Dissertation Abstracts

Kopitch, Lima. An Analysis of the Impact of an Incident Management System on Secondary Incidents on Freeways – An Application to the I-5 in California PhD, Transportation Science, 2011 117 pp. Adviser: Jean-Daniel Saphores.

Accidents are the largest source of external costs related to transportation in the United States with annual costs estimated to exceed $200 billion per year. Incidents also create traffic backups and delays that can result in secondary incidents (i.e., collisions that occur as a result of other incidents). Although incident management has received a lot of attention from academics and practitioners alike, secondary incidents have so far been somewhat neglected.

The main purpose of this dissertation is to investigate empirically whether the implementation of changeable message signs (CMS), which are one Intelligent Transportation System tool, can reduce secondary collisions. After reviewing previously published methods for estimating secondary accidents, I implement a Binary Speed Contour Map approach to detect secondary incidents using PeMS data. I also estimate the extra time lost to congestion because of incidents.

My study area is a portion of Interstate 5 that stretches 74 miles from the Mexico-US border to Orange County, CA. This freeway has an average annualized daily traffic volume of 230,000 vehicles and fifty-five miles of it are equipped with CMS. My unique dataset includes incident data for 2008 combined with detailed weather data, elements of freeway geometry, and information about CMS usage.

I identify a total of 10,172 incidents in my study area in 2008. Using the BSCM approach, I find that 4.6 percent of collisions were secondary incidents. Moreover, my statistical model shows that incidents occurring during evening peak hours on Fridays are more likely to result in secondary crashes as do more severe incidents, areas with a complex geometry, wet pavement, and changeable message signs (CMS). The maximum effectiveness of a CMS is approximately 10.5 miles for a range of 21 miles. Finally, annual incident-related congestion is approximately 1.9 hours per freeway vehicle, which represents five percent of the 37 hours of annual traffic delay experienced by the average San Diego motorist.

Ayala, Roberto. Of Planes, Trains and Automobiles: Market Structure and Incentives for a more Efficient, Cleaner and Fairer Transportation System. PhD, Transportation Science, 2011 xxx pp. Adviser: Jean-Daniel Saphores

The unifying theme of this dissertation’s three applications of economics to transportation is an attempt to make transportation more efficient, environmentally friendlier and fairer.

In my first essay, I apply game theory and the notion of Cournot equilibrium to transportation. I compare two networks, hub-and-spoke and a point-to-point network, which is served by two non-cooperative transportation firms. I find that the way in which two firms set their respective network, either direct indirect service, has an effect on their costs and profits.

In my second essay, I analyze the ownership of hybrid electric vehicles by U.S. households using the 2009 National Household Travel Survey to understand the impact of various government policies aimed at increasing hybrid vehicle ownership, such as granting access to high-occupancy vehicle lanes, tax credits, and parking incentives. I use a logit model; explanatory variables include socio-economic characteristics, along with urban form, as well as policy variables. Understanding which policies are most cost-effective at fostering HEV ownership would allow policy makers to make effective use of public resources.

In my third essay, I address equity in transportation by stratifying the NHTS into three income groups: low-income, middle-income and upper-income. The purpose is to determine whether income affects travel behavior. I analyze questions in the 2009 NHTS that were not available in previous NHTS surveys. These questions inquire about internet use,medical condition and physical activity. I also estimate a multinomial logit model and find that those living in poverty and who report having a medical condition are more likely to make medical trips. Upper-income individuals are more likely to report social and recreational trips, meal and trips labeled as “other.” Analyzing trips by income is important from an equity standpoint when allocating scarce public funds for transportation projects, since it tells us what income groups are likely to be affected by specific transportation projects.

Sangkapichai, Mana. Transportation and the Environment: Essays on Technology, Infrastructure, and Policy. PhD, Transportation Science, 2009. XX pp. Adviser: Jean-Daniel Saphores.

With soaring oil prices and growing concerns for global warming, there is increasing interest in the environmental performance of transportation systems. This dissertation contributes to this growing literature through three independent yet related projects essays that deal with transportation technology, infrastructure, and policy.

My first essay analyze the increasing interest for hybrid cars by Californians based on a statewide phone survey conducted in July of 2004 by Public Policy Institute of California (PPIC) using discrete choice models. Results suggest that the possibility for single drivers to use hybrid vehicles in HOV lanes is more important than short term concerns for air pollution, support for energy efficiency policies, long term concerns for global warming, education, and income. This suggests that programs designed to improve the environmental performance of individual vehicles need to rely on tangible benefits for drivers; to make a difference, they cannot rely on environmental beliefs alone.

The second essay is concerned with assessments of Travel Demand management (TDM) policies, which have been used to deal with congestion, air pollution, and now global warming. I compare two TDM programs: Rule 2202 (The on-road motor vehicle mitigation options in southern California) and the Commute Trip Reduction Program (CTR) in Washington State. My results reveal that after 2002, the impacts of Rule 2202 are mixed. Commuters’ modal choices are affected by worksite characteristics but only two (out of six) basic strategies effect the change in average vehicle ridership (AVR). Moreover, the level of subsidies appears to play an important role in commuting behavior. In Washington State, location has an impact on AVR and combinations of location and employee duties influence the single occupant vehicle index. Details of the CTR and its relative success suggest that there is room for improving Rule 2202 to make it friendlier to businesses and more effective.

Finally, I examine the health impacts of NO x (nitrogen oxides) and PM (particulate matter) generated by trains moving freight through the Alameda Corridor to and from the Ports of Los Angeles and Long Beach. After estimating baseline emissions for 2005, I examine two scenarios: in the first one, I assume that all long-haul and switching locomotives are upgraded to Tier 2 (from Tier 1); in the second scenario, all Tier 2 locomotives operating in the study area are replaced with cleaner, Tier 3 locomotives. I find that mortality from PM exposure accounts for the largest component of health impacts, with 2005 annual costs from excess mortality in excess of $40 million. A shift to Tier 2 locomotives would save approximately half of these costs while the benefits of shifting from Tier 2 to Tier 3 locomotives would be much smaller. To my knowledge, this is the first comprehensive assessment of the health impacts of freight train transportation in a busy freight corridor.

Wang, Jiana-Fu. Operational Strategies for Single-Stage Crossdocks. PhD, Transportation Science, 2008. 146 pp. Adviser: Amelia C. Regan

Because of the growing importance of hub-and-spoke operations in the trucking industry, crossdocking has become an important and effective tool to transfer freight. Companies like Wal-Mart, Costco and Home Depot are using this kind of facility in their logistics operations. Efficiently operating crossdocks, thereby reducing unnecessary waiting and staging congestion for freight and workers is an important issue for managers.

This dissertation uses real-time information about the contents of inbound and outbound pallets and the locations of pallets to schedule unloading for waiting trailers and assign destinations for pallets. We show how to incorporate the information of waiting freight in trailers to benefit trailer scheduling; we also show how to use the information on freight staging to mitigate congestion. Two dynamic trailer scheduling and four alternate destination strategies are proposed and compared with baseline scenarios.

Our simulation results suggest that:

1. Our strategies are effective. The two time-based trailer scheduling algorithms can save cycle times as much as 64%, 57% and 30% in the 4-to-4, 4-to-8 and 8-to-8 crossdock scenarios, respectively; the four alternate destination strategies can save cycle times as much as 34% in the 8-to-8 staging crossdock scenarios. In addition, these strategies can raise throughputs for crossdocks. These effects should result in a noticeable improvement in supply chain networks, including shorter transportation lead-times, more reliable on-time deliveries and lower inventory costs.
2. In our alternate destination strategies, even if a destination change results in extra time for value-added services for freight, the strategies are still worth adopting.
3. The combination models of our trailer scheduling algorithms and alternate destination strategies work better than solely implementing an alternate destination strategy when trailer arrivals are dense.
4. A higher flexibility in choosing alternate destinations can bring higher performance for crossdocks.

Apivatanagul, Pruttipong. Network Design Formulations, Modeling, and Solution Algorithms for Goods Movement. PhD, Transportation Science, 2008. 180 pp. Adviser: Amelia C. Regan

Efficient freight transportation is an essential for a strong economic system. A rapid growth of freight demand, however, lessens the efficiency of provided infrastructure. In order to alleviate this problem effectively, evaluation studies have to be performed in order to invest the limited budget for the best of social benefits. In addition to many difficulties on making a decision for each project investment, it is made harder by the complimentary and substitution effects that happen when considering transportation project together. Current practices, however, limit number of project combinations in order to avoid numerous tests. The best project combination may have never been realized.

This dissertation proposes network design models which can automatically create project combinations and searching for the best. The network design models have been studied for the passenger movements and focus on highway expansions. In this dissertation, the focus is shifted to the freight movements which involve multimodal transportation improvements. Our freight network design model is developed based on the bi-level optimization model. The development then involves two components. The first task is to set the freight investment problems within the bi-level format. This includes finding a suitable freight flow prediction model which can work well with the bi-level model. The second task is to provide a solution algorithm to solve the problem.

The dissertation sets the framework of the freight flow network design model, identifies expecting model issues, and provides alternatives that alleviate them. Through a series of developments, the final model uses the shipper-carrier freight equilibrium model to represent freight behaviors. Capacity constraints are used as a mean to emphasize limited services since the reliability issues, an important factor for freight movements, cannot be captured by steady state traffic assignment. A case study is implemented to allocate a budget for improvements on the California highway network. The transportation modes are selected by the shipper model which can be trucks, rails, or the multimodal transportation. The results shown that the proposed network design model provided better solutions compared with traditional ranking methods. The solution algorithm can manage the problem with reasonable project alternatives. However, the computation expense increases rapidly with increasing number of project alternatives.

Kalandiyur, Nesamani. Estimating Vehicle Emissions in Transportation Planning Incorporating the Effect of Network Characteristics on Driving Patterns. PhD, Transportation Science, 2007. 189 pp. Advisers: R. Jayakrishnan and Michael G. McNally

Variations in traffic volumes and changes in travel-related characteristics significantly contribute to the level of vehicular emissions. However, in current practice, travel forecasting models rely on steady state hourly averages and are thus incapable of accurately capturing the effects of network traffic variations accurately on emissions. Recent research has focused on the implementation of modal emission models to overcome some of these shortcomings in existing emission rate models. A primary input to modal emission models is the fraction of time spent in different driving patterns. The estimation accuracy, however, is hampered by the application of static travel demand models for predicting driving patterns. There is a real need to evolve alternate methods to accurately predict driving patterns.

This dissertation proposes an approach to predicting driving patterns more accurately by applying different models at the macroscopic and microscopic network levels. The proposed models more accurately estimate the driving
pattern by considering a set of Emission Specific Characteristics (ESC) for each network link. Specific ESC considered in this research includes geometric design elements, traffic characteristics, roadside environment characteristics, and driver behavior.

Two different models have been developed in this study to capture the driving patterns at each network level. The first model is designed to capture macro-scale driving patterns (average speed) in a larger network and the second model is designed to capture micro-scale driving patterns. The two models have been developed using structural equations. They have been calibrated, evaluated, and validated using a microscopic traffic simulation model.
Analysis of the models reveals that geometric design elements exert greater influence on driving patterns than traffic characteristics, roadway environment characteristics, and driver behavior in the estimation of emissions. This research has concluded that, for congested traffic conditions, the proposed models capture driving patterns more accurately than current practice and, consequently, these models estimate the range of emissions more accurately. Models that estimate time-dependent emissions in the presence of traffic sensor data were also successfully estimated.

Girvin, Raquel. Economic Analysis of Aircraft and Airport Noise Regulations. Ph.D, Transportation Science, 2006. 151 pp. Adviser: Jan Brueckner.

The aviation industry has sought to address the negative externality of aircraft noise using a variety of approaches, but there has been little theoretical work to date encompassing both the market implications and the social optimality of air transportation noise policy. This dissertation develops simple theoretical models to analyze the effects of noise regulation on an airline’s scheduling, aircraft ‘quietness’, and airfare choices. Monopolistic and duopolistic airline competition are modelled, and two types of noise limits are considered: maximum cumulative noise from aircraft operations and noise per aircraft operation. As expected, tighter noise limits, which reduce community exposure to noise, also cause airlines to reduce service frequency and raise fares, which hurts consumers. Welfare analysis investigates the social optimality of noise regulation, taking into account the social cost of exposing airport communities to noise damage, as well as consumer surplus and airline profit. Numerical simulations show that the type of noise limit has a significant effect on the magnitude of the first-best and second-best optimal solutions for service frequency, cumulative noise, and aircraft size and level of quietness. Furthermore, the numerical analyses suggest that under the more realistic second-best case, the cumulative noise limit might be a preferable policy instrument over the per-aircraft noise limit. In the monopoly’s parameter space exploration, welfare is found to be slightly higher, cumulative noise is lower, and the fare is slightly lower when the planner controls cumulative noise rather than per-aircraft noise. In the duopoly case, when the per-aircraft limit yields greater welfare than the cumulative limit, the per-aircraft limit offers only modest welfare gains above the levels achieved with the cumulative limit. But when the cumulative limit yields greater welfare than the per-aircraft limit, the cumulative limit offers substantial welfare gains above the levels achieved with the per-aircraft limit. The effects of noise taxation and the optimal level of noise taxes are also investigated with the duopoly model; the analysis shows equivalence between noise taxation and the cumulative noise limit.

Kulkarni, Anup. Modeling Activity Pattern Generation and Execution. Ph.D., Transportation Science, 2002. 143 pp. Adviser: Michael G. McNally.

Activity-based approaches are perhaps the most promising alternative to the current travel forecasting methodology. This dissertation first presents a pattern generation model that can serve as a link between activity and trip-based methodologies. The model uses a clustering approach to identify groups of similar activity-travel behavior and relates them to household socioeconomic attributes. Minimally, the pattern generation model is offered as a possible replacement to the standard trip generation model. This initial model is then expanded to serve as the core component of a proposed activity-based microsimulation model that constructs complete origin-destination tables using a wholly activity-based approach. The techniques developed provide due diligence to the complex nature of activity-travel behavior in terms of spatial and temporal constraints, household interactions, and the derived nature of such behavior. A successful application of the expanded model is outlined using data from the 1994 Portland activity-travel survey.

Parkany, Ann Emily. Traveler Responses to New Choices: Toll Versus Free Alternatives in a Congested Corridor. Ph.D., Transportation Science, 1999. 168 pp. Adviser: Kenneth A. Small

This dissertation presents several travel behavior models related to the 91 Express Lanes. The 91 Express Lanes are a facility in Orange County, California that opened in December 1995. The Express Lanes are built in the median of an existing freeway and offer users a congestion-free tolled alternative to the heavy traffic on the regular, general purpose lanes. The facility requires an electronic transponder and has tolls that change by time of day so that traffic flows freely. Many transponder-owners use the Express Lanes only infrequently. Although the Express Lanes were built and are operated by a private company, for the first two years, carpools with three or more people could travel on the Lanes without paying the toll making the facility a High Occupancy/Toll (HOT) lane. The models in the dissertation look at the main objective: what accounts for use of the facility. In addition to presenting summary statistics from the mail-based survey conducted by researchers at University of California, Irvine, several models are proposed, estimated, and analyzed. One chapter presents models of use and frequency of use. The "hurdle" of obtaining the electronic transponder is also considered. One chapter considers revealed preference and stated preference (RP and SP) models of the real-time decision to use the Express Lanes by infrequent Express Lane users. Another chapter looks at RP and SP data models of carpooling in the corridor. Income plays a role in all of the models in intuitive ways. Yet, I can argue that income does not have an overwhelming effect on all of the behavioral decisions related to the toll road. Cultural differences and education influence having or not having a transponder. The independent variables tested explained little in the models of real-time choice which suggest that the decision to use the lanes may not be occurring due to real traffic conditions, but to each individual's extenuating circumstances (for example, having to get to a meeting). There is little here to support the hypothesis that HOT lanes encourage carpooling, but the evidence shows that carpooling remains stable in the corridor.

Ryan, Sherry. The Value of Access to Highways and Light Rail Transit: Evidence for Industrial and Office Firms. Ph.D., Transportation Science, 1997. 138 pp. Adviser: Joseph F. DiMento

This dissertation examines the relationship between transportation access and industrial and office property rents. The primary purpose of this research is to evaluate two sparsely studied topics in the transportation-land use literature: the impacts of light rail transit on property values, and the effect of transportation facilities on non-residential land uses. Multivariate regression analysis is used on longitudinal data for approximately five hundred and twenty office properties and five hundred industrial properties collected from the San Diego metropolitan region over the period from 1986 to 1995. Asking rents ($/square foot/month) is the dependent variable. Straight-line distance of each property to the nearest freeway on/off ramp, the nearest light rail station, and to the San Diego central business district provide measures of access. Other independent variables include building and neighborhood characteristics. The findings show that access to freeways is consistently significant in predicting office rents. This result indicates that freeways are important in shaping office property values, and by extension office land use patterns. Light rail transit did not have a significant effect on office rents. Access to the CBD was only significant for downtown office properties. The CBD variable in this case may be a proxy for the effect of localization economies. None of the measures of access was significant for industrial properties. This research underscores the importance of refining measures of access in order to capture and better understand the transportation-land use relationship. In particular, if the distance of an industrial firm to freeways, light rail transit, and the CBD is not important, then what kinds of access do matter? This research also has important implications for planning light rail transit systems. There is strong evidence that light rail systems do not provide enough travel cost savings to increase non-residential property values. This finding should be taken seriously in planning alignments for future light rail systems. Light rail systems need to be aligned with existing activity centers, rather than expected to stimulate new development or the redevelopment of distressed urban areas.