published journal article
working paper
Starting in the mid-1960’s, federal policy encouraged the public takeover and subsidy of what had been a privately owned, self-supporting transit industry. The combination of public ownership and subsidy was able to halt the long-term decline in ridership, but it also led to the growth of an enormous financial deficit that has become increasingly difficult to bear. This paper uses disaggregate data for 62 transit properties to measure the change in productivity (output per dollar of input) over the period 1950–1985. It also shows the relationship between productivity and the size of the transit property – the large transit properties showed the greatest declines in productivity. The evidence shows substantial diseconomies of scale too. The magnitude of the productivity decline is surprising: indeed, if transit productivity had merely remained constant since 1964, the year the federal subsidy program began, total operating expenses would be more than forty percent lower. To put that figure in perspective, this is enough cost reduction to erase most of the current operating deficit — without raising fares.
working paper |
May 1990
working paper |
Nov 1988
working paper |
Jun 1991
working paper |
Jun 1989
working paper |
Nov 1991
working paper
The recent fiscal problems of public transit in many large metropolitan areas have stimulated interest in alternative service delivery systems for public transportation. One strategy. that of contracting with private providers for public transportation services. has received particular attention. Private sector contracting is viewed as attractive due to its cost and subsidy savings potential–savings of 25 to 50 percent of public agency transit operator costs have been cited.(1.2.3) The reality. however. is that relatively little transit service contracting currently takes place and that substantial political, organizational, and legal obstacles confront plans to increase the use of this strategy. In addition, little detailed information is available on the extent of service contracting. its economic benefits. and the institutional factors which affect its feasibility. The purpose of this paper is to contribute to remedying this information deficiency by providing a review of selected experiences and issues of transit service contracting. The paper focuses on five major topics. (1) How widespread is transit service contracting. who practices it. and what services are involved? (2) Why do public agencies engage in private sector contracting, and what are typical situations in which they do so? (3) What is the magnitude of the estimated cost and subsidy savings which have been realized from contracting? (4) What are the major obstacles to service contracting and when are they able to be overcome? (5) What issues involving service contracting require additional research?
Phd Dissertation
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 55 miles from the Mexico-US border to Northern San Diego County, CA. This freeway portion has an average annualized daily traffic volume of 230,000 vehicles. 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 9,003 incidents in my study area in 2008. Using the BSCM approach, I find that 3.7 percent of collisions were secondary incidents. Moreover, my statistical model shows that incidents occurring during evening peak hours on Fridays or during midday on weekends are more likely to result in secondary crashes as do incidents with injuries or fatalities, incidents that involve more vehicles or trucks, or incidents that take place when the pavement is wet. Conversely, secondary crashes are less likely to occur in areas with a complex geometry (perhaps because drivers are more cautious there) or for incidents taking place on the side of the freeway. More importantly, changeable message signs (CMS) decrease the occurrence of secondary crashes. The maximum effectiveness of a CMS is approximately 11.75 miles for a range of 23.6 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.
conference paper
conference paper
Information is effectively the same as a change in uncertainty, and therefore, they share the same unit system of measurement, such as bit, nat, and qubit. This paper adopts a strict definition of information and implements a method to quantify traveler information provision using an information-based modeling framework developed in earlier research. The framework combines a cognitive grouping model and information update scheme (learning) for calculating in quantified units the amount of information any traveler has about a route, which can be further decomposed to any sub-route during any time period of relevance. Such numerical quantification can be meaningful in evaluating network performance enhancement schemes such as ATIS and in modeling decision making when uncertainty is a significant factor. An application study with traffic network and detector data near downtown Los Angeles is used to demonstrated the use of the method for quantifying information provision from a dynamic message board, as an illustrative case. Further improvement and research directions are identified.
policy brief
Tractor-trailers dominate the truck cargo industry. Between 1990 and 2010, this industry grew significantly; vehicle miles traveled increased 87 percent and ton-miles increased by 47 percent. While the growth of trucking miles and tonmiles is a positive indicator of economic transformation and expansion, the trucking sector also produces negative externalities, including but not limited to pavement damage. Pavement damage is closely tied to vehicle weight, which is a product of private market decisions driven by the cost of delivery per ton and the frequency of delivery. Understanding the interplay between fuel cost and private sector decisions on truck dispatch (i.e., frequency and load of trucks) is key to understanding infrastructure damage.
policy brief |
Aug 2020
research report |
Jun 2017
conference paper
conference paper
With the goal of developing procedures for predicting activity/travel patterns of individuals given their socio-demographic characteristics, the authors cluster individuals based on their activity patterns using a two-stage clustering technique to infer activity time windows. The two-stage technique is a combination of affinity propagation and K-means clustering methods. Activity patterns are created by segmenting daily activities into ten-minute intervals, carrying information about activity types, duration, schedule and travel distance. The authors test different combinations of two error measures: sequential alignment and agenda dissimilarity to compute the distance between each pair of patterns. In order to analyze the effectiveness of clustering on inferring activity patterns, the authors further test the prediction accuracy for two population, clustered and un-clustered. The results indicate that updating activity time windows based on the arrival time distribution of the clustered data, has higher accuracy than using those distributions with un-clustered data.
published journal article