conference paper
published journal article
This paper ls a discussion of an in-depth evaluation study of highway data development and analysis activities of the Washington State Department of Transportation. Statistically based procedures and recommendations that were developed to streamline the highway data collection program are described. Opportunities to reduce manpower and equipment costs, streamline work activities, Improve the quality of data collected, and provide accurate and timely data for the various users were Identified. Given the focus on highway data, a major effort was devoted to the department’s traffic-counting program. However, many data items and programs were considered, and the following items received particular attention: traffic volume counting, including estimation of annual average dally traffic at any location tbroughout the state highway system; associated seasonal, axle, and growth factors; vehicle classification; trqck weight; and the relationships between the statistical sampling requirements recommended for these items and those associated with the FHWA Highway Performance Monitoring System (HPMS) in the state. Employing statistical sampling methods that complement the HPMS sample offers a strong potential for significantly Improving the cost-effectiveness of a statewide highway data collection program.
working paper
Trip chaining is a phenomenon that has a significant impact on urban transportation and activity systems. This paper argues that an appropriate representation of the underlying behavioral processes in models of trip chaining is crucial to the capability and reliability of the models. To examine the behavioral processes, data on the complete processes of activity scheduling and trip chaining were collected with a computerized survey instrument, REACT!. The scheduling horizons of sojourn activities were analyzed with contingency tables. The results of this analysis indicate that some of the decision elements entailed in trip chaining were opportunistically formed within constraints set by previously planned activities. While engaged in earlier activities, individuals might see opportunities of carrying out certain activities at different locations occurring later in the day. The decisions as to whether to take these opportunities or not would depend on their evaluation of scheduling feasibility (e.g., the travel time required to reach these activities). However, the analysis also illustrates that some trip chains were indeed executed as planned, suggesting optimality and potential routine behavior. Based on the empirical evidence, transactional opportunistic planning within a constrained environment is viewed as a potential behavioral model for trip chaining behavior.
published journal article
To better understand how road congestion adversely affects trucking operations, we surveyed approximately 1200 managers of all types of trucking companies operating in California. More than 80% of these managers consider traffic congestion on freeways and surface streets to be either a “somewhat serious” or “critically serious” problem for their business. A structural equations model (SEM) is estimated on these data to determine how five aspects of the congestion problem differ across sectors of the trucking industry. The five aspects were slow average speeds, unreliable travel times, increased driver frustration and morale, higher fuel and maintenance costs, and higher costs of accidents and insurance. The model also simultaneously estimates how these five aspects combine to predict the perceived overall magnitude of the problem. Overall, congestion is perceived to be a more serious problem by managers of trucking companies engaged in intermodal operations, particularly private and for-hire trucking companies serving airports and private companies serving rail terminals. Companies specializing in refrigerated transport also perceive congestion to be a more serious overall problem, as do private companies engaged in LTL operations. The most problematic aspect of congestion is unreliable travel times, followed by driver frustration and morale, then by slow average speeds. Unreliable travel times are a significantly more serious problem for intermodal air operations. Driver frustration and morale attributable to congestion is perceived to be more of a problem by managers of long-haul carriers and tanker operations. Slow average speeds are also more of a concern for airport and refrigerated operations. (C) 2001 Elsevier Science Ltd. All rights reserved.
published journal article
conference paper
The navigation performance with low Earth orbit (LEO) satellite signals is evaluated. The navigation framework used to perform this evaluation tightly integrates a vehicle’s inertial navigation system (INS) with Doppler and pseudorange measurements from LEO satellites. The following scenario is considered. A vehicle has access to global navigation satellite system (GNSS) signals and a priori, uncertain information about LEO satellite states. The vehicle navigates by tightly integrating GNSS pseudorange measurements with its onboard INS. During the period when GNSS signals are available, the vehicle tracks the LEO satellites from pseudorange and Doppler measurements, refining estimates about their states. Next, GNSS signals are assumed to be unavailable. The vehicle transitions to a simultaneous tracking and navigation (STAN) mode where it simultaneously tracks the LEO satellites and navigates by integrating pseudorange and Doppler measurements made on the LEO satellites with its onboard INS. The performance of this navigation framework is evaluated for two cases: when the LEO satellites periodically transmit their position and when the do not transmit such information. Simulation results with existing LEO satellite constellations pertaining to Orbcomm and Globalstar as well as the future satellite constellation pertaining to Starlink are presented. It was assumed that the LEO satellites are periodically transmitting their positions. These simulation results consider an unmanned aerial vehicle (UAV) equipped with a tactical-grade inertial measurement unit (IMU) navigating for 81.6 km in 600 seconds, in which GNSS signals were only available for the first 100 seconds. It is demonstrated that the final position error of the INS-Orbcomm-Globalstar system was 93.01 m while the INS-Starlink system was 9.81 m. The position root mean squared error (RMSE) of the INS-Orbcomm-Globalstar system was 58.59 m while the INS-Starlink system was 10.13 m. Experimental results with existing Orbcomm LEO satellites are presented in which only Doppler measurements were made on two available satellites. The experimental results were conducted on a ground vehicle equipped with a tactical-grade IMU that traversed 7.5 km in 258 seconds, in which GNSS signals were only available for the first 30 seconds. It is demonstrated that the final position error of the INS without GNSS signals was 3.73 km and the position RMSE was 1.42 km. On the other hand, the final position error of the INS-Orbcomm system was 233.3 m and the position RMSE was 188.6 m when the position of the satellite was decoded from its transmitted message. If such position was not decoded and was estimated only from the STAN framework, the final position error was 476.3 m and the position RMSE was 195.6 m.
research report
The paper analyzes the effects on the demand for owner-occupied housing that are likely to result from the Swedish 1983-85 tax reform. This is done by means of a microsimulation model which takes into account the dichotomous nature of the demand for housing: the consumers choose the mode of tenure (owning versus renting) as well as the quantity of housing conditional on the choice of the mode of tenure. The tax reform consists of a general reduction of marginal tax rates (i.e. an increase in disposable income) together with limitations in the deductibility of mortgage interests. The simulations show that this will cause an increase in home-ownership in the sense that more households will demand owner-occupied housing. At the same time, however, the households will demand smaller houses in the average, and thus aggregate demand for small and medium-sized units will increase while demand for large units will fall sharply.
conference paper
published journal article
published journal article