Evaluating the Efficacy of Zero-Emission Vehicle Deployment Strategies: The Maryland Case

Zhenbao Wang; Sevgi Erdogan; Frederick W. Ducca

doi:10.3390/su11061750

Evaluating the Efficacy of Zero-Emission Vehicle Deployment Strategies: The Maryland Case

Sustainability ◽

10.3390/su11061750 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1750 ◽

Cited By ~ 1

Author(s):

Zhenbao Wang ◽

Sevgi Erdogan ◽

Frederick W. Ducca

Keyword(s):

Co2 Emissions ◽

Travel Demand ◽

Unit Area ◽

Operating Cost ◽

Cross Combination ◽

Demand Models ◽

Balanced Distribution ◽

Zero Emission ◽

Carbon Dioxide Equivalent ◽

Zero Emission Vehicle

This study aimed to develop a model to estimate the impacts of zero-emission vehicle (ZEV) adoption on CO2 emissions and to evaluate efficacy of ZEV deployment strategies in achieving greenhouse gas (GHG) emission reduction goals. We proposed a modeling scheme to represent ZEVs in four-step trip-based travel demand models. We then tested six ZEV scenarios that were a cross-combination of three ZEV ownership levels and two ZEV operating cost levels. The proposed modeling scheme and scenarios were implemented on the Maryland Statewide Transportation Model (MSTM) to analyze the impacts of different ZEV ownership and cost combinations on travel patterns and on CO2 emissions. The main findings were the following: (1) A high-ZEV ownership scenario (43.14% of households with ZEVs) could achieve about a 16% reduction in statewide carbon dioxide equivalent (CO2Eq) emissions from 2015 base year levels; and (2) CO2Eq emissions at a future year baseline (2030) (the Constrained Long-Range Plan) level dropped by approximately 11% in low-ZEV ownership scenarios, 17% in medium-ZEV ownership scenarios, and 32% in high-ZEV ownership scenarios. The high-ZEV ownership results also indicated a more balanced distribution of emissions per unit area or per vehicle mile traveled among different counties.

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A Framework for Determining Highway Truck-Freight Benefits and Economic Impacts

Journal of the Transportation Research Forum ◽

10.5399/osu/jtrf.52.2.4156 ◽

2013 ◽

Cited By ~ 1

Author(s):

Zun Wang ◽

Jeremy Sage ◽

Anne Goodchild ◽

Eric Jessup ◽

Kenneth Casavant ◽

...

Keyword(s):

Computable General Equilibrium ◽

Travel Demand ◽

Economic Impacts ◽

Operating Cost ◽

Cost Savings ◽

State Highway ◽

Transportation Projects ◽

Demand Models ◽

Travel Time Savings

This paper proposes a method for calculating both the direct freight benefits and the larger economic impacts of transportation projects. The identified direct freight benefits included in the methodology are travel time savings, operating cost savings, and environmental impacts. These are estimated using regional travel demand models (TDM) and additional factors. Economic impacts are estimated using a regional Computable General Equilibrium (CGE) model. The total project impacts are estimated combining the outputs of the transportation model and an economic model. A Washington State highway widening project is used as a case study to demonstrate the method. The proposed method is transparent and can be used to identify freight specific benefits and generated impacts.

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PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v12i3.861 ◽

2013 ◽

Vol 12 (3) ◽

Author(s):

Rusmadi Suyuti

Keyword(s):

Information System ◽

Real Time ◽

Travel Demand ◽

Urban Traffic ◽

Road User ◽

Traffic Information ◽

Estimation Methods ◽

Traffic Counts ◽

Real Time Traffic ◽

Demand Models

Traffic information condition is a very useful information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.

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Address-based computation of intra-cell distances for travel demand models

Procedia Computer Science ◽

10.1016/j.procs.2021.03.023 ◽

2021 ◽

Vol 184 ◽

pp. 123-130

Author(s):

Matthias Heinrichs ◽

Rita Cyganski ◽

Daniel Krajzewicz

Keyword(s):

Travel Demand ◽

Demand Models

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Assessing CO2 Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City

Land ◽

10.3390/land10020137 ◽

2021 ◽

Vol 10 (2) ◽

pp. 137

Author(s):

Xianchun Tan ◽

Tangqi Tu ◽

Baihe Gu ◽

Yuan Zeng ◽

Tianhang Huang ◽

...

Keyword(s):

Land Use ◽

Co2 Emissions ◽

Travel Demand ◽

Development Model ◽

Low Carbon ◽

Passenger Transport ◽

Transport Accessibility ◽

Mixed Use ◽

Mixed Land Use ◽

Low Carbon City

Assessing transport CO2 emissions is important in the development of low-carbon strategies, but studies based on mixed land use are rare. This study assessed CO2 emissions from passenger transport in traffic analysis zones (TAZs) at the community level, based on a combination of the mixed-use development model and the vehicle emission calculation model. Based on mixed land use and transport accessibility, the mixed-use development model was adopted to estimate travel demand, including travel modes and distances. As a leading low-carbon city project of international cooperation in China, Shenzhen International Low-Carbon City Core Area was chosen as a case study. The results clearly illustrate travel demand and CO2 emissions of different travel modes between communities and show that car trips account for the vast majority of emissions in all types of travel modes in each community. Spatial emission differences are prominently associated with inadequately mixed land use layouts and unbalanced transport accessibility. The findings demonstrate the significance of the mixed land use and associated job-housing balance in reducing passenger CO2 emissions from passenger transport, especially in per capita emissions. Policy implications are given based on the results to facilitate sophisticated transport emission control at a finer spatial scale. This new framework can be used for assessing the impacts of urban planning on transport emissions to promote sustainable urbanization in developing countries.

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A conceptual framework for modeling the supply side of mobility services within large-scale agent-based travel demand models

Transportation Letters ◽

10.1080/19427867.2021.1913303 ◽

2021 ◽

pp. 1-10

Author(s):

Francisco Calderón ◽

Eric J. Miller

Keyword(s):

Conceptual Framework ◽

Large Scale ◽

Travel Demand ◽

Supply Side ◽

Agent Based ◽

Demand Models

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A copula-based continuous cross-nested logit model for tour scheduling in activity-based travel demand models

Transportation Research Part B Methodological ◽

10.1016/j.trb.2021.01.001 ◽

2021 ◽

Vol 145 ◽

pp. 324-341

Author(s):

Sepehr Ghader ◽

Carlos Carrion ◽

Liang Tang ◽

Arash Asadabadi ◽

Lei Zhang

Keyword(s):

Logit Model ◽

Travel Demand ◽

Nested Logit ◽

Nested Logit Model ◽

Demand Models ◽

Tour Scheduling

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Ensemble learning activity scheduler for activity based travel demand models

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2021.102972 ◽

2021 ◽

Vol 123 ◽

pp. 102972

Author(s):

Mohammad Hesam Hafezi ◽

Naznin Sultana Daisy ◽

Hugh Millward ◽

Lei Liu

Keyword(s):

Ensemble Learning ◽

Travel Demand ◽

Learning Activity ◽

Demand Models

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

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211028870 ◽

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.

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