working paper

Real-World CO2 Impacts of Traffic Congestion

Publication Date

February 29, 2008

Author(s)

Matthew Barth, Kanok Boriboonsomsin

Areas of Expertise

Transportation Economics， Funding， & Finance, Infrastructure Delivery， Operations， & Resilience, Intelligent Transportation Systems， Emerging Technologies， & Big Data

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Abstract

Transportation plays a significant role in carbon dioxide (CO2) emissions, accounting for approximately a third of the United States’ inventory. In order to reduce CO2 emissions in the future, transportation policy makers are looking to make vehicles more efficient and increasing the use of carbon-neutral alternative fuels. In addition, CO2 emissions can be lowered by improving traffic operations, specifically through the reduction of traffic congestion. This paper examines traffic congestion and its impact on CO2 emissions using detailed energy and emission models and linking them to real-world driving patterns and traffic conditions. Using a typical traffic condition in Southern California as example, it has been found that CO2 emissions can be reduced by up to almost 20% through three different strategies: 1) congestion mitigation strategies that reduce severe congestion, allowing traffic to flow at better speeds; 2) speed management techniques that reduce excessively high free-flow speeds to more moderate conditions; and 3) shock wave suppression techniques that eliminate the acceleration/deceleration events associated with stop-and-go traffic that exists during congested conditions.

Phd Dissertation

Realistic models for scheduling tasks on network nodes

Publication Date

May 31, 2008

Author(s)

Jie Hu

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

Parallel distributed computing has been widely studied and utilized to enable grids (or clusters) to meet the increasing demand of computation, especially in the field of scientific computation and modeling. The goal of distributed computing platforms is to provide the necessary infrastructure so that applications and their users can aggregate resources dynamically and shorten the processing time of the applications. With the rapid development of the Internet, the current distributed computing platforms are becoming more complicated. A typical type of modern distributed computing platforms is grid. Because the modern distributed computing platforms may contain numerous computational network nodes, one important challenge is how to schedule the load of tasks to these network nodes efficiently [1]. In addition, the environments of current computational platforms are becoming more complicated due to the availability of high performance network nodes and interconnects. Therefore, more advanced scheduling algorithms should be utilized to handle these problems. It is therefore necessary to create a new generation of schedulers that provides more comprehensive support for addressing the modern distributed computing platform requirements, so that the network nodes can be utilized effectively By analyzing and identifying the limitations of applying conventional scheduler technologies for distributed parallel applications, this dissertation presents a new design and its associated algorithms for enhancing conventional schedulers to provide better performance with considering more realistic factors. This dissertation also presents both mathematical and empirical analysis of three different proposed models. This dissertation provides three contributions to the field of task scheduling in distributed computing. First, current published algorithms are analyzed and weakness are exposed when real-world factors are considered, such as startup-costs, arbitrary processor times. Second, it contributes to the design of the scheduling algorithms by considering more realistic factors, which extend the usages of schedulers. Finally, it presents empirical and analytical results to demonstrate the effectiveness and the advantage of the proposed algorithms. The work in this dissertation has a broader impact beyond the algorithms in which they were developed, as it provides deeper understanding of scheduling tasks in the more realistic models, which will allow us to design more efficient algorithms.

Phd Dissertation

Activity-based Travel Demand Model with Time-use and Microsimulation Incorporating Intra-Household Interactions

Publication Date

February 4, 2008

Author(s)

Hee-Hyung Kim

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

The activity-based travel demand model recognizes that travel is derived from the demand for activity participation distributed in space and time. The focus on intrahousehold interactions and linkages between people’s behavior and social and physical environment has been identified as emerging features of the activity-based approach that would be important to travel behavior research. The dissertation is dedicated to an indepth exploration of the within-household interactions by theoretical specification and empirical development of the household activity time allocation models based on a utility maximization framework with the household as the unit of analysis. Furthermore, the dissertation also aims to propose a model of the household activity scheduling process primarily focusing on task allocation mechanisms on the basis of the human agents adjusting themselves to the built social and physical environment.

Development of the activity time allocation model in this dissertation includes two types of structural time allocation models. First, the collective models based on two assumptions that household heads have their own utility functions and that decisions by them reach Pareto-efficient outcomes are introduced to develop intra-household activity time allocation models for leisure demand and housework activity. Secondly, intrahousehold time allocation to housework activity is further examined through the estimation of time allocation to the different types of activities by the different types of household members along with extensive exploration of various theories and identification of related interactions.

This dissertation proposes a household activity scheduling process with a model design based on a weekly pattern system, which is expected to keep various advantages compared to a deterministic daily model system. Along with learning and adaptation procedures, the human being as a learning agent is designed to prepare strategic schedules of behavior to achieve individual goals through interactive environments, and implement those plans via activity execution. At the household level, the household and its members as decision agents are also designed to optimize the allocation of the available household labor resource under the presence of the uncertainties of the physical and social environments. After describing the mathematical framework and solution procedure, a simulation experiment is conducted within a hypothetical environment to demonstrate how the proposed model works.

Phd Dissertation

New dynamic travel demand modeling methods in advanced data collecting environments.

Publication Date

January 21, 2008

Author(s)

Hyunmyung Kim

Areas of Expertise

Travel Behavior， Land Use， & the Built Environment, Intelligent Transportation Systems， Emerging Technologies， & Big Data

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Abstract

Estimating and forecasting travel demand have been a popular study topic among transportation researchers; however the research needs to pursue new direction with the advent of data from the potential availability of newer types of data previously not envisaged. In this dissertation, the author reviews previous studies on this topic and develops approaches for two aspects of travel demand analysis in the transportation network: A newer OD estimation method and a household activity-based demand modeling framework. First, a trip-based dynamic OD estimation model is developed. Several previous studies on OD trip table estimation focused on a static problem and many recent dynamic OD estimation methods also have not sufficiently proved their practical applicability. In order to overcome the shortcomings, this dissertation introduces supplementary information (i.e., vehicle trajectory data) to a dynamic OD estimation model. However, the trip-based approach has certain well-known shortcomings. OD estimation results can not give satisfactory solutions for forecasting purposes, and the estimated OD table only contains materialized trips, which implies that no latent travel demand is included in the table. Therefore, the estimated OD table does not have sufficient information for identifying the real travel demand pattern and it is not so useful for transportation planning works. Contrarily, a standard four-step model has a better capability for explaining a travel demand pattern. However, when we load the OD trip table calculated by the four-step model, we might see some discrepancies between simulated traffic patterns and the ground truth. The discrepancies can come from various factors such as insufficient network capacities and unexplained influencing factors. When the discrepancy is caused by insufficient network capacities, then it can be solved by an iterative adjusting procedure. Using the ground truth such as link traffic counts, it might be updated correctly. However, if the discrepancies come from incapability of the four-step model, then we should look for a new approach. The capability of the four-step model already has been criticized continuously by numerous activity researchers because a trip-based approach does not correctly consider the real motivation of travel. To overcome these drawbacks, the second item of fucud in the dissertation is in developing a dynamic agent-based household activity and travel demand simulation model framework named DYNAHAP. The framework calculates a demand pattern in terms of activity chains generated by synthetic families. A traffic simulator then executes the activity chains, and finally an aggregated dynamic traffic pattern is generated. In order to calibrate DYNAHAP, huge activity data should be gathered. Such tasks had been regarded very difficult or even nearly impossible before, but with the development of data collecting technologies, currently we have several ways for collecting the activity chains of individuals. Like vehicle trajectory data, sample activity chains collected from personal communication devices such as PDA (Personal digital assistant) could be used for DYNAHAP calibration. Some numerical test results also will be given for proving the performance of the developed models. In last chapter, some important issues for future study are also discussed.

working paper

Environmental Impacts of a Major Freight Corridor: A study of the I-710 in California

Publication Date

December 31, 2007

Author(s)

Gunwoo Lee, Soyoung (Iris) You, Stephen Ritchie, Jean-Daniel Saphores, Mana Sangkapichai, R. (Jay) Jayakrishnan

Areas of Expertise

Freight， Logistics， & Supply Chain, Zero-Emission Vehicles & Low-Carbon Fuels

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Abstract

The San Pedro Bay Ports (SPBP) of Los Angeles and Long Beach in Southern California comprise one of the largest container port complexes in the world. The SPBP contribute significantly to both regional and national economies in California, and the US, respectively. However, the ongoing growth and economic benefits of the SPBP are threatened by negative externalities associated with port operations, particularly increasing congestion and air pollution. The objective of this paper is to explore a new approach to estimating vehicle emission impacts of freight corridor operations related to the port area, particularly those associated with heavy duty diesel trucks. The approach involves use of a microscopic traffic simulation model to capture detailed vehicle trajectories and congestion effects (ultimately including the effects of Intelligent Transportation System strategies), emissions modeling, and modeling the spatial dispersion of pollutants in the corridor, to facilitate estimation of the health and environmental justice impacts of freight corridor operations. In this paper we focus on operation of the I-710 freeway in the Alameda Corridor, leading from the SPBP area for about 20 miles toward Los Angeles. In a parallel effort we are also studying rail operations in the same corridor. In the future both the rail and highway elements will be combined to form an integrated, overall assessment of air quality impacts in the corridor. In this paper, seven scenarios were evaluated in addition to the 2005 Base Scenario: replacement of the current fleet of port heavy duty diesel trucks with zero emission trucks (25%, 50%, and 100% of port trucks), elimination of port heavy duty diesel truck trips (25%, 50%, and 100% reductions) that would correspond to shifting more containers to other modes such as rail, and implementation of a truck restricted-lane on I-710 preventing trucks from using the left most lanes. The results show that fleet replacement with cleaner trucks yields the most emission reductions both quantitatively and spatially.

working paper

Development of an estimation procedure for an activity-based travel demand model

Publication Date

December 31, 2007

Associated Project

An Activity-Based Assessment of the Potential Impacts of Plug-in Hybrid Electronic Vehicles (PHEV’s) on Energy: Emissions Using One-day Travel Data

Author(s)

Will Recker, Junping Duan

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

In this paper, we implement an estimation procedure for a particular mathematical programming activity-based model in order to estimate the relative importance of factors associated with spatial and temporal interrelationships among the out-of-home activities that motivate a household’s need or desire to travel. The method uses a genetic algorithm to estimate coefficient values of the utility function, based on a particular multidimensional sequence alignment method to deal with the nominal, discrete, attributes of the activity/travel pattern (e.g., which household member performs which activity, which vehicle is used, sequencing of activities), and a time sequence alignment method to handle temporal attributes of the activity pattern (e.g., starting and ending time of each activity and/or travel). The estimation procedure is tested on data drawn from a well-know activity/travel survey.

Related Publications

published journal article | February 05, 2025

Development of an Estimation Procedure for an Activity-Based Travel Demand Model

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working paper

User Characteristics and Reponses to a Shared-Use Station Car Program: An Analysis of ZEV•NET in Orange County, CA

Publication Date

December 31, 2007

Author(s)

Jean-Daniel Saphores, Scott Samuelsen

Areas of Expertise

Travel Behavior， Land Use， & the Built Environment, Public Transit， Shared Mobility， & Active Transportation

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Abstract

Growing concerns about petroleum dependence, greenhouse gas emissions, and traffic congestion make shared-use vehicle programs look increasingly attractive. They offer an alternative to car ownership that yields benefits to their members by lowering the cost of transportation and to society at-large by reducing per capita VMT and increasing the use of public transportation. While neighborhood carsharing programs have already received a lot of attention, station car programs, the other type of shared-use vehicle program, largely have not. In the station car approach, shared vehicles are based at public transportation terminals to “extend” the public transportation network. This paper analyzes responses to a survey of the users of UC-Irvine’s ZEV•NET research program, which employs battery electric vehicles and is managed using information technologies. We find that ZEV•NET users participate in the program because they like the flexibility, the ease of use, and the reliability of ZEV•NET vehicles. ZEV•NET commuters are also more concerned about travel stress, cost, and environmental impacts than those who drive alone. By contrast, the latter place greater value in flexibility, reliability, and to a lesser degree, time. Moreover, the demographic characteristics of ZEV•NET users are not statistically different from those of non-users. As ZEV•NET users are not much more concerned about environmental issues than non-users, just advertising the environmental impacts of this program would not be sufficient to grow ZEV•NET; instead, potential cost advantages should be emphasized. These findings should be useful for designing more station car programs that rely on zero-emitting vehicles.

working paper

A Solution Algorithm for Long Haul Freight Network Design Using Shipper-Carrier Freight Flow Prediction with Explicit Capacity Constraints

Publication Date

December 31, 2007

Author(s)

Pruttipong Apivatanagul, Amelia Regan

Areas of Expertise

Freight, Logistics, & Supply Chain

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Abstract

Freight transportation has long been recognized as an important foundation of economic strength. Previous studies use traditional methods to examine a set of scenarios. However, due to the complexity of transportation projects which can have substitution effects in a network the number of resulting scenarios may be more than can be examined on a case by case basis.

In this paper, a sequential shipper-carrier freight flow prediction model is examined. Additionally, an explicit capacity constraint is used to divert the traffic volume from congested links. A branch and bound method is applied to obtain a solution to our model. We discuss the benefits and limitations of our method, examine its computational efficiency and provide a numerical example. The results show that project selection by the traditional case by case analysis method cannot capture the complexity of freight transportation network improvements and yields the sub-optimal solution.

working paper

An Analysis of PM and NOx Train Emissions in the Alameda Corridor, CA.

Publication Date

December 31, 2007

Author(s)

Mana Sangkapichai, Jean-Daniel Saphores, Stephen Ritchie, Soyoung (Iris) You, Gunwoo Lee

Areas of Expertise

Zero-Emission Vehicles & Low-Carbon Fuels, Freight， Logistics， & Supply Chain

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Abstract

The Alameda corridor provides a crucial rail link for moving freight in and out of the Ports of Los Angeles and Long Beach, also known as the San Pedro Bay Ports (SPBP). While the benefits of this trade are enjoyed by the whole nation, the associated air pollution costs are born mostly by the people who live in the vicinity of the Alameda corridor and the two freeways (the I-710 and the I-110) that serve the Ports. Although they are more energy efficient than trucks, trains contribute heavily to regional air pollution; in addition, rail traffic in the South Coast Air Basin is projected to almost double in the next twenty years. This paper presents an analysis of the emissions and the dispersion of PM and NOx emitted by train operations in and around the Alameda corridor. We find spatial and temporal variations in the dispersion of these pollutants, which justifies our approach. Moreover, the railyards in our study area are responsible for the bulk of PM and NOx emissions (compared to line haul operations). While PM emissions from train operations contribute only a fraction of the recommended maximum concentration, NOx emissions go over recommended guidelines in different areas. The affected population is mostly Latino or African American. Our approach is also useful for better understanding trade-offs between truck and rail freight transport.

working paper

Freight Transportation Electronic Marketplaces: A Survey of the Industry and Exploration of Important Research Issues

Publication Date

December 31, 2007

Author(s)

Srinivas Nandiraju, Amelia Regan

Areas of Expertise

Freight, Logistics, & Supply Chain

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Abstract

B2B e-Commerce facilitates the reduction of supply chain intermediaries and reduces transaction costs. This revolution has spawned a number of online marketplaces for freight transportation service procurement. The paper looks into the operational models of existing electronic freight marketplaces and the strategic behavior of shipper and carriers conducting their business in these market places. A literature survey of market clearing mechanisms models for online freight transportation market places is provided. Models for shipper-carrier strategic interaction are presented for freight transportation procurement. Some of the key research questions for developing methodologies to aid both the shippers and carriers are discussed.