Estimating time dependent O‐D trip tables during peak periods

Intelligent transportation systems (ITS) have been used to alleviate congestion problems arising due to demand during peak periods. The success of ITS strategies relies heavily on two factors: 1) the ability to accurately estimate the temporal and spatial distribution of travel demand on the transportation network during peak periods, and, 2) providing real‐time route guidance to users. This paper addresses the first factor. A model to estimate time dependent origin‐destination (O‐D) trip tables in urban areas during peak periods is proposed. The daily peak travel period is divided into several time slices to facilitate simulation and modeling. In urban areas, a majority of the trips during peak periods are work trips. For illustration purposes, only peak period work trips are considered in this paper. The proposed methodology is based on the arrival pattern of trips at a traffic analysis zone (TAZ) and the distribution of their travel times. The travel time matrix for the peak period, the O‐D trip table for the peak period, and the number of trips expected to arrive at each TAZ at different work start times are inputs to the model. The model outputs are O‐D trip tables for each time slice in the peak period. 1995 data for the Las Vegas metropolitan area are considered for testing and validating the model, and its application. The model is reasonably robust, but some lack of precision was observed. This is due to two possible reasons: 1) rounding‐off, and, 2) low ratio of total number of trips to total number of O‐D pair combinations. Hence, an attempt is made to study the effect of increasing this ratio on error estimates. The ratio is increased by multiplying each O‐D pair trip element with a scaling factor. Better estimates were obtained. Computational issues involved with the simulation and modeling process are discussed.     

Estimating economic losses of industry clusters due to port disruptions

Seaport operations are highly important for industries which rely heavily on imports and exports. A reliable evaluation of port risks is essential to govern the normal running of seaborne transportation and thus the industrial economies. The occurrence of a breakdown in the trade facilitators, such as ports, will disrupt the smooth flow of supply chains for the industries. The estimation of the economic loss for an industry when a port gets disrupted is a challenging task as the relationship between the port and industry clusters is complex. This study aims to develop a systematic framework for performing economic loss estimation of industry clusters due to port disruptions. The whole risk assessment is split into three stages focusing on the establishment of a network flow model, economic estimations and evaluating risk mitigation strategies. The proposed idea is demonstrated by a case study on Shenzhen port and its related manufacturing industries. A dynamic inventory control strategy used by manufacturers is found to be beneficial for mitigating port disruption risks.     

The role of transportation sectors in the Korean national economy: An input-output analysis

The transportation industry has been playing an important role in the economic development of Korea and, thus, has become a critical factor in sustaining the well-being of the Korean people. This paper attempts to analyze the economic impacts of four transportation modes using input-output (I-O) analysis, with specific application to Korea. To this end, we apply the I-O models to the Korean I-O tables generated by the Bank of Korea, paying particular attention to the four transportation sectors in Korea (rail, road, water, and air transportations), considering them as exogenous, and then determining their impacts. Specifically, the production-inducing effects, supply shortage effects, sectoral price effects, forward linkage effects, and backward linkage effects of the four transportation modes are quantitatively derived over the period 2000–2010. For example, the production-inducing effect of a KRW 1.0 production or investment in transportation is larger in the petroleum and transportation equipment sectors than in other sectors. Furthermore, the rail and road transportation sectors have greater supply shortage effects than the other transportation sectors. Finally, the potential uses of the results of this analysis are presented from the perspective of policy instruments, and policy implications are discussed.     

Quantifying sustainable strategies for the construction of highway pavements in Illinois

The environmental and economic burdens of various pavement construction strategies are evaluated in this study. A partial life-cycle approach was used to determine the environmental and economic benefits of asphalt concrete and Portland concrete mix designs as well as pavement-related pay items. Approximately 920 designs were assessed to determine the upstream energy consumption and global warming potential (GWP) of producing these mixes. In general, it was found that transportation hauling distances as well as asphalt binder type and production imposed the greatest variability on the environmental and economic costs of the mixes. In many cases, these variabilities were seen to reduce some of the benefits from using increased recycled content. A similar analysis was performed for pay items where it was found that the contribution of environmental and economic impacts to a project followed a trend with upper pavement layers having the greatest impact, followed by subsequently lower layers, and finally earth exaction and preparation. A cost effectiveness (CE) analysis was then conducted for 18 sustainable strategies, the majority of which had, on average, cost savings as well as environmental savings for both energy and GWP at the mix design level. Overall, this study systematically used common reference units (i.e., mix designs and pay items) from the industry to assess general trends, inconsistencies, and implications from using sustainable strategies in pavement construction.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

Total cost analysis: An alternative to benefit-cost analysis in evaluating transportation alternatives

This paper explains the theory in support of total cost analysis (TCA) to compare transportation system alternatives. The full costs of each alternative are first aggregated, including travel time costs and monetizable environmental and social costs. Many costs which are considered on the benefits side of the equation in benefit-cost analysis (BCA) as "cost savings" are brought over to the costs side. Total cost differences among alternatives are then traded off against their estimated non-monetized benefits or impacts, just as a consumer trades off product quality against cost before deciding which product he or she will buy. One advantage of TCA over traditional BCA is that the concept of "total cost" is more easily understood by the public and by political decision-makers than BCA concepts such as "net present worth", "benefit-cost ratio" and "internal rate of return". A second advantage is that there is no suggestion that all "benefits" have been considered; decision-makers are free to use their own value judgements to trade off total cost against non-monetizable social, environmental and economic impacts, just as they trade off quality and convenience against cost when purchasing goods and services in their roles as consumers. The TCA approach is demonstrated in this paper through a case study of two systemwide alternatives for the Baltimore, MD urban area.     

Correlations between industrial demands (direct and total) for communications and transportation in the U.S. economy 1947–1997

Using input–output (I–O) accounts provided by the U.S. Department of Commerce, this study investigates the aggregate relationships between the transportation and communications inputs demanded (directly and in total) by all industries in the U.S., and compares the results across time. We analyzed five pairs of Spearman correlations of transportation and communications demands (utilities, manufacturing, and overall) using the direct and total coefficient tables from the ten benchmark input–output years spanning 1947 to 1997. To correctly represent the overall economy-wide relationship, each industry (direct table) or commodity (total table) in the correlation was weighted proportionately to the monetary value of its contribution to the U.S. economy. In the analysis using direct I–O coefficients, we found a pattern of predominant complementarity between transportation and communications manufacturing, and substitution between transportation and communications utilities. There are intriguing indications, however, of a shift from substitution to complementarity in the latter case, beginning around 1987. In the analysis using total I–O coefficients, we found a pattern of complementarity for all years between transportation and communications manufacturing, and a pattern changing from substitution to complementarity for the remaining four pairs (transportation manufacturing and communications utilities; transportation utilities and communications manufacturing; the utilities pair; and the overall pair). Thus, from the industrial perspective (which constitutes a sizable proportion of the total demand for communications and transportation), it is not realistic in modern times to expect telecommunications to substitute for travel. Nevertheless, further research is needed into the specific causes of the observed shift from substitution to complementarity, and current trends should continue to be monitored for any changes.

Mitigating environmental impacts in advance: Evidence of cost and time savings for transportation projects

The traditional model for mitigating a transportation project’s environmental impacts typically operates project-by-project and delivers the mitigation just-in-time. In contrast, the newer practice of advance mitigation comprehensively assesses and mitigates impacts from one or multiple transportation projects before or during project planning, sometimes long before project construction begins. The practice has gained adherents for its potential to improve ecological outcomes, by better aligning mitigation and conservation goals. Advance mitigation also stands to reduce mitigation costs, an important secondary benefit for transportation agencies with constrained resources. Evidence of cost savings, however, has been piecemeal and anecdotal. This paper advances knowledge of advance mitigation’s financial impacts in two ways. First, it critically assesses the evidence about cost savings realized through advance mitigation, both through avoided up-front costs and reduced project delay. Second, it directly estimates the project time savings that might accrue with advance mitigation of state highway projects in California. Overall, the balance of evidence is encouraging for transportation agencies that would introduce the practice, and general agreement exists on its financial benefits. Considering project delays related only to the environmental process, we estimate advance mitigation could reduce delivery times by 1.3–5.0 months per project. Still, we also identify factors limiting comprehensive analysis. Transportation agencies adopting advance mitigation practices into their operations could use a pilot approach that includes rigorous environmental and mitigation cost accounting; such pilots would build needed empirical evidence of advance mitigation’s financial and ecological outcomes.     

Contracting for public transportation service

There is increasing interest in contracting to private industry for the provision of public transportation. The trend has accelerated since the mid 1970's spreading from local to regional transit authorities as the need for cost savings arise. Promising major savings without major service reductions, the merits of the strategy are now being evaluated at various levels. This paper focusses on the extent and magnitude of service contracting, the reasons why some agencies adopt the strategy, the nature and capability of the contractors and the actual performance of the arrangements.     

Fueling for contingencies: The hidden cost of unpredictability in the air transportation system

The aviation community is increasing its attention on the concept of predictability when conducting aviation service quality assessments. Reduced fuel consumption and the related cost is one of the various benefits that could be achieved through improved flight predictability. A lack of predictability may cause airline dispatchers to load more fuel onto aircraft before they depart; the flights would then in turn consume extra fuel just to carry excess fuel loaded. In this study, we employ a large dataset with flight-level fuel loading and consumption information from a major US airline. With these data, we estimate the relationship between the amount of loaded fuel and flight predictability performance using a statistical model. The impact of loaded fuel is translated into fuel consumption and, ultimately, fuel cost and environmental impact for US domestic operations. We find that a one-minute increase in the standard deviation of airborne time leads to a 0.88 min increase in loaded contingency fuel and 1.66 min in loaded contingency and alternate fuel. If there were no unpredictability in the aviation system, captured in our model by eliminating standard deviation in flight time, the reduction in the loaded fuel would between 6.12 and 11.28 min per flight. Given a range of fuel prices, this ultimately would translate into cost savings for US domestic airlines on the order of $120–$452 million per year.     

The role of volume-delay functions in forecasting and evaluating congestion charging schemes: the Stockholm case

This paper uses observations from before and during the Stockkholm congestion charging trial in order to validate and improve a transportation model for Stockholm. The model overestimates the impact of the charges on traffic volumes while at the same time it substantially underestimates the impact on travel times. These forecast errors lead to considerable underestimation of economic benefits which are dominated by travel time savings. The source of error lies in the static assignment that is used in the model. Making the volume-delay functions (VDFs) steeper only marginally improves the quality of forecast but strongly impacts the result of benefit calculations. We therefore conclude that the dynamic assignment is crucial for an informed decision on introducing measures aimed at relieving congestion. However, in the absence of such a calibrated dynamic model for a city, we recommend that at least a sensitivity analysis with respect to the slope of VDFs is performed.     

An optimization model of energy and transportation systems: Assessing the high-speed rail impacts in the United States

This paper presents a long-term investment planning model that co-optimizes infrastructure investments and operations across transportation and electric infrastructure systems for meeting the energy and transportation needs in the United States. The developed passenger transportation model is integrated within the modeling framework of a National Long-term Energy and Transportation Planning (NETPLAN) software, and the model is applied to investigate the impact of high-speed rail (HSR) investments on interstate passenger transportation portfolio, fuel and electricity consumption, and 40-year cost and carbon dioxide (CO₂) emissions. The results show that there are feasible scenarios under which significant HSR penetration can be achieved, leading to reasonable decrease in national long-term CO₂ emissions and costs. At higher HSR penetration of approximately 30% relative to no HSR in the portfolio promises a 40-year cost savings of up to $0.63 T, gasoline and jet fuel consumption reduction of up to 34% for interstate passenger trips, CO₂ emissions reduction by about 0.8 billion short tons, and increased resilience against petroleum price shocks. Additionally, sensitivity studies with respect to light-duty vehicle mode share reveal that in order to realize such long-term cost and emission benefits, a change in the passenger mode choice is essential to ensure higher ridership for HSR.     

An advanced traveler general information system for Fresno,California

This study estimates the effects of an advanced traveler general information system (ATGIS), which includes fuel consumption and health-related emissions cost information on transportation network users’ travel choice behavior for recurrent congestion conditions. The effects are estimated using four different formulations based on four different behavioral assumptions. Incorporating stochastic features in link cost estimation rather than in route choice, we provide a novel modeling approach that enables us to use transportation planning models of major metropolitan areas without a need for major computationally-expensive changes in the existing models. We examined the effects of an ATGIS on the Fresno, CA, road network and found several interesting results. First, the ATGIS impact is closely related to pre-system (prior to the implementation of an ATGIS) perceived fuel and emissions costs. Total travel time in the city can be reduced by 17% (no pre-system perceived costs) to 1% (accurate pre-system perceived costs), and even increased by 1% (higher-than-actual pre-system perceived costs). Second, the addition of emissions costs, although negligible relative to fuel and time costs, can effectively reduce total system-wide travel time by up to 1% and fuel consumption by up to 0.6% during peak hours. Third, the ATGIS can reduce annual social costs by as much as $1053 million (high gas price, no pre-system perception) to $48 million (medium gas price, accurate pre-system perception), which are comparable to social cost savings by a congestion pricing (CP) scheme in the study area.     

Efficiency of European Funds in the Accession Countries: The Case of Transport Infrastructure Investments in Latvia

ABSTRACT

A transport initiative, like any kind of public action, has an impact on the monetary cost, time cost, efficiency and comfort of the transportation of goods and people, in particular transport infrastructure investments. All such initiatives are subject to cost benefit analyses at the national and EU level to know whether the present value of total net benefits including environmental impacts exceeds their cost. However, several important policy issues remain unresolved in standard evaluation procedures. One issue is whether the so-called direct measurement of user benefit, which consists of quantifying changes in surplus of the users of the transport system, captures all welfare generated in the economy. Another issue is how the gains (or possibly losses) of a transport initiative are distributed among regions. The aim of this article is to perform a systematic and quantitative analysis of the socio-economic and spatial impacts of alternative transport investments by carrying out scenario simulations in order to improve the understanding of the impact of transportation policies on the short- and long-term spatial development in Latvia. The general result from the scenario simulations is that rail projects seem to be more effective in terms of promoting regional economic activity than road projects.     

The effect of socio-economic factors on the value of time in commuting to work

It is important to specify accurately the dollar value assigned to time savings, since up to eighty percent of the benefits estimated to accrue from improvements in transportation systems are associated with savings in travel time. In this paper the economic theory of consumer choice is utilized to structure a model that is used to estimate how Value of Time (VOT) measures vary with community-related variables.Parameters for this theoretical model are empirically estimated using data from transportation surveys conducted in Ithaca and Syracuse, New York and Amherst, Massachusetts. The results confirm the validity of the theoretical model and suggest that leisure time, travel cost, and household income level, as well as community population, are important determinants of the marginal value of time. These models are particularly suited for transferring data results obtained in one community to another, thereby saving survey costs, since the resulting VOT estimates are based solely on underlying socio-economic variables and community characteristics that are known for most localities. The methodology is also useful for estimating different VDT's for particular population subgroups, like the elderly, which may be the focus of a particular transportation project.     

Preparing a nation for autonomous vehicles: opportunities,barriers and policy recommendations

Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.     

Regional climate impact of aerosols emitted by transportation modes and potential effects of policies on demand and emissions

The transportation system is one of the main sectors with significant climate impact. In the U.S. it is the second main emitter of carbon dioxide. Its impact in terms of emission of carbon dioxide is well recognized. But a number of aerosol species have a non-negligible impact. The radiative forcing due to these species needs to be quantified. A radiative transfer code is used. Remote sensing data is retrieved to characterize different regions. The radiative forcing efficiency for black carbon are 396 ± 200 W/m²/AOD for the ground mode and 531 ± 190 W/m²/AOD for the air transportation, under clear sky conditions. The radiative forcing due to contrail is 0.14 ± 0.06 W/m² per percent coverage. Based on the forcing from the different species emitted by each mode of transportation, policies may be envisioned. These policies may affect demand and emissions of different modes of transportation. Demand and fleet models are used to quantify these interdependencies. Depending on the fuel price of each mode, mode shifts and overall demand reduction occur, and more fuel efficient vehicles are introduced in the fleet at a faster rate. With the introduction of more fuel efficient vehicles, the effect of fuel price on demand is attenuated. An increase in fuel price of 50 cents per gallon, scaled based on the radiative forcing of each mode, results in up to 5% reduction in emissions and 6% reduction in radiative forcing. With technologies, significant reduction in climate impact may be achieved.     

A review of input–output models on multisectoral modelling of transportation–economic linkages

Understanding the role of transportation in urban and regional economy is a persistent analytical topic within the transportation research community. Multi-sectoral input–output (IO) modelling, as a standard economic analysis tool, has great advantages in reflecting industrial interdependencies in an economy. The simplicity of IO and the well-known concept of multiplier effect also make it broadly used in both academia and practice. This paper provides an introduction of IO models and reviews the past IO studies from 2000 onward on modelling transportation–economic linkages. The following types of models are included: single-region, multi-region and random utility-based multi-region IO models, with central methodological features described. An evaluation of modelling issues brought to light by reviewing the literature is then presented. For future research, more critical attention should be directed towards IO’s modelling assumptions, spatial linkages and the static representation of the economy. In addition, there are needs for more attention in the following areas: sectoral aggregation, specification of household sector and the integration with transportation forecasting models. The paper concludes with brief recommendations on future IO applications.     

The socio-economics of travel behavior and environmental burdens: A Detroit,Michigan regional context

The transportation industry—particularly light-duty vehicles—is a significant contributor of greenhouse gasses, accounting for about one-third of overall emissions in the U.S. Research to date has studied various factors that impact travel behavior of residents with varying socio-economic characteristics. However, research on the socio-economic characteristics of residents and their impact on environmental burdens within a single urban region, as measured by fuel consumption and vehicular emissions, is recognized as under-represented in the U.S. planning and transportation literature. This study focuses on the Detroit region, Michigan, a unique case study due to the scale of suburbanization and urban decline, yet representative of many mid-western cities. The article explores how socio-economic characteristics impact travel patterns and environmental burdens within six Detroit region neighborhoods. Data on individual travel behavior and personal vehicle characteristics gathered from a mail survey enabled an analysis into how associated environmental burdens varied with socio-economic composition. The analysis explores contributions to environmental burdens between poorer urban and wealthier suburban populations.     

Timing rules for major transportation investments

The timing decision for major transportation investments – when to build – typically is made without an objective approach for considering the economic value of implementation at different times. This paper uses a model of benefit-cost analysis and derives rules for timing major transportation investments. Three sets of conditions are considered, depending on whether annual benefits of an investment are uncertain and whether the objective is to maximize net present value or simply to achieve positive net present value. The timing rules under each set of conditions are stated in three forms: benefit-cost ratio, annual benefits, and implementation time. The paper compares these timing rules analytically, discusses potential applications, and illustrates them with a numerical example. Consequences of incorrectly using the timing rules are also examined with the example. This revised version was published online in June 2006 with corrections to the Cover Date.