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.

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.

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.

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 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.

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.

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.

Statewide Assessment of Broader Economic Benefits from Transportation Investment: Integration of Travel Demand Models and SHRP 2 Project C11 Tools in Maryland

2015 ◽  
Vol 2531 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Eirini Kastrouni ◽  
Elham Shayanfar ◽  
Paul M. Schonfeld ◽  
Subrat Mahapatra ◽  
Lei Zhang
Keyword(s):  
Travel Demand ◽  
Public Investment ◽  
Economic Benefits ◽  
Federal State ◽  
Travel Time Reliability ◽  
Demand Model ◽  
Investment Projects ◽  
Demand Models ◽  
State And Local ◽  
Local Agencies

Project selection and prioritization are of utmost importance to federal, state, and local agencies and should be performed cautiously on the basis of expected project costs and benefits. Informed resource allocation decisions with respect to project candidates not only maximize public investment benefits but create economic opportunities and ultimately improve quality of life. With the use of tools readily available to most state agencies (e.g., travel demand models), along with the open-source SHRP 2 Project C11 tools, planners and engineers can proceed with informed statewide assessments of investment projects that yield benefits in market accessibility, travel time reliability, and connectivity. In this study, a seven-level framework was proposed to integrate a travel demand model with the SHRP 2 Project C11 tools and to showcase its functionality with the Intercounty Connector (ICC) MD-200 in Maryland as a case study. After a customized version of the SHRP 2 tools was developed in which Maryland-specific values were used in lieu of the default SHRP 2 parameters, the results suggested that, in the year 2030, a total increase of approximately 1% in buyer–supplier market accessibility would be achieved in the counties that surrounded the ICC as a result of the new construction. Also, all three corridors parallel to the ICC, which served similar origin–destination pairs, would experience a decrease in recurring and incident delays attributable to the ICC. In dollar terms, the value of the total annual benefits from the ICC construction in the year 2030 would amount to approximately $200 million.

Updating of parameters in aggregate total demand models

1992 ◽  
Vol 19 (2) ◽  
pp. 236-244
Author(s):  
A. S. Kumarage ◽  
S. C. Wirasinghe
Keyword(s):  
Sri Lanka ◽  
Travel Demand ◽  
Model Updating ◽  
Common Factor ◽  
Parameter Estimates ◽  
Calibration Model ◽  
Demand Model ◽  
Demand Models ◽  
Sample Data ◽  
Model Transfer

Research on demand-model transferability has consistently shown that the updated models perform better than the simple transfer of the original model with the original coefficients. Several methods are available for the updating of parameter estimates during model transfer. The scalar factor method has been extended to specify individual factors for each variable. This method allows the flexibility of removing insignificant variables in transfer; it also permits the grouping of parameters that have to be updated by a common factor. Individual scalar factors can also be identified for variables that are uniquely affected during transfer. This approach therefore incorporates the strength of both the sample data and the calibration model to its maximum showing that this method gives excellent fit to observed flows when tested for geographical transferability of an aggregate intercity total demand model for public transport in Sri Lanka. It is also shown that the Bayesian method becomes less efficient when sample sizes available for updating become smaller. Key words: travel, demand model, updating, transferability, Sri Lanka.

scholarly journals Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results

2021 ◽  
Author(s):  
Jörg Sonnleitner ◽  
Markus Friedrich ◽  
Emely Richter
Keyword(s):  
First Generation ◽  
Travel Demand ◽  
Demand Model ◽  
Automated Vehicles ◽  
Modal Shift ◽  
Macroscopic Modeling ◽  
Driving Time ◽  
Demand Models ◽  
Step Algorithm ◽  
Demand Changes

AbstractAutomated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific passenger car unit factors that depend on roadway type and the capabilities of the vehicles. The second extension enables travel demand models to calculate demand changes caused by a different perception of travel time as the active driving time is reduced. The presented methods are applied to a use case of a regional macroscopic travel demand model. The basic assumption is that AV are considered highly but not fully automated and still require a driver for parts of the trip. Model results indicate that first-generation AV, probably being rather cautious, may decrease traffic performance. Further developed AV will improve performance on some parts of the network. Together with a reduction in active driving time, cars will become even more attractive, resulting in a modal shift towards car. Both circumstances lead to an increase in time spent and distance traveled.

scholarly journals Generating activity based, multi-modal travel demand for SUMO

10.29007/794z ◽  
2018 ◽  
Author(s):  
Joerg Schweizer ◽  
Federico Rupi ◽  
Francesco Filippi ◽  
Cristian Poliziani
Keyword(s):  
Travel Demand ◽  
Travel Times ◽  
Demand Model ◽  
Efficient Manner ◽  
Plan Generation ◽  
Mobility Strategies ◽  
Demand Models ◽  
Plan Selection ◽  
Selection Step ◽  
Frame Work

This article explains a travel demand generator developed within the SUMOPy frame- work which aims at providing person-based plans for the SUMO micro-simulator. The plan generation has four principal steps: 1.) a population needs to be generated, with specific attributes for each person; 2.) activities and their associated locations need to be identified, 3.) travel plans need to be generated, with the aim to connect the various activities in an efficient manner. 4.) A microsimulator determines the effective travel times for each plan which persons can use to modify or change their plan. In a first part, this article briefly describes other software packages which allow activity based demand models. It is further explained that the use of SUMO as microsimulator is particularly suited to evaluate multi-modal travel plans.The article then focuses on SUMOPy’s activity based demand model and in particular on the population synthesizer, plan generation and plan selection step. SUMOPy’s activity based demand framework has two distinguishing features: 1.) the time travel budget can be controlled during the population synthesizing process; 2.) The concept of abstract mobility strategies – each person may have different feasible plans, following different mobility strategies. The SUMO micro-simulator is used to evaluate the effective travel time of plans for the entire population. Regarding the plan selection method, a method is described if and how persons change plans based on the the effective travel times experienced after each simulation run. It is shown by means of a synthetic network and a realistic city network that the proposed algorithm is converging and total travel times are decreasing after each simulation run until an equilibrium is reached. Some preliminary attempts were undertaken to improve the speed of convergence. For both of the analyzed networks an equilibrium has been reached after approximately 10 simulation runs.

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