstick to assess transferability; emphasis should be placed on model sensitivity to changes in explanatory variables. Updating constants helps in improving a transferred model’s aggregate prediction ability - thanks to the prediction properties of the MDCEV model - but not necessarily in improving its policy sensitivity. The extent of transferability between different regions within a state is greater than that across different states. Within Florida, there is greater transferability between urban regions (especially between Southeast Florida and Central Florida regions) than between urban and rural regions.
  Authors: Sikder, Sujan; Pinjari, Abdul Rawoof
  Authors: Sikder, Sujan; Pinjari, Abdul Rawoof
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-3944
• Multiple Discrete-Continuous Model of Activity Type Choice and Time Allocation for Home-Based Nonwork Tours
  Abstract: In the activity-based modeling arena, tour-based approaches to modeling travel demand have been implemented in practice in a number of geographical contexts. In the tour context, there are a number of choice dimensions wherein the choice of the alternatives and the amount to consume is made simultaneously. In particular, the choice of different activity types and the amount of time allocated to various activity types within a tour is considerable interest. The simulation of these choice processes must be done while also recognizing the dependencies and interactions across choice contexts within the tour. It is desirable to model the choice context of multiple discrete choices (activity types) and the associated continuous variable (time spent on the activity types) under a single unifying framework to accurately capture the interrelationships across the choice dimensions within a tour. Data from the latest wave of the NHTS is used to estimate a joint model of activity type choice and continuous time allocation using the multiple discrete-continuous extreme value model. In addition, history of activity participation is explicitly captured in the model specification as explanatory variables. Results from the empirical exercise provide plausible results and support the case for modeling these choice dimensions simultaneously to accurately capture the inter-relationship between activity type choice and activity time allocation. History of activity participation was found to be significant with notable trade-off and complementarity effects exhibited by individuals for selected non-work activity types.
  Authors: You, Daehyun; Garikapati, Venu M; Konduri, Karthik Charan; Pendyala, Ram M.; Vovsha, Peter; Livshits, Vladimir
  Authors: You, Daehyun; Garikapati, Venu M; Konduri, Karthik Charan; Pendyala, Ram M.; Vovsha, Peter; Livshits, Vladimir
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-5266
• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Authors: Zhu, Xiaoyu
  Authors: Zhu, Xiaoyu
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Authors: Mishra, Sabyasachee
  Authors: Mishra, Sabyasachee
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Authors: Welch, Timothy
  Authors: Welch, Timothy
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Authors: Pandey, Birat
  Authors: Pandey, Birat
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Investigating Microsimulation Error in Activity-Based Travel Demand Forecasting Using Confidence Intervals
  Authors: Bellemans, Tom
  Authors: Bellemans, Tom
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2528
• Framework for Modeling and Forecasting Population Age Distribution in Metropolitan Areas at Level of Transportation Analysis Zone
  Authors: Baber, Charles
  Authors: Baber, Charles
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-2158
• Spatial Transferability of Person-Level Daily Activity Generation and Time-Use Models: Empirical Assessment
  Authors: Sikder, Sujan
  Authors: Sikder, Sujan
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-3944
• Multiple Discrete-Continuous Model of Activity Type Choice and Time Allocation for Home-Based Nonwork Tours
  Authors: Garikapati, Venu
  Authors: Garikapati, Venu
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 829
  Paper Number: 13-5266