scholarly journals Modeling Activity-Time to Build Realistic Plannings in Population Synthesis in a Suburban Area

2021 ◽  
Vol 11 (16) ◽  
pp. 7654
Author(s):  
Younes Delhoum ◽  
Rachid Belaroussi ◽  
Francis Dupin ◽  
Mahdi Zargayouna
Keyword(s):  
Choice Model ◽  
Time Of Day ◽  
Suburban Area ◽  
Population Synthesis ◽  
Activity Time ◽  
Or Education ◽  
Time To Build ◽  
Home Based ◽  
Demand Models ◽  
Activity Choices

In their daily activity planning, travelers always considers time and space constraints such as working or education hours and distances to facilities that can restrict the location and time-of-day choices of other activities. In the field of population synthesis, current demand models lack dynamic consistency and often fail to capture the angle of activity choices at different times of the day. This article presents a method for synthetic population generation with a focus on activity-time choice. Activity-time choice consists mainly in the activity’s starting time and its duration, and we consider daily planning with some mandatory home-based activity: the chain of other subsequent activities a traveler can participate in depends on their possible end-time and duration as well as the travel distance from one another and opening hours of commodities. We are interested in a suburban area with sparse data available on population, where a discrete choice model based on utilities cannot be implemented due to the lack of microeconomic data. Our method applies activity-hours distributions extracted from the public census, with a limited corpus, to draw the time of a potential next activity based on the end-time of the previous one, predicted travel times, and the successor activities the agent wants to participate in during the day. We show that our method is able to construct plannings for 126k agents over five municipalities, with chains of activity made of work, education, shopping, leisure, restaurant and kindergarten, which fit adequately real-world time distributions.

Analyzing Cell Phone Location Data for Urban Travel

2015 ◽  
Vol 2526 (1) ◽  
pp. 126-135 ◽  
Author(s):  
Serdar Çolak ◽  
Lauren P. Alexander ◽  
Bernardo G. Alvim ◽  
Shomik R. Mehndiratta ◽  
Marta C. González
Keyword(s):  
Travel Behavior ◽  
Rio De Janeiro ◽  
Cell Phone ◽  
Travel Demand ◽  
Census Data ◽  
Low Cost ◽  
Time Of Day ◽  
Raw Data ◽  
Home Based ◽  
Demand Models

Travelers today use technology that generates vast amounts of data at low cost. These data could supplement most outputs of regional travel demand models. New analysis tools could change how data and modeling are used in the assessment of travel demand. Recent work has shown how processed origin–destination trips, as developed by trip data providers, support travel analysis. Much less has been reported on how raw data from telecommunication providers can be processed to support such an analysis or to what extent the raw data can be treated to extract travel behavior. This paper discusses how cell phone data can be processed to inform a four-step transportation model, with a focus on the limitations and opportunities of such data. The illustrated data treatment approach uses only phone data and population density to generate trip matrices in two metropolitan areas: Boston, Massachusetts, and Rio de Janeiro, Brazil. How to label zones as home- and work-based according to frequency and time of day is detailed. By using the labels (home, work, or other) of consecutive stays, one can assign purposes to trips such as home-based work. The resulting trip pairs are expanded for the total population from census data. Comparable results with existing information reported in local surveys in Boston and existing origin–destination matrices in Rio de Janeiro are shown. The results detail a method for use of passively generated cellular data as a low-cost option for transportation planning.

Regional Bicycle Network Evaluation and Strategic Planning: A Quantitative Methodological Approach Despite Limited Data Sources for Cycling

2021 ◽  
pp. 036119812110288
Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf
Keyword(s):  
Travel Demand ◽  
Choice Model ◽  
Methodological Approach ◽  
Data Availability ◽  
Data Sources ◽  
Test Case ◽  
Demand Model ◽  
Limited Data ◽  
Demand Models ◽  
Bicycle Infrastructure

In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.

Improved Modeling of Non-Home-Based Trips

1996 ◽  
Vol 1556 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Gordon W. Schultz ◽  
William G. Allen
Keyword(s):  
Detailed Analysis ◽  
Urban Areas ◽  
Mode Choice ◽  
Time Of Day ◽  
Place Of Residence ◽  
Trip Length ◽  
Trip Purpose ◽  
Trip Chaining ◽  
Home Based ◽  
A Chain

Non-home-based (NHB) trip making typically accounts for about 25 to 30 percent of travel by individuals in urban areas. However, the NHB trip purpose is usually treated as a large unknown category, and little attention is paid to the nature of these trips. An effort to better understand the characteristics of NHB trips by subdividing the NHB trip category is described. It is hoped that this effort will serve as a useful precursor to improving the analysis of trip chaining behavior. By definition, NHB trips are almost always part of a chain of trips that usually starts or ends at the trip maker's place of residence or work. By examining this chain more closely, it is possible to group NHB trips into two or three categories. More detailed analysis of these categories reveals that they have very different trip length, mode choice, and time of day characteristics. Making this subdivision improves the accuracy of the model, increases the sensitivity of the forecast to important factors, and provides a greater understanding of trip chaining behavior.

Traveler Destination Choice Behavior: Effects of Time of Day, Activity Duration, and Home Location

1998 ◽  
Vol 1645 (1) ◽  
pp. 76-81 ◽  
Author(s):  
Ryuichi Kitamura ◽  
Cynthia Chen ◽  
Ravi Narayanan
Keyword(s):  
Strong Evidence ◽  
Choice Behavior ◽  
Multinomial Logit ◽  
Time Of Day ◽  
Destination Choice ◽  
Duration Of Stay ◽  
Home Location ◽  
Activity Duration ◽  
Home Based ◽  
Statistical Results

Multinomial logit destination choice models are developed and the following hypotheses are examined: ( a) time of day affects destination choice behavior, ( b) the duration of stay at the destination affects destination choice, and ( c) home location affects non-home-based destination choice. The statistical results offer strong evidence in support of the hypotheses.

Multinomial Probit with Structured Covariance for Choice Situations with Similar Alternatives

1998 ◽  
Vol 1645 (1) ◽  
pp. 69-75
Author(s):  
Tetsuo Yai ◽  
Tetsuo Shimizu
Keyword(s):  
Empirical Study ◽  
Utility Function ◽  
Survey Data ◽  
Error Term ◽  
Choice Model ◽  
Time Of Day ◽  
Metropolitan Region ◽  
Multinomial Probit ◽  
Time Length ◽  
Mode Choice Model

The estimatability of the multinomial probit (MNP) model has been improved greatly by the modeling of the error structure. A modeling idea for travelers’ choice behaviors using the MNP with structured covariances (MNPSC) model is proposed. Choice of route, destination, and time of day are considered. The covariance of the error term of the utility function is structured by introducing the overlapped length between any two routes and the overlapped time length between any two departure times. Simultaneous models such as route and train class, route and mode, and time of day and mode choice model also are introduced by applying the MNPSC modeling idea. These are formulated easily by assuming that the error is generated independently between two choices. An empirical study for a route and train class choice model was conducted by using the passenger survey data in the Tokyo metropolitan region, and its estimatability and applicability are examined.

Travel Demand Modeling and Conformity Determination: Atlanta Regional Commission Case Study

2002 ◽  
Vol 1817 (1) ◽  
pp. 172-176 ◽  
Author(s):  
Guy Rousseau ◽  
Tracy Clymer
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Mode Choice ◽  
Time Of Day ◽  
Traffic Model ◽  
Demand Model ◽  
Primary Input ◽  
Land Use Model ◽  
Home Based ◽  
Travel Demand Model

The Atlanta Regional Commission (ARC) regional travel demand model is described as it relates to its link-based emissions postprocessor. In addition to conformity determination, an overview of other elements is given. The transit networks include the walk and highway access links. Trip generation addresses trip production, trip attraction, reconciliation of productions and attractions, and special adjustments made for Hartsfield Atlanta International Airport. Trip distribution includes the application of the composite impedance variable. In the mode choice model, home-based work uses a logit function, whereas nonwork uses information from the home-based work to estimate modal shares. Traffic assignment includes preparation of time-of-day assignments. The model assigns single-occupancy vehicles, high-occupancy vehicles, and trucks by using separate trip tables. The procedures can accept or prohibit each of the three types of vehicles from each highway lane. Feedback between the land use model and the traffic model is accounted for via composite impedances generated by the traffic model and is a primary input to the land use model DRAM/EMPAL. The land use model is based on census tract geography, whereas the travel demand model is based on traffic analysis zones that are subareas within census tracts. The ARC model has extended the state of the practice by using the log sum variable from mode choice as the impedance measure rather than the standard highway time. This change means that the model is sensitive not only to highway travel time but also to highway and transit costs.

Analysis of Travel Time Saving Benefit by Understanding Individual Needs and Value of Activity Time: Case Study of Tokyo and Jakarta

2003 ◽  
Vol 1854 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Irwan Prasetyo ◽  
Daisuke Fukuda ◽  
Hirosato Yoshino ◽  
Tetsuo Yai
Keyword(s):  
Travel Time ◽  
Time Allocation ◽  
Choice Model ◽  
Stated Preference ◽  
Revealed Preference ◽  
Psychological Needs ◽  
Activity Time ◽  
Time Saving ◽  
Allocation Model ◽  
Preference Data

Quantification of the value of time (VOT) is important for measurement of the benefit of transportation projects in terms of travel time savings. In Japan, VOT is considered higher on weekends than on weekdays because on the weekend people have limited time to allocate to discretionary activities that are not normally done on weekdays, such as family care-related activities. In Indonesia, a culturally diverse country, providers and users seem to have different perceptions of VOT. A method of analyzing the value of activity time is presented. It argues that the benefit of travel time saving should be evaluated in more detail on weekends by considering the value of discretionary activities to explain these phenomena theoretically. Activity diary surveys were conducted in Tokyo, Japan, and Jakarta, Indonesia, to verify the influence of psychological needs on people's holiday activities. Finally, a time allocation model that uses the revealed preference data and a marginal activity choice model that uses stated preference data are proposed to calculate the value of activity time. The theories underpinning these models are Maslow's psychological needs, consumer theory in economics, and a discrete choice model. The empirical results show that an individual's priority of needs influences time allocation. In particular, the results show that in Tokyo, spending time with family on weekends is more valuable than other types of activities, while in Indonesia the value of spending time with family exceeds that of work time even on weekdays.

The Effect of Site Congestion on Valuing Freshwater Fishing for Urban Residents

2019 ◽  
Vol 06 (04) ◽  
pp. 1950008 ◽  
Author(s):  
Richard T. Melstrom ◽  
Taylor Welniak
Keyword(s):  
Instrumental Variables ◽  
Choice Model ◽  
Revealed Preference ◽  
Recreation Demand ◽  
Oklahoma City ◽  
Weight Of Evidence ◽  
Urban Residents ◽  
Demand Models ◽  
A Site ◽  
Congestion Effects

This paper provides evidence that welfare estimates from recreation demand models can be severely biased if the model omits congestion effects. Congestion effects arise when crowding at popular sites lowers site values. Measuring the effect of congestion is complicated by a well-known endogeneity problem in revealed preference data. We study congestion effects in a sample of licensed anglers in Oklahoma City. We develop a site choice model of freshwater fishing, and correct for endogenous congestion using an instrumental variables strategy. Our results add to the growing weight of evidence that ignoring congestion leads to estimates that understate the value of individual sites and site amenities.

Understanding the Potential of Variable Tolling to Smooth Congestion on Downstream Facilities: Applications of a Joint Time-of-Day and Route Choice Model

2016 ◽  
Vol 2563 (1) ◽  
pp. 29-39
Author(s):  
Gregory D. Erhardt ◽  
Sunil Patil ◽  
Thomas Light ◽  
Flavia Tsang ◽  
Peter Burge ◽  
...  
Keyword(s):  
Choice Model ◽  
Route Choice ◽  
Time Of Day

Crossing the Line: Direct Estimation of Cross-Border Cigarette Sales and the Effect on Tax Revenue

2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Lesley Chiou ◽  
Erich Muehlegger
Keyword(s):  
Choice Model ◽  
Policy Issue ◽  
Tax Avoidance ◽  
Border Crossing ◽  
Tax Revenue ◽  
Excise Tax ◽  
Excise Taxes ◽  
Cross Border ◽  
Public Policy Issue ◽  
Demand Models

Abstract Differences in excise taxes across jurisdictions create incentives for consumers to cross the border and to purchase in lower-tax jurisdictions. This paper introduces a discrete choice model to examine tax avoidance and state border crossing in the market for cigarettes. We exploit a rich dataset of consumer location choices and demographics to estimate a consumer's tradeoff between distance and price when choosing a location to maximize utility. Using the estimates from our location and demand models, we reconsider a recent public policy issue among states and simulate tax avoidance under alternative cigarette excise tax levels.

Sign in / Sign up

Export Citation Format

Share Document