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Public transit systems with efficient designs and operating plans can reduce greenhouse gas (GHG) emissions relative to low-occupancy transportation modes, but many current transit systems have not been designed to reduce environmental impacts. This motivates the study of the benefits of design and operational approaches for reducing the environmental impacts of transit systems. For example, transit agencies may replace level-of-service (LOS) by vehicle miles traveled (VMT) as a criterion in evaluating design and operational changes. Previous studies have demonstrated in an idealized singletechnology transit system the potential of reducing GHG emissions by lowering the transit level-of-service (LOS) provided to the users. In this research, we extend the analysis to account for a more realistic case: a transit system with a hierarchical structure (trunk and feeder lines) providing service to a city where demand is elastic. By considering the interactions between the trunk and the feeder systems, the study provides a quantitative basis for designing and operating integrated urban transit systems that can reduce GHG emissions and costs to both transit users and agencies. The study shows that highly elastic transit demand may cancel emission reduction potentials resulting from lowering LOS, due to demand shifts to lower occupancy vehicles, causing unintended consequences. However, for mass transit modes, these potentials are still significant. Transit networks with buses, bus rapid transit or light rail as trunk modes should be designed and operated near the cost-optimal point when the demand is highly elastic, while this is not required for metro. We also find that the potential for unintended consequences increases with the size of the city. The results are robust to uncertainties in the costs and emissions parameters. The study also includes a discussion of a current transit system. Since many current transit systems have not yet been optimally designed, it should b

Public transit systems with efficient designs and operating plans can reduce greenhouse gas (GHG) emissions relative to low-occupancy transportation modes, but many current transit systems have not been designed to reduce environmental impacts. This motivates the study of the benefits of design and operational approaches for reducing the environmental impacts of transit systems. For example, transit agencies may replace level-of-service (LOS) by vehicle miles traveled (VMT) as a criterion in evaluating design and operational changes. Previous studies have demonstrated in an idealized singletechnology transit system the potential of reducing GHG emissions by lowering the transit level-of-service (LOS) provided to the users. In this research, we extend the analysis to account for a more realistic case: a transit system with a hierarchical structure (trunk and feeder lines) providing service to a city where demand is elastic. By considering the interactions between the trunk and the feeder systems, the study provides a quantitative basis for designing and operating integrated urban transit systems that can reduce GHG emissions and costs to both transit users and agencies. The study shows that highly elastic transit demand may cancel emission reduction potentials resulting from lowering LOS, due to demand shifts to lower occupancy vehicles, causing unintended consequences. However, for mass transit modes, these potentials are still significant. Transit networks with buses, bus rapid transit or light rail as trunk modes should be designed and operated near the cost-optimal point when the demand is highly elastic, while this is not required for metro. We also find that the potential for unintended consequences increases with the size of the city. The results are robust to uncertainties in the costs and emissions parameters. The study also includes a discussion of a current transit system. Since many current transit systems have not yet been optimally designed, it should b

Different highway agencies use different maintenance strategies. Our research indicates that each agency should compute its own cost estimates of maintenance on the basis of: • the measure of pavement performance that it uses to trigger maintenance (and accordingly, the appropriate value of the axle load power which is not necessarily equal to four), • and the actual maintenance activities and policies that it uses (which are not necessarily thick overlays applied at regular time intervals).If agencies were to move toward more realistic cost estimates, they would be able to better forecast maintenance costs and plan their maintenance programs accordingly. They also could establish fees that would be more equitable across truck sizes and potentially even raise additional needed dollars.

Different highway agencies use different maintenance strategies. Our research indicates that each agency should compute its own cost estimates of maintenance on the basis of: • the measure of pavement performance that it uses to trigger maintenance (and accordingly, the appropriate value of the axle load power which is not necessarily equal to four), • and the actual maintenance activities and policies that it uses (which are not necessarily thick overlays applied at regular time intervals).If agencies were to move toward more realistic cost estimates, they would be able to better forecast maintenance costs and plan their maintenance programs accordingly. They also could establish fees that would be more equitable across truck sizes and potentially even raise additional needed dollars.

As road conditions worsen, users experience an increase in fuel consumption and vehicle wear and tear. This increases the costs incurred by the drivers, and also increases the amount of greenhouse gases that vehicles emit. Pavement condition can be improved through rehabilitation activities (resurfacing) to reduce the effects on users, but these activities also have significant cost and greenhouse gas emission impacts. The objective of pavement management is to minimize total societal (user and agency) costs. However, the environmental impacts associated with the cost-minimizing policy are not currently accounted for. Preliminary research has shown that the optimal policies for minimizing total costs and for minimizing total emissions do not coincide. Instead, there exists a range of potentially optimal decisions, known as the Pareto curve, in which it is not possible to decrease total emissions without increasing total costs and vice versa. The first part of the dissertation explores these tradeoffs for a system of pavement segments, taking the approach of an agency who looks to minimize their total costs subject to an emissions constraint. This expands on the existing literature where environmental aspects and costs had only been examined at a single facility level. Other pavement management optimization techniques either did not include costs, or did not examine tradeoffs between costs and environmental aspects. For a case study, a network was created from a subset of California’s highways using available traffic data. The first step was to look at policies that have been used in practice. Caltrans applies a universal trigger roughness policy, which is a policy where all roads in the network are treated the same. Whenever any road reaches the designated trigger roughness value, it will be rehabilitated, independent of road geometry and traffic. The past policy by Caltrans used a trigger roughness value of 3.5 m/km and the current value is 2.7 m/km. Moving from th

This dissertation presents a methodology for the joint optimization of a variety of pavement construction and management activities for segment and system problems under multiple budget constraints. The objective of pavement management is to minimize the total discounted life time costs for the agency and the highway users by finding optimal policies. The scope of the dissertation is focused on continuous time and continuous state formulations of pavement condition. We use a history-dependent pavement deterioration model to account for the influence of history on the deterioration rate. Three topics, representing different aspects of the problem are covered in the dissertation. In the first part, the subject is the joint optimization of pavement design, maintenance and rehabilitation (M&R) strategies for the segment-level problem. A combination of analytical and numerical tools is proposed to solve the problem. In the second part of the dissertation, we present a methodology for the joint optimization of pavement maintenance, rehabilitation and reconstruction (MR&R) activities for the segment-level problem. The majority of existing Pavement Management Systems (PMS) do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damage in the underlying layers (base, sub-base or subgrade). We propose dynamic programming solutions using an augmented state which includes current surface condition and age. In the third part, we propose a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. Within a bottom-up solution approach, Genetic Algorithm (GA) is adopted. The complexity of the algorithm is polynomial in the size of the system and the policy-related parameters.

As road conditions worsen, users experience an increase in fuel consumption and vehicle wear and tear. This increases the costs incurred by the drivers, and also increases the amount of greenhouse gases that vehicles emit. Pavement condition can be improved through rehabilitation activities (resurfacing) to reduce the effects on users, but these activities also have significant cost and greenhouse gas emission impacts. The objective of pavement management is to minimize total societal (user and agency) costs. However, the environmental impacts associated with the cost-minimizing policy are not currently accounted for. Preliminary research has shown that the optimal policies for minimizing total costs and for minimizing total emissions do not coincide. Instead, there exists a range of potentially optimal decisions, known as the Pareto curve, in which it is not possible to decrease total emissions without increasing total costs and vice versa. The first part of the dissertation explores these tradeoffs for a system of pavement segments, taking the approach of an agency who looks to minimize their total costs subject to an emissions constraint. This expands on the existing literature where environmental aspects and costs had only been examined at a single facility level. Other pavement management optimization techniques either did not include costs, or did not examine tradeoffs between costs and environmental aspects. For a case study, a network was created from a subset of California’s highways using available traffic data. The first step was to look at policies that have been used in practice. Caltrans applies a universal trigger roughness policy, which is a policy where all roads in the network are treated the same. Whenever any road reaches the designated trigger roughness value, it will be rehabilitated, independent of road geometry and traffic. The past policy by Caltrans used a trigger roughness value of 3.5 m/km and the current value is 2.7 m/km. Moving from th

This dissertation presents a methodology for the joint optimization of a variety of pavement construction and management activities for segment and system problems under multiple budget constraints. The objective of pavement management is to minimize the total discounted life time costs for the agency and the highway users by finding optimal policies. The scope of the dissertation is focused on continuous time and continuous state formulations of pavement condition. We use a history-dependent pavement deterioration model to account for the influence of history on the deterioration rate. Three topics, representing different aspects of the problem are covered in the dissertation. In the first part, the subject is the joint optimization of pavement design, maintenance and rehabilitation (M&R) strategies for the segment-level problem. A combination of analytical and numerical tools is proposed to solve the problem. In the second part of the dissertation, we present a methodology for the joint optimization of pavement maintenance, rehabilitation and reconstruction (MR&R) activities for the segment-level problem. The majority of existing Pavement Management Systems (PMS) do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damage in the underlying layers (base, sub-base or subgrade). We propose dynamic programming solutions using an augmented state which includes current surface condition and age. In the third part, we propose a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. Within a bottom-up solution approach, Genetic Algorithm (GA) is adopted. The complexity of the algorithm is polynomial in the size of the system and the policy-related parameters.

In 2012, over 25% of the bridges in the United States were rated as structurally deficient or functionally obsolete. Moreover, 35% of bridges are serving beyond their theoretical design lifespan and the number has been projected to increase over the next decade. The imperative needs of improving the overall condition of the bridge system has been impeded by the shortage of funding available for bridge repairs and maintenance. In 2006 the gap between Federal Highway Administration's (FHWA) estimates to eliminate the bridge maintenance backlog and the actual appropriations to bridges for repairs and maintenance from the Highway Bridge Program was $43.4 Billion. In 2009, the gap increased to $65.7 Billion. Such conflict has made effective bridge management more critical than ever. In bridge management, agencies collect bridge condition data and develop deterioration models that predict the bridges' future conditions and associated costs, based on which maintenance, rehabilitation and reconstruction (MR&R) decisions are made. It is therefore critical to have accurate deterioration models. However, limited availability of data and incomplete understanding of the deterioration process result in inaccurate models, which lead to sub-optimal MR&R decisions and significant cost increases. To address the inaccuracy stemming from limited bridge condition data, researchers have proposed Adaptive Control (AC) methods that update the deterioration models successively as new data become available. The underlying belief is that agencies can obtain more accurate deterioration models through updating and subsequently improve their MR&R decisions and achieve cost savings. State-of-the-art bridge management systems, such as Pontis, use a class of AC procedures known as Certainty Equivalent Control (CEC). The procedure used in Pontis updates the transition probabilities (i.e., the parameters of the component deterioration models) after each condition survey, and uses the upda

In response to the growing climate change problem, many governments around the world are seeking ways to reduce the greenhouse gas (GHG) emissions of various sectors of the economy. The trucking sector is important in meeting this challenge in the US because it is responsible for a share of emissions that is significant and rapidly growing. For governments to intervene in this sector smartly, they need models that capture its key incentives, constraints and dynamics, while making the most out of the limited data available. However, existing models fall short of this ideal. This dissertation first introduces the Trucking Sector Optimization Model (TSO) as a tool for studying the decisions that carriers and shippers make within a short-run time horizon--modeling the dynamics of truck fleets, penetration rate of Fuel Saving Technologies (FSTs) such as aerodynamic improvements and low rolling resistance tires, and changes in the demand of trucking. In addition to estimating tailpipe GHG emissions, the model also estimates emissions from upstream fuel production sources, vehicle manufacturing, and pavement rehabilitation activities. This model is then used to evaluate the effectiveness of various incentives-based and regulation-based strategies that California's government could implement in the trucking sector to help achieve the objectives of the Global Warming Solutions Act of 2006 (AB 32). The strategies analyzed are: fuel taxation, mileage taxation, truck purchase taxation, FST subsidies, FST regulations, increases in the allowed weight of trucks, and the Low Carbon Fuel Standard recently introduced in California. Results indicate that there presently exist significant economic incentives for carriers to invest in FSTs beyond what is currently commonplace. The correction of market mechanisms that are responsible for this apparently suboptimal behavior, would lead to significant reductions in emissions, and would also allow for incentive-based strategies to have thei

Public transit is often touted as a "green" transportation option and a way for users to reduce their environmental footprint by avoiding automobile emissions. Many transit systems, however, have considerable emissions, and when vehicles run with ridership significantly below capacity, the per-passenger-kilometer emissions can be greater than for automobile. Efforts to reduce public transit emissions have centered on shifting users from more polluting modes and improving technology either by retrofitting existing vehicles or replacing them with more efficient models. I explore an approach to optimizing the design and operations of transit systems for both costs and emissions using continuum approximation models. The research identifies the Pareto frontier for designing an idealized transit network, and compares transit modes, including bus, bus rapid transit, light rail, and metro heavy rail, over four city scenarios. The slope at any point on the Pareto curve represents the cost of decreasing emissions by another unit, and this can be used to identify an emissions level that is equal to the market value of carbon. Further, I explore how the level of service for users impacts emissions: first, comparing modes at a given emissions level to see which provides the best service to users in terms of average travel time; second, incorporating travel time elasticities into the optimization to allow demand to reduce subject to increases in the travel time. Results of the parametric analysis suggest that a BRT system is a low cost and low emissions transit option for many types of cities. Choosing GHG reduction levels based on the market price of carbon has a small impact on user travel time, so further reductions may be reasonable. In general, the lowest-cost mode will provide the fastest travel time to users at a given emissions level. When shifting demand is accounted for, emissions reductions are moderated, but not eliminated, by the increase in automobile emissions when

In 2012, over 25% of the bridges in the United States were rated as structurally deficient or functionally obsolete. Moreover, 35% of bridges are serving beyond their theoretical design lifespan and the number has been projected to increase over the next decade. The imperative needs of improving the overall condition of the bridge system has been impeded by the shortage of funding available for bridge repairs and maintenance. In 2006 the gap between Federal Highway Administration's (FHWA) estimates to eliminate the bridge maintenance backlog and the actual appropriations to bridges for repairs and maintenance from the Highway Bridge Program was $43.4 Billion. In 2009, the gap increased to $65.7 Billion. Such conflict has made effective bridge management more critical than ever. In bridge management, agencies collect bridge condition data and develop deterioration models that predict the bridges' future conditions and associated costs, based on which maintenance, rehabilitation and reconstruction (MR&R) decisions are made. It is therefore critical to have accurate deterioration models. However, limited availability of data and incomplete understanding of the deterioration process result in inaccurate models, which lead to sub-optimal MR&R decisions and significant cost increases. To address the inaccuracy stemming from limited bridge condition data, researchers have proposed Adaptive Control (AC) methods that update the deterioration models successively as new data become available. The underlying belief is that agencies can obtain more accurate deterioration models through updating and subsequently improve their MR&R decisions and achieve cost savings. State-of-the-art bridge management systems, such as Pontis, use a class of AC procedures known as Certainty Equivalent Control (CEC). The procedure used in Pontis updates the transition probabilities (i.e., the parameters of the component deterioration models) after each condition survey, and uses the upda

In response to the growing climate change problem, many governments around the world are seeking ways to reduce the greenhouse gas (GHG) emissions of various sectors of the economy. The trucking sector is important in meeting this challenge in the US because it is responsible for a share of emissions that is significant and rapidly growing. For governments to intervene in this sector smartly, they need models that capture its key incentives, constraints and dynamics, while making the most out of the limited data available. However, existing models fall short of this ideal. This dissertation first introduces the Trucking Sector Optimization Model (TSO) as a tool for studying the decisions that carriers and shippers make within a short-run time horizon--modeling the dynamics of truck fleets, penetration rate of Fuel Saving Technologies (FSTs) such as aerodynamic improvements and low rolling resistance tires, and changes in the demand of trucking. In addition to estimating tailpipe GHG emissions, the model also estimates emissions from upstream fuel production sources, vehicle manufacturing, and pavement rehabilitation activities. This model is then used to evaluate the effectiveness of various incentives-based and regulation-based strategies that California's government could implement in the trucking sector to help achieve the objectives of the Global Warming Solutions Act of 2006 (AB 32). The strategies analyzed are: fuel taxation, mileage taxation, truck purchase taxation, FST subsidies, FST regulations, increases in the allowed weight of trucks, and the Low Carbon Fuel Standard recently introduced in California. Results indicate that there presently exist significant economic incentives for carriers to invest in FSTs beyond what is currently commonplace. The correction of market mechanisms that are responsible for this apparently suboptimal behavior, would lead to significant reductions in emissions, and would also allow for incentive-based strategies to have thei

Public transit is often touted as a "green" transportation option and a way for users to reduce their environmental footprint by avoiding automobile emissions. Many transit systems, however, have considerable emissions, and when vehicles run with ridership significantly below capacity, the per-passenger-kilometer emissions can be greater than for automobile. Efforts to reduce public transit emissions have centered on shifting users from more polluting modes and improving technology either by retrofitting existing vehicles or replacing them with more efficient models. I explore an approach to optimizing the design and operations of transit systems for both costs and emissions using continuum approximation models. The research identifies the Pareto frontier for designing an idealized transit network, and compares transit modes, including bus, bus rapid transit, light rail, and metro heavy rail, over four city scenarios. The slope at any point on the Pareto curve represents the cost of decreasing emissions by another unit, and this can be used to identify an emissions level that is equal to the market value of carbon. Further, I explore how the level of service for users impacts emissions: first, comparing modes at a given emissions level to see which provides the best service to users in terms of average travel time; second, incorporating travel time elasticities into the optimization to allow demand to reduce subject to increases in the travel time. Results of the parametric analysis suggest that a BRT system is a low cost and low emissions transit option for many types of cities. Choosing GHG reduction levels based on the market price of carbon has a small impact on user travel time, so further reductions may be reasonable. In general, the lowest-cost mode will provide the fastest travel time to users at a given emissions level. When shifting demand is accounted for, emissions reductions are moderated, but not eliminated, by the increase in automobile emissions when

An urban transit system can be made more cost-efficient by improving the access to it. Efforts in this vein often entail the provision of greater mobility, as when high-speed feeder buses are used to carry commuters to and from trunk-line stations. Other efforts have focused on the creation of more favorable land-use patterns, as occurs when households within a Transit-Oriented Development (TOD) are tightly clustered around trunk stations. The efficacy of these mobility and land-use solutions are separately examined in the present work. To this end, continuum approximation models are used to design idealized transit systems that minimize the generalized costs to both the users and the operators of those systems. The assessments unveil how the choice of rolling-stock for the trunk-line portion of a transit network can be influenced by its access mode. If transit is accessed solely (and slowly) on foot, then the optimal spacings between lines, and between the stations along those lines, are small. This can place capital-intensive rail systems at a competitive disadvantage with transit systems that feature buses instead. When access speeds increase, the optimal spacings between lines and stops expand as well. Hence, if accessed by fast-moving feeder buses, Metro-rail or bus-rapid transit can become preferred trunk-line options. By comparison, the influence of altered land use patterns brought by TODs was found to be less dramatic. While clustering households around Metro-rail stations justifies larger spacings between the stations, it yields only modest reductions in generalized costs because the larger spacings penalize transit users who reside outside of the TODs.

This report evaluates the performance of Continuous Risk Profile (CRP) compared with the Sliding Window Method (SWM) and Peak Searching (PS) methods. These three network screening methods all require the same inputs: traffic collision data and Safety Performance Functions (SPFs), however, depending on how these input parameters are analyzed at the network screening level, the result of the analysis can vary significantly. Findings indicated that the CRP method produced far fewer false positives than SWM and PS. The false negative rates for CRP, SWM and PS were comparable. These findings indicate that by using the CRP method, California Department of Transportation (Caltrans) can significantly reduce the resources spent on investigating falsely identified locations and better utilize the resources in improving high collision concentration locations. It will also help Caltrans in reducing the backlog in Caltrans Table C.

This report evaluates the performance of Continuous Risk Profile (CRP) compared with the Sliding Window Method (SWM) and Peak Searching (PS) methods. These three network screening methods all require the same inputs: traffic collision data and Safety Performance Functions (SPFs), however, depending on how these input parameters are analyzed at the network screening level, the result of the analysis can vary significantly. Findings indicated that the CRP method produced far fewer false positives than SWM and PS. The false negative rates for CRP, SWM and PS were comparable. These findings indicate that by using the CRP method, California Department of Transportation (Caltrans) can significantly reduce the resources spent on investigating falsely identified locations and better utilize the resources in improving high collision concentration locations. It will also help Caltrans in reducing the backlog in Caltrans Table C.

An urban transit system can be made more cost-efficient by improving the access to it. Efforts in this vein often entail the provision of greater mobility, as when high-speed feeder buses are used to carry commuters to and from trunk-line stations. Other efforts have focused on the creation of more favorable land-use patterns, as occurs when households within a Transit-Oriented Development (TOD) are tightly clustered around trunk stations. The efficacy of these mobility and land-use solutions are separately examined in the present work. To this end, continuum approximation models are used to design idealized transit systems that minimize the generalized costs to both the users and the operators of those systems. The assessments unveil how the choice of rolling-stock for the trunk-line portion of a transit network can be influenced by its access mode. If transit is accessed solely (and slowly) on foot, then the optimal spacings between lines, and between the stations along those lines, are small. This can place capital-intensive rail systems at a competitive disadvantage with transit systems that feature buses instead. When access speeds increase, the optimal spacings between lines and stops expand as well. Hence, if accessed by fast-moving feeder buses, Metro-rail or bus-rapid transit can become preferred trunk-line options. By comparison, the influence of altered land use patterns brought by TODs was found to be less dramatic. While clustering households around Metro-rail stations justifies larger spacings between the stations, it yields only modest reductions in generalized costs because the larger spacings penalize transit users who reside outside of the TODs.

In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

This report summarizes the layout and content of a website created for the CEC to make the information in the Energy Aware Planning Guide readily available to California cities and counties, to assist them in their efforts to reduce energy use. The website consists of an electronic version of the entire Planning Guide that allows easy maneuverability among the many sections of the document, and quick downloading of references cited in the document. The website also contains individual briefing pages for 46 land use- and transportation-related measures, including 21 briefs that provide information on additional transportation-related measures that are not specifically identified in the Planning Guide. The website also summarizes estimates of the effectiveness of individual measures described in the briefings, as well as the cost-effectiveness of each measure, derived from a comprehensive national study of the potential to reduce energy use from the transportation sector

The US parking infrastructure is vast and little is known about its scale and environmental impacts. The few parking space inventories that exist are typically regionalized and no known environmental assessment has been performed to determine the energy and emissions from providing this infrastructure. A better understanding of the scale of US parking is necessary to properly value the total costs of automobile travel. Energy and emissions from constructing and maintaining the parking infrastructure should be considered when assessing the total human health and environmental impacts of vehicle travel. We develop five parking space inventory scenarios and from these estimate the range of infrastructure provided in the US to be between 105 million and 2 billion spaces. Using these estimates, a life-cycle environmental inventory is performed to capture the energy consumption and emissions of greenhouse gases, CO, SO2, NOX, VOC (volatile organic compounds), and PM10 (PM: particulate matter) from raw material extraction, transport, asphalt and concrete production, and placement (including direct, indirect, and supply chain processes) of space construction and maintenance. The environmental assessment is then evaluated within the life-cycle performance of sedans, SUVs (sports utility vehicles), and pickups. Depending on the scenario and vehicle type, the inclusion of parking within the overall life-cycle inventory increases energy consumption from 3.1 to 4.8 MJ by 0.1–0.3 MJ and greenhouse gas emissions from 230 to 380 g CO2e by 6–23 g CO2e per passenger kilometer traveled. Life-cycle automobile SO2 and PM10 emissions show some of the largest increases, by as much as 24% and 89% from the baseline inventory. The environmental consequences of providing the parking spaces are discussed as well as the uncertainty in allocating paved area between parking and roadways.

This paper focuses on the estimation of highway maintenance marginal costs. Highway maintenance marginal cost has been estimated in the literature using the perpetual overlay indirect approach. This approach assumes that pavement overlay costs dominate maintenance costs and ignores other maintenance activities. This paper focuses on two questions. First, is it acceptable to ignore the less costly activities? Second, if multiple maintenance activities are to be considered, is it acceptable to ignore their interdependence? The results show that less costly maintenance activities cannot be ignored. Furthermore, if multiple activities are to be considered, their interdependence should be taken into account.

The paper explores how the coordination of vehicle schedules in a public transit system affects generalized costs. We consider an idealized system that delivers its users to a common destination by requiring each to transfer from a feeder- to a trunk-line vehicle. Continuum models are used first to analyze cases in which the trunk-line vehicle schedule is given exogenously. We find that when feeder vehicles are dispatched in coordination with this exogenous trunk-line schedule, the reduction in user cost often outweighs the added cost to the feeder operation. In cases when the frequencies of trunk and feeder services can be established jointly, the models show that coordination can be Pareto improving, meaning that operator and user costs both diminish. Conditions that give rise to these cost savings are specified. Practical implications are discussed.

Local bus operators can reduce costs and better serve their customers by matching service frequencies to those of the regional trunk lines that pass through their jurisdictions. For an entire region, trunk line and local bus operators should coordinate their schedules and the carrying capacities of their fleets. Metropolitan Planning Organizations (MPOs) are in a position to encourage this through their purse-string powers and ability to provide financial incentives. For future investments, facilities should be designed to allow quick and efficient transfers not just between the same types of vehicles (e.g. cross-platform transfers for rail systems), but also between different types of vehicles across different systems (e.g. small feeder buses and commuter rail lines).Before implementing these changes, several issues should be considered. One, additional costs will likely be incurred for technologies that improve scheduling and for upgrading stations. Also, improved bus-rail coordination can lengthen headways, thus reducing the frequency of services. Additionally, not all local feeder bus riders are destined for trunk line stops. Thus, the benefits of coordination should be weighed against the additional waiting times experienced by those riders.

This paper focuses on the estimation of highway maintenance marginal costs. Highway maintenance marginal cost has been estimated in the literature using the perpetual overlay indirect approach. This approach assumes that pavement overlay costs dominate maintenance costs and ignores other maintenance activities. This paper focuses on two questions. First, is it acceptable to ignore the less costly activities? Second, if multiple maintenance activities are to be considered, is it acceptable to ignore their interdependence? The results show that less costly maintenance activities cannot be ignored. Furthermore, if multiple activities are to be considered, their interdependence should be taken into account.

The paper explores how the coordination of vehicle schedules in a public transit system affects generalized costs. We consider an idealized system that delivers its users to a common destination by requiring each to transfer from a feeder- to a trunk-line vehicle. Continuum models are used first to analyze cases in which the trunk-line vehicle schedule is given exogenously. We find that when feeder vehicles are dispatched in coordination with this exogenous trunk-line schedule, the reduction in user cost often outweighs the added cost to the feeder operation. In cases when the frequencies of trunk and feeder services can be established jointly, the models show that coordination can be Pareto improving, meaning that operator and user costs both diminish. Conditions that give rise to these cost savings are specified. Practical implications are discussed.

Local bus operators can reduce costs and better serve their customers by matching service frequencies to those of the regional trunk lines that pass through their jurisdictions. For an entire region, trunk line and local bus operators should coordinate their schedules and the carrying capacities of their fleets. Metropolitan Planning Organizations (MPOs) are in a position to encourage this through their purse-string powers and ability to provide financial incentives. For future investments, facilities should be designed to allow quick and efficient transfers not just between the same types of vehicles (e.g. cross-platform transfers for rail systems), but also between different types of vehicles across different systems (e.g. small feeder buses and commuter rail lines).Before implementing these changes, several issues should be considered. One, additional costs will likely be incurred for technologies that improve scheduling and for upgrading stations. Also, improved bus-rail coordination can lengthen headways, thus reducing the frequency of services. Additionally, not all local feeder bus riders are destined for trunk line stops. Thus, the benefits of coordination should be weighed against the additional waiting times experienced by those riders.

The US parking infrastructure is vast and little is known about its scale and environmental impacts. The few parking space inventories that exist are typically regionalized and no known environmental assessment has been performed to determine the energy and emissions from providing this infrastructure. A better understanding of the scale of US parking is necessary to properly value the total costs of automobile travel. Energy and emissions from constructing and maintaining the parking infrastructure should be considered when assessing the total human health and environmental impacts of vehicle travel. We develop five parking space inventory scenarios and from these estimate the range of infrastructure provided in the US to be between 105 million and 2 billion spaces. Using these estimates, a life-cycle environmental inventory is performed to capture the energy consumption and emissions of greenhouse gases, CO, SO2, NOX, VOC (volatile organic compounds), and PM10 (PM: particulate matter) from raw material extraction, transport, asphalt and concrete production, and placement (including direct, indirect, and supply chain processes) of space construction and maintenance. The environmental assessment is then evaluated within the life-cycle performance of sedans, SUVs (sports utility vehicles), and pickups. Depending on the scenario and vehicle type, the inclusion of parking within the overall life-cycle inventory increases energy consumption from 3.1 to 4.8 MJ by 0.1–0.3 MJ and greenhouse gas emissions from 230 to 380 g CO2e by 6–23 g CO2e per passenger kilometer traveled. Life-cycle automobile SO2 and PM10 emissions show some of the largest increases, by as much as 24% and 89% from the baseline inventory. The environmental consequences of providing the parking spaces are discussed as well as the uncertainty in allocating paved area between parking and roadways.

This report summarizes the layout and content of a website created for the CEC to make the information in the Energy Aware Planning Guide readily available to California cities and counties, to assist them in their efforts to reduce energy use. The website consists of an electronic version of the entire Planning Guide that allows easy maneuverability among the many sections of the document, and quick downloading of references cited in the document. The website also contains individual briefing pages for 46 land use- and transportation-related measures, including 21 briefs that provide information on additional transportation-related measures that are not specifically identified in the Planning Guide. The website also summarizes estimates of the effectiveness of individual measures described in the briefings, as well as the cost-effectiveness of each measure, derived from a comprehensive national study of the potential to reduce energy use from the transportation sector

This paper documents a new method for monitoring traffic collision data from continuous roadway facilities to detect high collision concentration locations. Many existing methods for detecting collision concentration locations require segmentation of roadways and assume traffic collision data are spatially uncorrelated, resulting in both false positives (i.e., identifying sites for safety improvements that should not have been selected) and false negatives (i.e., not identifying sites that should have been selected). The proposed method does not require segmentation of roadways; spatial correlation in the collision data does not affect the results of analysis. This new method has a lower false positive rate than the conventional sliding moving window approach. This paper shows how the proposed method can proactively identify high collision concentration locations and capture the benefit of safety improvements observed in the project location and in neighboring sites.

In recent years, the reduction of freight vehicle trips during peak hours has been a common policy goal. To this end, policies have been implemented to shift logistics operations to nighttime hours. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, the atmospheric boundary layer is generally more stable during the night than the day. Consequently, shifting logistics operations to the night may increase 24‐hour average concentrations of diesel exhaust pollutants in many locations. This paper presents realistic scenarios for two California cities, which provide exhaust concentration and human intake estimates after temporal redistributions of daily logistics operations. Estimates are made for multiple redistribution patterns, including from 07:00‐19:00 to 19:00‐0:700, similar to daytime congestion charging polices and from 03:00‐18:00 to 18:00‐03:00, corresponding to the PierPASS program at the ports of Los Angeles and Long Beach. Results for these two redistribution scenarios indicate that 24‐hour average exhaust concentrations would increase at most locations in California, and daily human intake is likely to worsen or be unimproved at best. These results are shown to be worse for inland than coastal settings, due to differences in meteorology. Traffic congestion effects are accounted for, using a new graphical method, which depicts how off‐peak policies can be environmentally improving or damaging, depending on traffic speeds and meteorology. An investigation into the decreasing marginal environmental benefits of off‐policies is then provided, through the application of traffic flow theory. Finally, related environmental and human exposure concerns are considered to provide a comprehensive policy discussion of the environmental effects of shifting logistics operations from day to night.

In recent years, the reduction of freight truck trips has been a common policy goal. To this end, policies aimed at influencing load consolidation, load factors and increasing maximum truck weight limits have been suggested and implemented, resulting in higher gross vehicle weights. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, trucks cause most of the damage incurred by highways pavements. The supply chain associated with pavement maintenance and construction releases significant air emissions, raising the question of whether increased vehicle weights may cause unintended environmental consequences. This paper presents case examples with estimated emissions resulting from shifts in load consolidation and increased maximum weight. These examples indicate that increased load factors in local and long-distance freight movement can cause significant increases in emissions of certain pollutants. Emissions associated with pavement construction are also found to increase as a result of pavement design specifications that account for heavier trucks.

In recent years, the reduction of freight truck trips has been a common policy goal. To this end, policies aimed at influencing load consolidation, load factors and increasing maximum truck weight limits have been suggested and implemented, resulting in higher gross vehicle weights. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, trucks cause most of the damage incurred by pavements. The supply chain associated with pavement maintenance and construction releases significant air emissions, raising the question of whether increased vehicle weights may cause unintended environmental consequences. This paper presents scenarios with estimated emissions resulting from load consolidation and changes in load factors. These scenarios reveal several points having to do with the tradeoff between tailpipe versus pavement supply‐chain emissions. In some cases, unintended emissions from the pavement supply‐chain are found to be significant. Emissions associated with pavement construction are also found to increase as a result of pavement design specifications that account for heavier trucks.

In recent years, the reduction of freight truck trips has been a common policy goal. To this end, policies aimed at influencing load consolidation, load factors and increasing maximum truck weight limits have been suggested and implemented, resulting in higher gross vehicle weights. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, trucks cause most of the damage incurred by highways pavements. The supply chain associated with pavement maintenance and construction releases significant air emissions, raising the question of whether increased vehicle weights may cause unintended environmental consequences. This paper presents case examples with estimated emissions resulting from shifts in load consolidation and increased maximum weight. These examples indicate that increased load factors in local and long-distance freight movement can cause significant increases in emissions of certain pollutants. Emissions associated with pavement construction are also found to increase as a result of pavement design specifications that account for heavier trucks.

In recent years, the reduction of freight truck trips has been a common policy goal. To this end, policies aimed at influencing load consolidation, load factors and increasing maximum truck weight limits have been suggested and implemented, resulting in higher gross vehicle weights. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, trucks cause most of the damage incurred by pavements. The supply chain associated with pavement maintenance and construction releases significant air emissions, raising the question of whether increased vehicle weights may cause unintended environmental consequences. This paper presents scenarios with estimated emissions resulting from load consolidation and changes in load factors. These scenarios reveal several points having to do with the tradeoff between tailpipe versus pavement supply‐chain emissions. In some cases, unintended emissions from the pavement supply‐chain are found to be significant. Emissions associated with pavement construction are also found to increase as a result of pavement design specifications that account for heavier trucks.

In recent years, the reduction of freight vehicle trips during peak hours has been a common policy goal. To this end, policies have been implemented to shift logistics operations to nighttime hours. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, the atmospheric boundary layer is generally more stable during the night than the day. Consequently, shifting logistics operations to the night may increase 24‐hour average concentrations of diesel exhaust pollutants in many locations. This paper presents realistic scenarios for two California cities, which provide exhaust concentration and human intake estimates after temporal redistributions of daily logistics operations. Estimates are made for multiple redistribution patterns, including from 07:00‐19:00 to 19:00‐0:700, similar to daytime congestion charging polices and from 03:00‐18:00 to 18:00‐03:00, corresponding to the PierPASS program at the ports of Los Angeles and Long Beach. Results for these two redistribution scenarios indicate that 24‐hour average exhaust concentrations would increase at most locations in California, and daily human intake is likely to worsen or be unimproved at best. These results are shown to be worse for inland than coastal settings, due to differences in meteorology. Traffic congestion effects are accounted for, using a new graphical method, which depicts how off‐peak policies can be environmentally improving or damaging, depending on traffic speeds and meteorology. An investigation into the decreasing marginal environmental benefits of off‐policies is then provided, through the application of traffic flow theory. Finally, related environmental and human exposure concerns are considered to provide a comprehensive policy discussion of the environmental effects of shifting logistics operations from day to night.

This paper documents a new method for monitoring traffic collision data from continuous roadway facilities to detect high collision concentration locations. Many existing methods for detecting collision concentration locations require segmentation of roadways and assume traffic collision data are spatially uncorrelated, resulting in both false positives (i.e., identifying sites for safety improvements that should not have been selected) and false negatives (i.e., not identifying sites that should have been selected). The proposed method does not require segmentation of roadways; spatial correlation in the collision data does not affect the results of analysis. This new method has a lower false positive rate than the conventional sliding moving window approach. This paper shows how the proposed method can proactively identify high collision concentration locations and capture the benefit of safety improvements observed in the project location and in neighboring sites.

Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent bridge component deterioration. In existing Markovian models, the state is the bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and maintenance as part of the model. This model is then used to formulate and solve a reliability-based bridge maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.

Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent bridge component deterioration. In existing Markovian models, the state is the bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and maintenance as part of the model. This model is then used to formulate and solve a reliability-based bridge maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.

This paper presents a discussion directed at determining the most progressive options for shifting the freight logistics industry towards having more sustainable-oriented goals. The authors first discuss transportation sustainability and the concept of green logistics. This is followed by a discussion on externalities resulting from vehicle emissions and indirect environmental externalities. The problem of environmental externalities is then examined, with focus on emissions and other related data. The authors then examine options for reducing environmental externalities. They discuss impact considerations, options focused on emissions reduction, changing freight sector operations, and considerations regarding demand and economic development.

This paper presents a discussion directed at determining the most progressive options for shifting the freight logistics industry towards having more sustainable-oriented goals. The authors first discuss transportation sustainability and the concept of green logistics. This is followed by a discussion on externalities resulting from vehicle emissions and indirect environmental externalities. The problem of environmental externalities is then examined, with focus on emissions and other related data. The authors then examine options for reducing environmental externalities. They discuss impact considerations, options focused on emissions reduction, changing freight sector operations, and considerations regarding demand and economic development.

The network-level infrastructure management problem involves selecting and scheduling Maintenance, Repair, and Rehabilitation (MR&R) activities on networks of infrastructure facilities so as to maintain the level of service provided by the network in a cost-effective manner. This problem is frequently formulated as a Markov Decision Problem (MDP) solved via Linear Programming (LP). The conditions of facilities are represented by elements of discrete condition rating sets, and transition probabilities are employed to describe deterioration processes. Epistemic and parametric uncertainties not considered within the standard MDP/LP framework are associated with the transition probabilities used in infrastructure management optimization routines. This paper contrasts the expected costs incurred when model uncertainty is ignored with those incurred when this uncertainty is explicitly considered using Robust Optimization. A case study involving a network-level pavement management MDP/LP problem demonstrates how explicitly considering uncertainty may limit worst case MR&R expenditures. The methods and results can also be used to identify the costs of uncertainty in transition probability matrices used in infrastructure management systems.

Asset management systems help public works agencies decide when and how to maintain and rehabilitate infrastructure facilities in a cost-effective manner. Many sources of error, some difficult to quantify, can limit the ability of asset management systems to accurately predict how built systems will deteriorate. This paper introduces the use of robust optimization to deal with epistemic uncertainty. The Hurwicz criterion is employed to ensure management policies are never ‘too conservative.’ An efficient solution algorithm is developed to solve robust counterparts of the asset management problem. A case study demonstrates how the consideration of uncertainty alters optimal management policies and shows how the proposed approach may reduce maintenance and rehabilitation (M&R) expenditures.