scholarly journals PENGEMBANGAN MODEL TRANSPORTASI PENUMPANG ANTAR KOTA/KABUPATEN DI PROPINSI JAWA BARAT

2015 ◽  
Vol 1 (1) ◽  
pp. 77-94
Author(s):  
I Made Suraharta
Keyword(s):  
Transportation Planning ◽  
Travel Demand ◽  
Planning Process ◽  
Transport Model ◽  
Cost Model ◽  
Trip Generation ◽  
Demand Model ◽  
Demand Models ◽  
Distribution Mode ◽  
Generalized Cost

Transport models are crucial in the transportation planning process. Transport model is made by adjusting the needs and availability of data and capability models in representing the real conditions and the future. Transportation models commonly used in transportation planning mechanism is the sequential demand models, which include the trip generation, trip distribution, mode choice, and traffic assignment. This model is suitable to be applied to various situations study areas, especially areas of the city. For intercity regional planning needs, modeling the sequential demand can be simplified into a direct demand model, the record is not much involved in modeling mode. In this study, the authors tried to develop a model of a direct demand models to represent the pattern of movement of people with other modes of road in West Java. The proposed transport model is a function of population, GDP, total number of trip generation traffic zone, the total transportation costs (generalized cost). Model results show the validity of the development of significant and can be used as a travel demand model for transportation planning.

Proof-of-concept for methodological framework to evaluate operational strategies with travel demand models

2015 ◽  
Vol 42 (11) ◽  
pp. 854-864
Author(s):  
Jiaqi Ma ◽  
Changju Lee ◽  
Michael J. Demetsky
Keyword(s):  
Transportation Planning ◽  
Travel Demand ◽  
Planning Process ◽  
Methodological Framework ◽  
Demand Model ◽  
Peak Period ◽  
Operational Strategies ◽  
Operational Analysis ◽  
Starting Point ◽  
Demand Models

Recently, limited available resources for physical capacity expansion have generated supports for short-term operational improvements. Yet, only a few studies have dealt with evaluating these operational strategies effectively within the traditional transportation planning process even though suitable operational strategies impact to not only specific corridors or regions but also the whole transportation network. This is because it is generally perceived that integrating travel demand models with operational analysis approaches is quite difficult due to different constraints, modeling structures, and required data sets. In this regard, the concept of methodological framework to evaluate operational strategies with travel demand models is developed and validated by the proper case study (i.e., high occupancy toll lanes deployment in the Hampton Roads area in Virginia, US) in this research. The proposed framework consists of three major components: (i) the selection of an appropriate operational analysis approach, (ii) the disaggregation of daily traffic volumes to peak period volumes, and (iii) the alignment of modeling elements between the travel demand model and operational tool. Key contributions from this research are that (i) the proposed methodology enables the evaluation of travel behavioral changes without microscopic simulation, especially in terms of capturing network flow pattern changes caused by behavioral shifts after operational strategy deployment, (ii) the proposed framework eliminates assumptions required when only operational tools are used to evaluate operational strategies, (iii) the disaggregation method of a daily trip distribution matrix into peak period matrices by using survey data are developed, (iv) specific details influencing integration in terms of data types, peak period link capacity, volume-delay functions, and link impedance are identified. Consequently, even though this research still has some limitations (e.g., inherent weakness of travel demand models), this can be a starting point to develop more detailed guidelines as well as a good reference for practitioners and researchers who wish to evaluate operation strategies within transportation planning process.

Using Travel Demand Models and Pairwise Comparisons To Evaluate Alternative Transportation Networks in Niagara

1998 ◽  
Vol 1645 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Ali Mekky
Keyword(s):  
Travel Demand ◽  
Planning Process ◽  
Comprehensive Evaluation ◽  
Evaluation Methodology ◽  
Pairwise Comparisons ◽  
Demand Model ◽  
Socioeconomic Groups ◽  
Alternative Transportation ◽  
Demand Models ◽  
Structured Approach

Evaluating various alternative transportation proposals is one of the most important stages in the transportation planning process. It represents the culmination of various efforts of data collection, goals and objectives formulation, and demand modeling. Some major problems in comparing alternatives are that their effects usually are numerous, affecting various socioeconomic groups in different ways; some effects are quantifiable and others are not; and the scale and the units of each effect may be different from the others. The pairwise comparisons (PWC) method, used for a Niagara-area study, offers a structured approach to deal with this situation. The Niagara study covers a large part of the peninsula between Lake Ontario and Lake Erie. A travel demand model was calibrated and used to quantify network indicators. In the comprehensive evaluation, nonnetwork criteria also were used. The PWC evaluation methodology used in this study is discussed, along with the network and nonnetwork objectives, criteria, and measures. Sensitivity analysis on the ranking results is explained. Another method of obtaining the most reliable consensus of a group of experts is compared with the PWC method. The benefits of the PWC method and conclusions are given.

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.

scholarly journals From Macro to Microscopic Trip Generation: Representing Heterogeneous Travel Behavior

2017 ◽  
Vol 11 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Rolf Moeckel ◽  
Leta Huntsinger ◽  
Rick Donnelly
Keyword(s):  
Travel Behavior ◽  
Processing Time ◽  
Travel Demand ◽  
Computer Processing ◽  
Professional Judgment ◽  
Trip Generation ◽  
Household Type ◽  
Demand Models ◽  
Generation Mode ◽  
Definition Of

Background: In four-step travel demand models, average trip generation rates are traditionally applied to static household type definitions. In reality, however, trip generation is more heterogeneous with some households making no trips and other households making more than a dozen trips, even if they are of the same household type. Objective: This paper aims at improving trip-generation methods without jumping all the way to an activity-based model, which is a very costly form of modeling travel demand both in terms of development and computer processing time. Method: Two fundamental improvements in trip generation are presented in this paper. First, the definition of household types, which traditionally is based on professional judgment rather than science, is revised to optimally reflect trip generation differences between the household types. For this purpose, over 67 million definitions of household types were analyzed econometrically in a Big-Data exercise. Secondly, a microscopic trip generation module was developed that specifies trip generation individually for every household. Results: This new module allows representing the heterogeneity in trip generation found in reality, with the ability to maintain all household attributes for subsequent models. Even though the following steps in a trip-based model used in this research remained unchanged, the model was improved by using microscopic trip generation. Mode-specific constants were reduced by 9%, and the Root Mean Square Error of the assignment validation improved by 7%.

scholarly journals Addressing Household Income Distribution in Air Travel Demand Models: Case Study of the Baltimore–Washington Region

2019 ◽  
Vol 2673 (1) ◽  
pp. 491-502 ◽  
Author(s):  
Geoffrey D. Gosling ◽  
David Ballard
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Travel Demand ◽  
Metropolitan Region ◽  
Annual Data ◽  
Demand Model ◽  
Passenger Demand ◽  
Average Household Income ◽  
Demand Models ◽  
The Future

The paper describes the development of an air passenger demand model for the Baltimore–Washington metropolitan region that was undertaken as part of a recently concluded ACRP project that explored the use of disaggregated socioeconomic data in air passenger demand studies. The model incorporated a variable reflecting the change in household income distribution, together with more traditional aggregate causal variables: population, employment, average household income, and airfares as measured by the average U.S. airline yield, as well as several year-specific dummy variables. The model was estimated on annual data for the period 1990 to 2010 and obtained statistically significant estimated coefficients for all variables, including both the average household income and the household income distribution variable. Including household income distribution in the model resulted in a significant change to the estimated coefficient for average household income, giving a much higher estimated elasticity of demand with respect to average household income compared with a model that does not consider changes in household income distribution. This has important implications for the use of such demand models for forecasting, as household income distribution and average household income may change in the future in quite different ways, which would affect the future levels of air passenger travel projected by the models.

scholarly journals Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Rolf Moeckel ◽  
Nico Kuehnel ◽  
Carlos Llorca ◽  
Ana Tsui Moreno ◽  
Hema Rayaprolu
Keyword(s):  
Travel Demand ◽  
Time Budget ◽  
Time Of Day ◽  
Destination Choice ◽  
Trip Generation ◽  
Demand Model ◽  
Agent Based ◽  
Travel Mode Choice ◽  
Travel Time Budget ◽  
Aggregate Nature

The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.

Transferability of aggregate intercity total demand models

1995 ◽  
Vol 22 (2) ◽  
pp. 283-291
Author(s):  
Amal S. Kumarage ◽  
S. C. Wirasinghe
Keyword(s):  
Sri Lanka ◽  
Public Transportation ◽  
Travel Demand ◽  
Contextual Factors ◽  
Demand Model ◽  
Aggregate Model ◽  
Demand Models ◽  
Intercity Travel ◽  
Model Transfer ◽  
Contextual Characteristics

Over the last 15 years, extensive research has been done on the transferability of travel demand models. However, much of this work has been concentrated towards investigating the transferability of disaggregate mode choice models. The transferability of an aggregate total demand model for intercity travel is examined. Model transfer is possible only when a number of preconditions for transferability are satisfied. One of the principal obstacles to the successful transfer of intercity demand models is the inability to overcome the contextual differences between calibration and application. Here, the components of the intercity total demand model are separated into exogenous and intrinsic (contextual) factors. The latter is thereafter classified as being either transferable or nontransferable. It is shown that transferable attributes can accompany a model during transfer. Nontransferable attributes, on the other hand, will free the model of city or city-pair specific contextual characteristics which should not be transferred to other city pairs. The issues involved in transferring an aggregate model are also investigated. Aggregate data on interdistrict travel by public transportation in Sri Lanka have been used to successfully calibrate a total demand model with a number of transferable and nontransferable attributes that represent both temporal and spatial contextual factors. It is shown that the forecasting ability of this model is far superior to a counterpart model without the intrinsic variables. Key words: travel demand, aggregate, forecasting, transferability, intercity, Sri Lanka.

Nonresponse and Urban Travel Models

1996 ◽  
Vol 1551 (1) ◽  
pp. 82-87
Author(s):  
Piyushimita (Vonu) Thakuriah ◽  
Ashish Sen ◽  
Siim Sööt ◽  
Ed J. Christopher
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Travel Demand ◽  
Gravity Models ◽  
Parameter Estimates ◽  
Trip Generation ◽  
Urban Travel ◽  
Mode Split ◽  
Demand Models ◽  
Simulation Results

Considerable attention has been paid to the presence of nonresponse in large-scale travel surveys on the basis of which urban travel demand models are developed. It has been shown that the effect of nonresponse can be reduced by careful model building, with categorical trip generation models as an example. The same philosophy is extended to logit mode split models and exponential gravity models to show that the usual levels of nonresponse that one encounters in urban travel surveys have virtually no adverse effects on the parameter estimates of these models if the model has been specified correctly. Some simulation results are also presented to show the behavior of logit and exponential gravity model parameter estimates under conditions on nonresponse.

scholarly journals Method of Obtaining Consumer Welfare from Regional Travel Demand Models

1998 ◽  
Vol 1649 (1) ◽  
pp. 81-85 ◽  
Author(s):  
Caroline J. Rodier ◽  
Robert A. Johnston
Keyword(s):  
Travel Demand ◽  
Consumer Welfare ◽  
The United States ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Demand Model ◽  
Compensating Variation ◽  
Demand Models ◽  
High Occupancy Vehicle Lanes

The need for more comprehensive traveler welfare measures is highlighted by the U.S. Intermodal Surface Transportation Efficiency Act (1991) requirement that transportation projects and plans be evaluated for economic efficiency. However, to date, there has been a discrepancy between this requirement and the methods used by regional transportation organizations to evaluate transportation policies in the United States. Kenneth Small and Harvey Rosen illustrate how a consumer welfare measure known as compensating variation can be obtained from discrete choice models. A method of application is developed for the mode choice models in the Sacramento Regional Travel Demand Model. The results of the method’s application to the model for light rail transit, high-occupancy vehicle lanes, and auto pricing scenarios are examined for both total consumer welfare and consumer welfare by income class.

Sign in / Sign up

Export Citation Format

Share Document