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

2013 ◽  
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.

Development of a Congestion Management System Methodology for the Indiana State Highway Network

2002 ◽  
Vol 1781 (1) ◽  
pp. 40-48 ◽  
Author(s):  
Kasem Choocharukul ◽  
Kumares C. Sinha ◽  
John L. Nagle
Keyword(s):  
Operating Cost ◽  
Cost Savings ◽  
Congestion Management ◽  
Incident Management ◽  
Signal Coordination ◽  
State Highway ◽  
Planning Project ◽  
Highway Network ◽  
Travel Time Savings ◽  
The Impact

A methodology for developing congestion management–related projects for the Indiana state highway network is described. The methodology is based on a sketch planning analysis technique that can be used with limited input data. The software package provides estimates of costs and other effects of potential congestion mitigation projects to undertake in a given year, which can be used by planners and programmers in long-range planning. Project types include road widening, high-occupancy-vehicle facilities, ramp metering, incident management, and arterial traffic signal coordination. The impact is assessed in travel time savings, vehicle operating cost savings, crash cost savings, and emission reductions. An example application of the methodology is given for the 7.81-mi segment of I-65 between Interchanges 116 and 123 in the Indianapolis area.

Traffic and Welfare Impacts of Credit-Based Congestion Pricing Applications: An Austin Case Study

2020 ◽  
pp. 036119812096013
Author(s):  
Weijia (Vivian) Li ◽  
Kara M. Kockelman ◽  
Yantao Huang
Keyword(s):  
Travel Demand ◽  
Congestion Pricing ◽  
Consumer Surplus ◽  
Net Benefit ◽  
Welfare Impacts ◽  
Administrative Costs ◽  
Demand Models ◽  
The Difference ◽  
Almost All

This study seeks smart credit-based congestion pricing (CBCP) solutions for maximally improving travelers’ welfare by varying toll levels and locations across the Austin, Texas network. Scenarios evaluated include selecting links with maximum delays by variably tolling bridges and by recognizing congestion externalities across all links. Travel demand models deliver inputs for normalized logsum differences to quantify and compare consumer surplus changes across traveler types, around the region. Results suggest limited tolling locations under four broad times of day can do more harm than good, unless travelers shift out of the PM and AM peak periods or revenues are returned to travelers as credits. When using CBCP across all congested links at congested times of day (with 10% of revenues retained to cover system administrative costs), an average net benefit of $1.61 per licensed driver per weekday is estimated, with almost all travelers benefiting. For example, 95% of the traffic analysis zones’ lowest value of travel time (VOTT) group (VOTT1 = $5/hour) are expected to benefit from the CBCP policy. Tolling at twice the difference between marginal social cost and average travel cost (on each subset of congested links) appears to benefit more people, although tolling high on various links adds to congestion elsewhere. For example: tolling Austin’s highest-delay-producing or “top 500” links is estimated to benefit 98.5% of the zones’ highest VOTT (VOTT5 = $45/hour) travelers, while raising vehicle-miles traveled by just 0.8% (as a result of more circuitous, congestion- and toll-avoiding travel).

Induced Vehicle Travel in the Environmental Review Process

2020 ◽  
Vol 2674 (7) ◽  
pp. 468-479
Author(s):  
Jamey M. B. Volker ◽  
Amy E. Lee ◽  
Susan Handy
Keyword(s):  
Environmental Impacts ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Planning Process ◽  
Capacity Expansion ◽  
Highway Capacity ◽  
Online Tool ◽  
Induced Travel ◽  
Demand Models

If we expand roadway capacity, more drivers will come, or so economic theory suggests and a substantial body of empirical research now shows. Despite strong evidence, the “induced travel” effect is often ignored, underestimated, or misestimated in the planning process, particularly in the assessment of the environmental impacts of roadway capacity expansions. Underestimating induced travel will generally lead to overestimation of the traffic congestion relief benefits a highway expansion project might generate, along with underestimation of its environmental impacts. A major reason that induced travel tends to be underplayed in environmental analyses is that travel demand models do not typically include all of the feedback loops necessary to accurately predict the induced travel effect. We developed an online tool, based on elasticities reported in the literature, to facilitate the estimation of the induced vehicle travel impacts of roadway capacity expansion projects in California, with potential future expansion to other geographies. We describe the tool, apply it to five case study highway capacity expansion projects, and then compare the results with the induced travel estimates reported in the environmental impact analyses for those projects. Our results suggest that environmental analyses frequently fail to fully capture the induced vehicle travel effects of highway capacity expansion projects.

scholarly journals Analyzing OpenStreetMap as data source for travel demand models A case study in Karlsruhe

2019 ◽  
Vol 41 ◽  
pp. 104-112
Author(s):  
Lars Briem ◽  
Michael Heilig ◽  
Christian Klinkhardt ◽  
Peter Vortisch
Keyword(s):  
Travel Demand ◽  
Demand Models ◽  
Data Source

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

2019 ◽  
Vol 11 (6) ◽  
pp. 1750 ◽  
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.

Bottom Hole Assembly Design Enhancement Successfully Eliminate Hole Problems and Reduce Significant Drilling Time : South S Field Case Study

2020 ◽  
Author(s):  
Y. D. Mulia
Keyword(s):  
Contact Area ◽  
Cost Savings ◽  
Assembly Design ◽  
Drilling Performance ◽  
Bottom Hole ◽  
Unconsolidated Sand ◽  
Bottom Hole Assembly ◽  
Drilling Parameter ◽  
Drilling Time

For S-15 and S-14 wells at South S Field, drilling of the 12-1/4” hole section became the longest tangent hole section interval of both wells. There were several challenges identified where hole problems can occur. The hole problems often occur in the unconsolidated sand layers and porous limestone formation sections of the hole during tripping in/out operations. Most of the hole problems are closely related to the design of the Bottom Hole Assembly (BHA). In many instances, hole problems resulted in significant additional drilling time. As an effort to resolve this issue, a new BHA setup was then designed to enhance the BHA drilling performance and eventually eliminate hole problems while drilling. The basic idea of the enhanced BHA is to provide more annulus clearance and limber BHA. The purpose is to reduce the Equivalent Circulating Density (ECD,) less contact area with formation, and reduce packoff risk while drilling through an unconsolidated section of the rocks. Engineering simulations were conducted to ensure that the enhanced BHA were able to deliver a good drilling performance. As a results, improved drilling performance can be seen on S-14 well which applied the enhanced BHA design. The enhanced BHA was able to drill the 12-1/4” tangent hole section to total depth (TD) with certain drilling parameter. Hole problems were no longer an issue during tripping out/in operation. This improvement led to significant rig time and cost savings of intermediate hole section drilling compared to S-15 well. The new enhanced BHA design has become one of the company’s benchmarks for drilling directional wells in South S Field.

PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

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.  

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

2021 ◽  
Vol 184 ◽  
pp. 123-130
Author(s):  
Matthias Heinrichs ◽  
Rita Cyganski ◽  
Daniel Krajzewicz
Keyword(s):  
Travel Demand ◽  
Demand Models

scholarly journals Optimal placement design for picking and packing in distribution centers

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica
Keyword(s):  
Optimal Allocation ◽  
Programming Model ◽  
Operating Cost ◽  
Nonlinear Integer Programming ◽  
Operating Costs ◽  
Optimal Placement ◽  
Distribution Centers ◽  
Suitable Space ◽  
Efficient Distribution

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.

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