Polycentrism as a Sustainable Development Strategy
Authors: Elijah Knaap, Chengri Ding, Yi Niu, Sabyasachee Mishra
Report
Synopsis: We present in this paper an analysis of economic centers and their role in shaping employment development patterns and travel behavior in the state of Maryland. We begin by identifying 23 economic centers in the Baltimore-Washington region. We then examine these centers first in their role as centers of economic activity then in their role as nodes in the state’s transportation system. Finally, we identify the commute sheds of each center, for multiple modes of travel and travel times, and examine jobs-housing balance within these various commute sheds. We find that Maryland’s economic centers not only promote agglomerative economies and thus facilitate economic growth; they also generate a disproportionate number of trips and promote transit ridership. These results provide empirical support for policies that promote polycentric urban development, and especially policies that promote polycentric employment development. Further, they suggest that polycentrism as a sustainable development strategy requires careful coordination of regional transportation systems designed to balance jobs and housing within a center’s transit commute shed. Based on these findings we recommend that the Maryland state development plan and regional sustainable communities’ plans across the nation should encourage the concentration of employment within economic centers and encourage housing development within the transit commute sheds of those centers.
Authors: Avin, Uri, Timothy F. Welch, Gerrit Knaap, Fred Ducca, Sabyasachee Mishra, Yuchen Cui, and Sevgi Erd
Report
Synopsis: Urban form studies have generally used regional density vs. sprawl land use scenarios to assesstravel behavior outcomes. The more nuanced but nonetheless important allocation of jobs andhousing and their relationship to each other as a factor in travel behavior has received much lessattention. That relationship is explored in this statewide urban form study for Maryland. This is astate where county land use has a long tradition of growth management, but one whose regionaland statewide implications have not been evaluated. How does a continuation of the County levelsmart growth regime play out statewide compared to other scenarios of job and housingdistribution that are driven by higher driving costs or transit oriented development goals or localzoning rather than local policy-driven projections? Answers are provided through the applicationof a statewide travel demand model, the Maryland Statewide Transportation Model (MSTM).The findings suggest that the debate should move beyond walkability, density and compactgrowth and towards a more productive dialog about how we organize whole cities and regions.
Authors: Snehamay Khasnabis, Sunder Lall Dhingra, Sabyasachee Mishra, and Chirag Safi (2010)
Report
Synopsis: In this paper, the authors examine different investment mechanisms for transportation infrastructure projects involving the private enterprise in developing countries. Roles identified vary from those of a financier to an operator for successful public-private ventures. A case study involving such a joint venture in India, the Mumbai Pune Expressway/National Highway 4 (MPEW/NH4) is presented, and fiscal implications of the program, both from the perspective of the public and the private enterprise are examined. The study concludes that if properly planned, joint ventures can be mutually beneficial. A joint public-private program may enable the public sector to use the resources saved for other public projects. It also provides the private agency an opportunity to invest monies in a profitable enterprise that yields social benefits, (e.g. improving mobility, promoting economic development, etc.). Careful analysis must be conducted before the project is undertaken to assess the financial and economic implications of the project from each participant’s viewpoint, with due regard to risks and uncertainties associated with such long term investments.
Authors: Sabyasachee Mishra, Xin Ye, Fred Ducca, and Gerrit Knaap (2011)
Report
Synopsis: The Maryland-Washington, DC region has been experiencing significant land-use changes and changes in local and regional travel patterns due to increasing growth and sprawl. The region’s highway and transit networks regularly experience severe congestion levels. Before proceeding with plans to build new transportation infrastructure to address this expanding demand for travel, a critical question is how future land use will affect the regional transportation system. This article investigates how an integrated land-use and transportation model can address this question. A base year and two horizon-year land use-transport scenarios are analyzed. The horizon-year scenarios are: (1) business as usual (BAU) and (2) high gasoline prices (HGP). The scenarios developed through the land-use model are derived from a three-stage top-down approach: (a) at the state level, (b) at the county level, and (c) at the statewide modeling zone (SMZ) level that reflects economic impacts on the region. The transportation model, the Maryland Statewide Transport Model (MSTM), is an integrated land use-transportation model, capable of reflecting development and travel patterns in the region. The model includes all of Maryland, Washington, DC, and Delaware, and portions of southern Pennsylvania, northern Virginia, New Jersey, and West Virginia. The neighboring states are included to reflect the entering, exiting, and through trips in the region. The MSTM is a four-step travel-demand model with input provided by the alternative land-use scenarios, designed to produce link-level assignment results for four daily time periods, nineteen trip purposes, and eleven modes of travel. This article presents preliminary results of the land use-transportation model. The long-distance passenger and commodity-travel models are at the development stage and are not included in the results. The analyses of the land use-transport scenarios reveal insights to the region’s travel patterns in terms of the congestion level and the shift of travel as per land-use changes. The model is a useful tool for analyzing future land-use and transportation impacts in the region.
Authors: Fred Ducca, Rolf Moeckel, Sabyasachee Mishra, and Tara Weidner (2012)
Report
Synopsis: Mega-regions are a new geography that may well form the “nation's operative regions when competing in the future global economy. A challenge is to determine how to foster greater efficiencies in these mega-regions by creating a stronger infrastructure and technology backbone in the Nation's surface transportation system,” according to the March 2010 FHWA Strategic Plan. To meet this challenge these regions will need analysis tools to evaluate scenarios and their regional impacts, analysis tools covering areas larger than covered by the typical Metropolitan Planning Organization (MPO) or State Department of Transportation (DOT) models. This paper describes what makes mega-regions different and identifies analytic issues mega-regions may need to address, identifies the Chesapeake Mega-region and provides a framework for analyzing issues within the Chesapeake mega-region. Finally, the framework is tested through a proof of concept scenario which assumes a sudden price rise in gasoline prices and the likely effects on travel. A brief summary of further work and additional scenarios planned is provided.
Authors: Sabyasachee Mishra, Timothy Welch, and Manoj K. Jha (2012)
Report
Synopsis: Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.
Authors: Snehamay Khasnabis, Sabyasachee Mishra, and Chirag Safi (2012)
Report
Synopsis: The purpose of evaluating mutually exclusive alternatives is to select the one with the highest benefits for implementation. A number of analytic techniques are available for such evaluation purposes. Four such techniques: Cost Effectiveness (C/E), Benefit Cost Ratio (B/C), Internal Rate of Return (IRR), and Pay-off Period (PP) are discussed in this paper, including their theoretical foundation and data requirements, Also discussed are the measures of effectiveness (MOE) associated with each of these techniques, and how these are to be interpreted.
Authors: Sabyasachee Mishra, Snehamay Khasnabis, and Sunder Lall Dhingra (2012)
Report
Synopsis: Traditional economic analysis techniques used in the assessment of Public Private Partnership (PPP) projects are based upon the assumption that future cash flows are fully deterministic in nature and are not designed to account for risks involved in the assessment of future returns. In reality, many of these infrastructure projects are associated with significant risks stemming from the lack of knowledge about future cost and benefit streams. The fundamental premise of the PPP concept is to efficiently allocate risks between the public and the private partner. The return based on deterministic analysis may not depict a true picture of future economic outcomes of a PPP project for the multiple agencies involved. This deficiency underscores the importance of risk-based economic analysis for such projects. In this paper, the authors present the concept of Value-at-Risk (VaR) as a measure of effectiveness (MOE) to assess the risk share for the public and private entity in a PPP project. Bootstrap simulation is used to generate the risk profile savings in vehicle operating cost, and in travel time resulting from demand-responsive traffic. The VaR for Internal Rate of Return (IRR) is determined for public and private entity. The methodology is applied to a case study involving such a joint venture in India, the Mumbai Pune
Authors: Yohannes Weldegiorgis, Sabyasachee Mishra, and Manoj K. Jha (2011)
Report
Synopsis: The primary purpose of installing Red Light Cameras (RLCs) is to improve intersection safety by discouraging motorists to cross the intersection when the signal for approaching vehicles turns red. Due to the fear of being fined when crossing an RLC equipped intersection at the onset of the red signal, many approaching vehicles may have a tendency of stopping during the yellow phase. This tendency may impact intersection capacity, which can be significant in congested transportation networks during rush hours, especially when several intersections are equipped with RLCs along a sequence of traffic signals, resulting in a disruption of traffic progression. In order to examine the driver and capacity characteristics at intersections with RLCs and compare them with those without RLCs we develop a binary probit choice model to understand driver's stop and go behavior at the onset of yellow intervals, also known as dilemma zone. Further, in order to capture the impact to intersection capacity at intersections with RLCs we develop a probabilistic computational procedure using data from ten intersection pairs (with and without RLCs) in the Baltimore area. The results indicate that, in general, RLCs reduce the intersection capacity since driver's travel behavior is influenced by the presence of the cameras. Other contributory factors for the so-called capacity reduction, such as driver population (e.g., familiar vs. unfamiliar drivers) and traffic-mix (e.g., trucks vs. passenger cars) characteristics have been left for future works.
Authors: Sabyasachee Mishra, Tom V. Mathew, and Snehamay Khasnabis (2010)
Report
Synopsis: The authors present a procedure for resource allocation among transit agencies for transit fleet management, specifically focusing on the purchase of new buses and rebuilding of existing buses. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subject to budgetary, policy and other constraints. The problem is solved using Integer Programming (IP) and its application is demonstrated through a case study utilizing actual transit fleet data from the Michigan Department of Transportation.
Authors: Arnab Chakraborty, Sabyasachee Mishra, and Yong Wook Kim (2012)
Report
Synopsis: Planning support systems often employ urban models that simulate and evaluate impacts of plans. Their application to plan making is however, challenging when issues transcend local jurisdictions, and model assumptions are contested by the stakeholders. Neglecting the role of such specifications, especially when they are important and uncertain, can diminish the efficacy of plans. In this paper, we use the principles of scenario analysis to illustrate the impacts of two such important considerations – forecasts and regional boundaries – on model outcomes and related decisions. We use Montgomery County, MD as a case and leverage a model developed for a larger region, i.e. the state of MD and vicinity. We develop two sets of scenarios – one where the county (a local government) freely competes with its neighboring jurisdictions for development and another where a higher (i.e. a regional or state) level agency controls the extent of development that the county can receive. The scenarios are constructed using different specifications for regional boundaries and also results in different amount of growth in the County – both rare practices in scenario analysis with models. We then compare the outcomes on a set of indicators and draw implications for planning. We conclude with the argument that planning agencies should compare future scenarios not just with different desirability but different sets of assumptions and regional formulations.
Authors: Tom V. Mathewa, Snehamay Khasnabisb, and Sabyasachee Mishra (2010)
Report
Synopsis: Most transit agencies require government support for the replacement of their aging fleet. A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is presented in this study. The proposed procedure is a 3-dimensional model that includes the choice of a fleet improvement program, agencies that may receive them, and the timing of investments. Earlier efforts to solve this problem involved the application of one or 2-dimensional models for each year of the planning period. These may have resulted in suboptimal solution as the models are blind to the impact of the fleet management program of the subsequent years. Therefore, a new model to address a long-term planning horizon is proposed. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subjected to improvement program and budgetary constraints. Two variants of the problem, one with an annual budget constraint and the other with a single budget constraint for the entire planning period, are formulated. Two independent approaches, namely, branch and bound algorithm and genetic algorithm are used to obtain the solution. An example problem is solved and results are discussed in details. Finally, the model is applied to a large scale real-world problem and a detailed analysis of the results is presented.
Authors: Arnab Chakraborty and Sabyasachee Mishra (2011)
Report
Synopsis: Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.
Authors: Arnab Chakraborty and Sabyasachee Mishra (2013)
Report
Synopsis: Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.
Authors: Sabyasachee Mishra and Timothy F. Welch (2011)
Report
Synopsis: Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the user’s in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO2 estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing of Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.
Authors: Sabyasachee Mishra and Timothy Welch (2012)
Report
Synopsis: Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution that arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the users in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO2 estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.
Authors: Sabyasachee Mishra and Snehamay Khasnabis (2012)
Report
Synopsis: The authors present a procedure for allocating resources for implementing safety improvement alternatives at urban intersections over a multi-year planning horizon. The procedure, based upon optimization techniques, attempts to maximize benefits-measured in dollars saved by reducing crashes of different severity categories, subject to budgetary and other constraints. It is presented in two parts (1) a Base case including the objective function and a set of mandatory constraints, and (2) additional policy constraints / special features that can be separately incorporated to the Base case.
Authors: Elijah Knaap, Chengri Ding, Yi Niu, Sabyasachee Mishra
Report
Synopsis: We present in this paper an analysis of economic centers and their role in shaping employment development patterns and travel behavior in the state of Maryland. We begin by identifying 23 economic centers in the Baltimore-Washington region. We then examine these centers first in their role as centers of economic activity then in their role as nodes in the state’s transportation system. Finally, we identify the commute sheds of each center, for multiple modes of travel and travel times, and examine jobs-housing balance within these various commute sheds. We find that Maryland’s economic centers not only promote agglomerative economies and thus facilitate economic growth; they also generate a disproportionate number of trips and promote transit ridership. These results provide empirical support for policies that promote polycentric urban development, and especially policies that promote polycentric employment development. Further, they suggest that polycentrism as a sustainable development strategy requires careful coordination of regional transportation systems designed to balance jobs and housing within a center’s transit commute shed. Based on these findings we recommend that the Maryland state development plan and regional sustainable communities’ plans across the nation should encourage the concentration of employment within economic centers and encourage housing development within the transit commute sheds of those centers.
Even Smarter Growth? Land Use, Transportation, and Greenhouse Gas in Maryland
Authors: Avin, Uri, Timothy F. Welch, Gerrit Knaap, Fred Ducca, Sabyasachee Mishra, Yuchen Cui, and Sevgi Erd
Report
Synopsis: Urban form studies have generally used regional density vs. sprawl land use scenarios to assesstravel behavior outcomes. The more nuanced but nonetheless important allocation of jobs andhousing and their relationship to each other as a factor in travel behavior has received much lessattention. That relationship is explored in this statewide urban form study for Maryland. This is astate where county land use has a long tradition of growth management, but one whose regionaland statewide implications have not been evaluated. How does a continuation of the County levelsmart growth regime play out statewide compared to other scenarios of job and housingdistribution that are driven by higher driving costs or transit oriented development goals or localzoning rather than local policy-driven projections? Answers are provided through the applicationof a statewide travel demand model, the Maryland Statewide Transportation Model (MSTM).The findings suggest that the debate should move beyond walkability, density and compactgrowth and towards a more productive dialog about how we organize whole cities and regions.
Mechanisms for Transportation Infrastructure Investment in Developing Countries
Authors: Snehamay Khasnabis, Sunder Lall Dhingra, Sabyasachee Mishra, and Chirag Safi (2010)
Report
Synopsis: In this paper, the authors examine different investment mechanisms for transportation infrastructure projects involving the private enterprise in developing countries. Roles identified vary from those of a financier to an operator for successful public-private ventures. A case study involving such a joint venture in India, the Mumbai Pune Expressway/National Highway 4 (MPEW/NH4) is presented, and fiscal implications of the program, both from the perspective of the public and the private enterprise are examined. The study concludes that if properly planned, joint ventures can be mutually beneficial. A joint public-private program may enable the public sector to use the resources saved for other public projects. It also provides the private agency an opportunity to invest monies in a profitable enterprise that yields social benefits, (e.g. improving mobility, promoting economic development, etc.). Careful analysis must be conducted before the project is undertaken to assess the financial and economic implications of the project from each participant’s viewpoint, with due regard to risks and uncertainties associated with such long term investments.
A Functional Integrated Land Use-Transportation Model for Analyzing Transportation Impacts in the Maryland-Washington D.C. Region
Authors: Sabyasachee Mishra, Xin Ye, Fred Ducca, and Gerrit Knaap (2011)
Report
Synopsis: The Maryland-Washington, DC region has been experiencing significant land-use changes and changes in local and regional travel patterns due to increasing growth and sprawl. The region’s highway and transit networks regularly experience severe congestion levels. Before proceeding with plans to build new transportation infrastructure to address this expanding demand for travel, a critical question is how future land use will affect the regional transportation system. This article investigates how an integrated land-use and transportation model can address this question. A base year and two horizon-year land use-transport scenarios are analyzed. The horizon-year scenarios are: (1) business as usual (BAU) and (2) high gasoline prices (HGP). The scenarios developed through the land-use model are derived from a three-stage top-down approach: (a) at the state level, (b) at the county level, and (c) at the statewide modeling zone (SMZ) level that reflects economic impacts on the region. The transportation model, the Maryland Statewide Transport Model (MSTM), is an integrated land use-transportation model, capable of reflecting development and travel patterns in the region. The model includes all of Maryland, Washington, DC, and Delaware, and portions of southern Pennsylvania, northern Virginia, New Jersey, and West Virginia. The neighboring states are included to reflect the entering, exiting, and through trips in the region. The MSTM is a four-step travel-demand model with input provided by the alternative land-use scenarios, designed to produce link-level assignment results for four daily time periods, nineteen trip purposes, and eleven modes of travel. This article presents preliminary results of the land use-transportation model. The long-distance passenger and commodity-travel models are at the development stage and are not included in the results. The analyses of the land use-transport scenarios reveal insights to the region’s travel patterns in terms of the congestion level and the shift of travel as per land-use changes. The model is a useful tool for analyzing future land-use and transportation impacts in the region.
A Mega-region Framework for Analyzing a High Energy Price Future
Authors: Fred Ducca, Rolf Moeckel, Sabyasachee Mishra, and Tara Weidner (2012)
Report
Synopsis: Mega-regions are a new geography that may well form the “nation's operative regions when competing in the future global economy. A challenge is to determine how to foster greater efficiencies in these mega-regions by creating a stronger infrastructure and technology backbone in the Nation's surface transportation system,” according to the March 2010 FHWA Strategic Plan. To meet this challenge these regions will need analysis tools to evaluate scenarios and their regional impacts, analysis tools covering areas larger than covered by the typical Metropolitan Planning Organization (MPO) or State Department of Transportation (DOT) models. This paper describes what makes mega-regions different and identifies analytic issues mega-regions may need to address, identifies the Chesapeake Mega-region and provides a framework for analyzing issues within the Chesapeake mega-region. Finally, the framework is tested through a proof of concept scenario which assumes a sudden price rise in gasoline prices and the likely effects on travel. A brief summary of further work and additional scenarios planned is provided.
Performance Indicators for Public Transit Connectivity in Multi-Modal Transportation Networks
Authors: Sabyasachee Mishra, Timothy Welch, and Manoj K. Jha (2012)
Report
Synopsis: Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.
An Evaluation Procedure for Mutually Exclusive Highway Safety Alternatives under Different Program Missions
Authors: Snehamay Khasnabis, Sabyasachee Mishra, and Chirag Safi (2012)
Report
Synopsis: The purpose of evaluating mutually exclusive alternatives is to select the one with the highest benefits for implementation. A number of analytic techniques are available for such evaluation purposes. Four such techniques: Cost Effectiveness (C/E), Benefit Cost Ratio (B/C), Internal Rate of Return (IRR), and Pay-off Period (PP) are discussed in this paper, including their theoretical foundation and data requirements, Also discussed are the measures of effectiveness (MOE) associated with each of these techniques, and how these are to be interpreted.
A Simulation Approach for Modeling Risk in Transportation Infrastructure Investment Decision Making
Authors: Sabyasachee Mishra, Snehamay Khasnabis, and Sunder Lall Dhingra (2012)
Report
Synopsis: Traditional economic analysis techniques used in the assessment of Public Private Partnership (PPP) projects are based upon the assumption that future cash flows are fully deterministic in nature and are not designed to account for risks involved in the assessment of future returns. In reality, many of these infrastructure projects are associated with significant risks stemming from the lack of knowledge about future cost and benefit streams. The fundamental premise of the PPP concept is to efficiently allocate risks between the public and the private partner. The return based on deterministic analysis may not depict a true picture of future economic outcomes of a PPP project for the multiple agencies involved. This deficiency underscores the importance of risk-based economic analysis for such projects. In this paper, the authors present the concept of Value-at-Risk (VaR) as a measure of effectiveness (MOE) to assess the risk share for the public and private entity in a PPP project. Bootstrap simulation is used to generate the risk profile savings in vehicle operating cost, and in travel time resulting from demand-responsive traffic. The VaR for Internal Rate of Return (IRR) is determined for public and private entity. The methodology is applied to a case study involving such a joint venture in India, the Mumbai Pune
Comparing Driver and Capacity Characteristics at Intersections With and Without Red Light Cameras
Authors: Yohannes Weldegiorgis, Sabyasachee Mishra, and Manoj K. Jha (2011)
Report
Synopsis: The primary purpose of installing Red Light Cameras (RLCs) is to improve intersection safety by discouraging motorists to cross the intersection when the signal for approaching vehicles turns red. Due to the fear of being fined when crossing an RLC equipped intersection at the onset of the red signal, many approaching vehicles may have a tendency of stopping during the yellow phase. This tendency may impact intersection capacity, which can be significant in congested transportation networks during rush hours, especially when several intersections are equipped with RLCs along a sequence of traffic signals, resulting in a disruption of traffic progression. In order to examine the driver and capacity characteristics at intersections with RLCs and compare them with those without RLCs we develop a binary probit choice model to understand driver's stop and go behavior at the onset of yellow intervals, also known as dilemma zone. Further, in order to capture the impact to intersection capacity at intersections with RLCs we develop a probabilistic computational procedure using data from ten intersection pairs (with and without RLCs) in the Baltimore area. The results indicate that, in general, RLCs reduce the intersection capacity since driver's travel behavior is influenced by the presence of the cameras. Other contributory factors for the so-called capacity reduction, such as driver population (e.g., familiar vs. unfamiliar drivers) and traffic-mix (e.g., trucks vs. passenger cars) characteristics have been left for future works.
Single Stage Integer Programming Model for Long Term Transit Fleet Resource Allocation
Authors: Sabyasachee Mishra, Tom V. Mathew, and Snehamay Khasnabis (2010)
Report
Synopsis: The authors present a procedure for resource allocation among transit agencies for transit fleet management, specifically focusing on the purchase of new buses and rebuilding of existing buses. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subject to budgetary, policy and other constraints. The problem is solved using Integer Programming (IP) and its application is demonstrated through a case study utilizing actual transit fleet data from the Michigan Department of Transportation.
Planning Support Systems and Planning Across Scales: Comparing Scenarios Using Multiple Regional Delineations and Projections
Authors: Arnab Chakraborty, Sabyasachee Mishra, and Yong Wook Kim (2012)
Report
Synopsis: Planning support systems often employ urban models that simulate and evaluate impacts of plans. Their application to plan making is however, challenging when issues transcend local jurisdictions, and model assumptions are contested by the stakeholders. Neglecting the role of such specifications, especially when they are important and uncertain, can diminish the efficacy of plans. In this paper, we use the principles of scenario analysis to illustrate the impacts of two such important considerations – forecasts and regional boundaries – on model outcomes and related decisions. We use Montgomery County, MD as a case and leverage a model developed for a larger region, i.e. the state of MD and vicinity. We develop two sets of scenarios – one where the county (a local government) freely competes with its neighboring jurisdictions for development and another where a higher (i.e. a regional or state) level agency controls the extent of development that the county can receive. The scenarios are constructed using different specifications for regional boundaries and also results in different amount of growth in the County – both rare practices in scenario analysis with models. We then compare the outcomes on a set of indicators and draw implications for planning. We conclude with the argument that planning agencies should compare future scenarios not just with different desirability but different sets of assumptions and regional formulations.
Optimal Resource Allocation Among Transit Agencies for Fleet Management
Authors: Tom V. Mathewa, Snehamay Khasnabisb, and Sabyasachee Mishra (2010)
Report
Synopsis: Most transit agencies require government support for the replacement of their aging fleet. A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is presented in this study. The proposed procedure is a 3-dimensional model that includes the choice of a fleet improvement program, agencies that may receive them, and the timing of investments. Earlier efforts to solve this problem involved the application of one or 2-dimensional models for each year of the planning period. These may have resulted in suboptimal solution as the models are blind to the impact of the fleet management program of the subsequent years. Therefore, a new model to address a long-term planning horizon is proposed. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subjected to improvement program and budgetary constraints. Two variants of the problem, one with an annual budget constraint and the other with a single budget constraint for the entire planning period, are formulated. Two independent approaches, namely, branch and bound algorithm and genetic algorithm are used to obtain the solution. An example problem is solved and results are discussed in details. Finally, the model is applied to a large scale real-world problem and a detailed analysis of the results is presented.
A Case for Increased State Role in Transit Planning: Analyzing Land Use and Transit Ridership Connections Using Scenarios
Authors: Arnab Chakraborty and Sabyasachee Mishra (2011)
Report
Synopsis: Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.
Land Use and Transit Ridership Connections: Implications for State-level Planning Agencies
Authors: Arnab Chakraborty and Sabyasachee Mishra (2013)
Report
Synopsis: Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.
A Joint Travel Demand and Environmental Model to Incorporate Emission Pricing for Large Transportation Networks
Authors: Sabyasachee Mishra and Timothy F. Welch (2011)
Report
Synopsis: Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the user’s in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO2 estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing of Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.
A Joint Travel Demand and Environmental Model To Incorporate Emission Pricing For Large Transportation Networks
Authors: Sabyasachee Mishra and Timothy Welch (2012)
Report
Synopsis: Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution that arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the users in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO2 estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.
An Optimization Model for Allocating Resources for Highway Safety Improvement at Urban Intersections
Authors: Sabyasachee Mishra and Snehamay Khasnabis (2012)
Report
Synopsis: The authors present a procedure for allocating resources for implementing safety improvement alternatives at urban intersections over a multi-year planning horizon. The procedure, based upon optimization techniques, attempts to maximize benefits-measured in dollars saved by reducing crashes of different severity categories, subject to budgetary and other constraints. It is presented in two parts (1) a Base case including the objective function and a set of mandatory constraints, and (2) additional policy constraints / special features that can be separately incorporated to the Base case.