Peer Review: The Volpe/Federal Highway Administration National Vehicle Miles Traveled Forecasting Models

2021 ◽  
pp. 036119812110119
Author(s):  
Jeffrey Cohen ◽  
Sharada Vadali ◽  
Michael F. Lawrence ◽  
Shikha Dave ◽  
Clayton Clark
Keyword(s):  
Peer Review ◽  
Travel Demand ◽  
Variable Coefficients ◽  
Transportation Systems ◽  
Vehicle Miles Traveled ◽  
Modeling Tools ◽  
Forecasting Models ◽  
Distributed Lag ◽  
Study Team ◽  
Light Duty Vehicle

This paper describes the findings of an independent peer review of the modeling tools used by the Volpe National Transportation Systems Center to forecast national vehicle miles traveled (VMT) over the next 30 years. Overall, the VMT forecasting models, which use autoregressive distributed lag models for light-duty vehicle, single-unit truck, and combination truck VMT, work well to estimate travel demand. All model estimations were reviewed, and all models perform well against several validation and testing techniques. The study team was supported by an expert panel selected from academia, government, and industry with experience in econometric methods, transportation and economic data, and modeling methods. The panel reviewed model documentation as well as the report assessing the VMT forecasting models and provided insight into alternative model research. The paper is an effort to synthesize the approaches and the validation methods used. A complementary literature search was also conducted to test the validity and comparability of several estimated variable coefficients. The paper concludes by summarizing the key findings and making recommendations on future model improvements.

Exploratory Modeling and Analysis for Transportation: An Approach and Support Tool - TMIP-EMAT

2019 ◽  
Vol 2673 (9) ◽  
pp. 407-418 ◽  
Author(s):  
Martin Milkovits ◽  
Rachel Copperman ◽  
Jeffrey Newman ◽  
Jason Lemp ◽  
Thomas Rossi ◽  
...  
Keyword(s):  
Travel Demand ◽  
Supply And Demand ◽  
Single Point ◽  
Transportation Systems ◽  
Analysis Tool ◽  
Demand Model ◽  
Improvement Program ◽  
Modeling And Analysis ◽  
Forecasting Models ◽  
Travel Forecasting

Traditionally, travel forecasting models have been used to provide single point predictions. That is, a single future scenario is developed and the model is applied to that scenario. This approach, however, ignores the deep uncertainty that exists in future land use, demographic, and transportation systems inputs, not to mention the uncertainty that exists in the model itself. More importantly, transportation policy decisions made on the basis of such model outputs may be misguided and ineffective. This paper demonstrates and motivates the use of travel forecasting models in an exploratory manner that accounts for the inherent uncertainties of the future. Specifically, this paper describes the user workflow for a new planning and modeling tool: the Travel Model Improvement Program Exploratory Modeling and Analysis Tool (TMIP-EMAT) that has been developed to facilitate the use of exploratory techniques with travel forecasting models. Examples from the proof of concept deployment using the Greater Buffalo-Niagara Regional Transportation Council regional travel demand model are included. The goal of the longer term study is to provide TMIP-EMAT for state and regional transportation planning agencies to assess how technological innovations will affect traffic and transit demand on major corridors 20 to 30 years down the road. The tool will illuminate interactions between transportation supply and demand on urban surface transportation systems (especially at the corridor level) through exploratory modeling and simulation, and facilitate insights into potential, possible, plausible, probable or preferred futures.

scholarly journals Model Contrast of Autonomous Vehicle Impacts on Traffic

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Derek Hungness ◽  
Raj Bridgelall
Keyword(s):  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Sociodemographic Factors ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Traffic Conditions ◽  
Demand Models ◽  
Wide Range ◽  
Potential Benefits

The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel demand models to forecast future traffic conditions. However, such models do not yet integrate any expected impacts from CAV deployments. Consequently, many long-range transportation plans do not yet account for their eventual deployment. To address some of these uncertainties, this work modified an existing model for Madison, Wisconsin. To compare outcomes, the authors used identical parameter changes and simulation scenarios for a model of Gainesville, Florida. Both models show that with increasing levels of CAV deployment, both the vehicle miles traveled and the average congestion speed will increase. However, there are some important exceptions due to differences in the road network layout, geospatial features, sociodemographic factors, land-use, and access to transit.

scholarly journals High Emitter Light Duty Vehicle Contributions to On-road Mobile Emissions in 2018 and 2030

2015 ◽  
Vol 2 (1) ◽  
pp. 47 ◽  
Author(s):  
Susan Collet ◽  
Toru Kidokoro ◽  
Yukio Kinugasa ◽  
Prakash Karamchandani ◽  
Allison DenBleyker
Keyword(s):  
Air Quality ◽  
Environmental Protection Agency ◽  
Protection Agency ◽  
Vehicle Miles Traveled ◽  
Improvement Strategy ◽  
Quality Improvement Strategy ◽  
Light Duty ◽  
Air Quality Improvement ◽  
Light Duty Vehicle ◽  
Tier 3

Quantifying the proportion of normal- and high-emitting vehicles and their emissions is vital for creating an air quality improvement strategy for emission reduction policies. This paper includes the California LEV III and United States Environmental Protection Agency Tier 3 vehicle regulations in this projection of high emitter quantification for 2018 and 2030. Results show high emitting vehicles account for up to 6% of vehicle population and vehicle miles traveled. Yet, they will contribute to over 75% of exhaust and 66% of evaporative emissions. As these high emitting vehicles are gradually retired from service and are removed from the roads, the overall effect on air quality from vehicle emissions will be reduced.

Effects of Traffic Congestion on Vehicle Miles Traveled

2018 ◽  
Vol 2672 (47) ◽  
pp. 92-102 ◽  
Author(s):  
Reza Sardari ◽  
Shima Hamidi ◽  
Raha Pouladi
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Structural Equation ◽  
National Level ◽  
Network Connectivity ◽  
Transportation Systems ◽  
Equation Modeling ◽  
Population Mobility ◽  
Vehicle Miles Traveled ◽  
Land Use Patterns

The effects of traffic congestion on travel behavior are complex and multidimensional because they are related to various factors such as density, land use patterns, network connectivity, and individual preferences. Traffic congestion is a phenomenon that not only affects transportation systems but also influences commuters’ quality of life and population mobility. The present research aims to analyze the effects of traffic congestion on individuals’ travel behaviors, addressing both direct and indirect effects of congestion on vehicle miles traveled (VMT) per driver by implementing structural equation modeling (SEM) techniques. In addition to the causal analysis between traffic congestion and VMT, this study examined the complex relationship between an individual’s socioeconomic characteristics, the built environment, congestion, and VMT. Measuring local congestion at a national level is also a key contribution of this research. This study used the same methodology as the Texas A&M Transportation Institute to compute a road congestion index and quantify local congestion for 93,769 drivers within 337 metropolitan areas. Our findings suggest that congestion is the main driver of VMT reduction. The findings also confirm that residents in compact development regions have lower daily VMTs because of the proximity of origins and destinations in denser areas with higher job–population balances. Therefore, rather than expanding highway networks, public transit investment might address traffic congestion more efficiently—not only by providing residents with more equitable and sustainable means of transportation, but also by encouraging people to reside in more compact and location-efficient areas.

scholarly journals Microfinance Institutions and Financial Sector Growth in Nigeria (1992-2018)

2021 ◽  
Author(s):  
Emmanuel Abiodun Ayodeji ◽  
Adebayo Tunbosun Ogundipe
Keyword(s):  
Secondary Data ◽  
Financial Sector ◽  
Variable Coefficients ◽  
Model Specification ◽  
Microfinance Institutions ◽  
Negative Effects ◽  
Positive Effects ◽  
Distributed Lag ◽  
Long Run ◽  
Bound Test

Abstract The extent to which microfinance bank institutions have contributed to the financial sector growth has not been well unraveled in the extant literature in Nigeria, hence, this study examined the effects of microfinance banks on financial sector growth in Nigeria. It further investigated the dynamic form of relationship between microfinance banks and financial sector growth in Nigeria covering a temporal scope 1992 to 2018. The model specification was formulated using financial sector GDP as the proxy for dependent variable, microfinance credit, deposits, assets and investment were used as proxies for microfinance banks institutions. Secondary data were sourced from CBN statistical Bulletin and analyzed using auto regressive distributed lag bound test and its corresponding short and long run coefficients. Finding revealed an inconclusive long run relationship between microfinance bank institutions and financial sector growth. Checking the individual variable coefficients in the short run, microfinance credit has significant positive effect while microfinance assets has insignificant effects on financial sector growth. In the long run, it was revealed that microfinance bank deposits and assets exert insignificant positive effects while microfinance credits have insignificant effect and investments have significant negative effects on financial sector growth. The study concluded that, in the long run, microfinance bank institutions exert positive and insignificant effects on financial sector growth in Nigeria. It was therefore recommended that, for microfinance bank institutions to impact significantly on financial sector growth in Nigeria, its credit should be increased and be more directed to the target individuals and the level of their investments should be geared up so as to engender growth of the financial sector in Nigeria. Furthermore, microfinance bank institutions should maintain its status quo on deposits and assets, however, improvement on them should be encouraged so as to enhance the growth of the financial sector in Nigeria

Household Travel, Household Characteristics, and Land Use: An Empirical Study from the 1994 Portland Activity-Based Travel Survey

1998 ◽  
Vol 1617 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Xiaoduan Sun ◽  
Chester G. Wilmot ◽  
Tejonath Kasturi
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Land Development ◽  
Data Set ◽  
Travel Survey ◽  
Forecasting Models ◽  
Demand Models ◽  
Residence Location ◽  
Household Travel ◽  
Use Factors

How a household’s travel behavior is influenced by its socioeconomic and land use factors has been a subject of interest for the development of travel demand forecasting models. This study investigates the relative importance of these factors based on the number of household daily trips and vehicle miles traveled (VMT). The travel data used in the study come from the 1994 Portland Activity-Based Travel Survey. In addition to income, vehicle ownership, and household size, other significant factors in household travel have been identified, such as the presence of car phones, dwelling type, home ownership, and even the length of resident’s time in the current home. Most important, this study has qualitatively revealed that land use makes a big difference in household VMT, whereas its impact on the number of daily trips is rather limited. After controlling for the land use variables, such as density and land development balance, it appears that there is little difference in household income distribution among three different land use areas. The household life stage/lifestyle appears to be more relevant to the residence location. And the land use development of the residence location imposes the greatest impact on the household daily VMT. The results from this study provide some empirical evidence to the development of travel forecasting models. Especially by examining the relationship between land use and household travel, the results shed light on how to incorporate land use factors into comprehensive travel demand models that can be used by policy makers in evaluation of alternative land use policies. This study serves as a step toward more comprehensive studies on transportation and land use. The results presented represent a preliminary analysis of an extensive data set; considerable additional analysis is already in process.

Transit Travel Demand Analysis Method Based on APTS Multi-Source Data

2013 ◽  
Vol 361-363 ◽  
pp. 2122-2126
Author(s):  
Jun Chen ◽  
Xiao Hua Li ◽  
Lan Ma
Keyword(s):  
Public Transportation ◽  
Large Scale ◽  
Travel Demand ◽  
Low Cost ◽  
Transportation Systems ◽  
Demand Analysis ◽  
Sample Survey ◽  
Analysis Method ◽  
Source Data ◽  
Bus Stops

Traditional transit travel information is acquired by Trip Sample Survey which has some disadvantages including high cost and short data lifecycle. This paper researched transit travel demand analysis method using Advanced Public Transportation Systems (APTS) data. The study collected APTS data of Nanning City in China and established APTS multi-source data analysis platform applying data warehouse technology. Based on key problems research, the paper presented the analysis procedure and content. Then, this study proposed the core algorithms of the method which are determinations of boarding bus stops, alighting bus stops and transfer bus stops of smart card passengers. Finally, these algorithms programs are experimented using large scale practical APTS data. The results show that this analysis method is low cost, operability and high accuracy.

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