Scott S Washburn

Statistical modeling of vehicle emissions from inspection/maintenance testing data: an exploratory analysis

Abstract Many metropolitan areas in the United States use vehicle inspection and maintenance (I/M) programs as a means of identifying high-polluting vehicles. While the effectiveness of such programs is debatable, the cost is undeniable, with millions of dollars spent in testing and millions more lost in the time motorists expend to participate in such programs. At the core of these costs is the blanket approach of requiring all vehicles to be tested. This paper sets the groundwork for a procedure that can be used to selectively target those vehicles most likely to be pollution violators. Using I/M data collected in the Seattle area in 1994, carbon monoxide, carbon dioxide and hydrocarbon emissions were modeled simultaneously using three-stage least squares. Our results show that vehicle age, vehicle manufacturer, number of engine cylinders, odometer reading, and whether or not oxygenated fuels were in use all play a significant role in determining I/M emission test results and these statistical findings can be used to form the basis for the selective sampling of vehicles for I/M testing.

Quality-of-Service Perceptions by Rural Freeway Travelers: Exploratory Analysis

In recent years the Transportation Research Boards Highway Capacity and Quality of Service Committee (HCQSC) has debated how performance measures for defining level of service (i.e., service measures) for a facility should be selected. The historical approach has been for the HCQSC to select the measure (or measures) thought most appropriate. However, some committee members have been suggesting that the selection of service measures should be based on research involving the driving public at large and that this research should either directly or indirectly obtain information from drivers and passengers on perceptions of quality and level of service. A preliminary investigation determining the factors that affect traveler-perceived quality of service on rural freeways using in-field surveys of motorists traveling on rural freeways has been conducted. In regard to quality of service, it is becoming more evident that travelers consider multiple factors, and the results from this study support that notion. Specifically, the survey shows that most respondents consider three or more factors important in determining their quality of service on rural freeways. Although density still appears to be a primary factor affecting perceived quality of service, additional factors, such as speed variance and percentage of freeflow speed, seem just as important to travelers. In addition, some nontraffic-performance measures, such as pavement quality and driver etiquette, were found to be important.

Development and Evaluation of Methods for Constructing Breakdown Probability Models

AbstractThe term breakdown of flow at a freeway bottleneck location has been used to describe the transition from relatively free-flowing traffic to congestion, often called stop-and-go traffic, but more generally experienced as slow-and-go. The focus of the research presented in this paper was to develop probabilistic models to predict breakdown of flow by using data from five freeway-ramp merging segments. The development of the probabilistic models allows exploration of several issues: the identification of breakdown, the performance measures for the identification of the breakdown, and the breakdown location. The breakdown probability model (BPM) is based on lifetime data analysis statistics. The breakdown probability models can be very useful tools in establishing capacity values, which in turn can be part of the freeway traffic management process.

Impact of Trucks on Signalized Intersection Capacity

The most common method used for the analysis of signalized intersections in the United States is contained in the Highway Capacity Manual (HCM). In this method, the base saturation flow rate of the signalized intersection is defined in units of passenger cars per hour green per lane (pc/hg/ln). To account for the presence of large trucks in the traffic stream, the HCM includes a Passenger Car Equivalency (PCE) value. In the current edition of the HCM, a PCE value of 2.0 is applied for all large trucks, with no distinction between different sizes of trucks. The HCM also recommends a single value of 2.0 seconds for startup lost time, regardless of queue composition. Many transportation professionals have questioned the validity of the PCE value and startup lost time recommended by the HCM. They are concerned that the impact of trucks at signalized intersections is being underestimated. If this is the case, then capacity is being overestimated and intersections are not being adequately designed. The objective of this study was to identify appropriate truck PCE values and a relationship for startup lost time as a function of truck percentage in the traffic stream. To accomplish this objective, a custom simulation tool was developed based on the modified Pitt car-following model, calibrated with field data, and applied to a comprehensive experimental design. The PCE values determined from this study are 1.8, 2.2, and 2.8 for small, medium, and large trucks, respectively. A model for estimating startup lost time based on the same small, medium, and large truck classifications was also developed.

Performance Measures for Truck Level of Service: An Exploratory Survey Analysis

The current Highway Capacity Manual (HCM) provides analytical methods to evaluate performance levels of transportation facilities and to estimate level of service (LOS) perceived by the users. The HCM methodologies yield a single LOS value for all users in a traffic stream. However, because of the unique size and operating characteristics of large trucks, truck mode users may perceive LOS on various roadway facilities on the basis of different criteria than those of other mode users. A study was conducted to determine, from an LOS perspective, what roadway, traffic, and control issues should be focused on to better serve the needs of the trucking community. This paper describes the second part of the study, in which a survey of truck drivers and truck company managers was performed to quantitatively measure the relative importance, satisfaction, and improvement priority of truck LOS determinants and to examine which aspects of a truck trip should be analyzed to estimate truck LOS on each roadway type. Speed variance and pavement quality were identified as the service measures for truck LOS on freeways, while percent time being followed, percent time spent following, and travel lane and shoulder width and their pavement quality were identified for truck LOS on two-lane highways. Truck trip quality on urban arterials was found to depend on factors such as ease of turning maneuver, speed variance, traffic density, and pavement quality. Other drivers’ behavior, pavement condition, level of congestion, and frequency and timing of construction activities were common major contributors to truck LOS regardless of roadway type.

FRAMEWORK FOR INVESTIGATION OF LEVEL-OF-SERVICE CRITERIA AND THRESHOLDS ON RURAL FREEWAYS

The Highway Capacity Manual prescribes level-of-service (LOS) criteria as a function of traffic density to categorize the operational conditions of both rural and urban freeway sections. This density-based level of service is ideally suited to the assessment of urban freeways when the performance must be optimized to meet high traffic demand. There is, however, some question as to whether density is the appropriate indicator of the quality of service on rural freeways, since drivers may think more in terms of psychological or emotional comfort for freeways, which generally serve long, high-speed trips and rarely experience more than moderate congestion levels. Three specific measures are examined that have at least an intuitive relationship to the concept of driver comfort: (a) acceleration noise, which is a measure of the physical turbulence in the traffic stream; (b) number and duration of cruise control applications, which could serve as a general indication of driver convenience or inconvenience; and (c) percent time spent following, which is already accepted as the basis for determining the level of service on rural two-lane highways. The three candidate measures were estimated for a hypothetical section of rural freeway by simulation, using the CORSIM model. The kinematic relationships of individual vehicles within the traffic stream were estimated by postprocessing the simulation data for each second of operation. All of the measures considered in this study have conceptual appeal. All have produced interesting and potentially usable results with respect to their relationships to traffic volume. Although the simulation results are interesting, further studies focusing on driver opinions, behavior, or field measurements, or all three, would likely be necessary to support the development and recommendation of a specific set of LOS criteria that recognizes the differences between the urban and rural freeway driving environments.

USING VOICE RECOGNITION TO COLLECT LICENSE PLATE DATA FOR TRAVEL TIME STUDIES

The use of portable computers for performing travel time studies has become commonplace with many transportation agencies. Whereas data entry has historically been done via the keyboard, a new method of data entry is being proposed that should make license plate data collection with portable computers more efficient and convenient. This new method uses voice recognition to allow the user to dictate license plate data into a microphone. These data are then directly entered into the computer and time-stamped. The authors have developed a standalone Windows program for performing license plate data collection using voice recognition. Preliminary testing has indicated that this technology has the capability to provide entry accuracy rates in excess of 95 percent, as well as to provide sample sizes comparable to or larger than those obtained through keyboard entry. Additionally, this technology has the capability to reduce personnel requirements for situations typically using two data-collecting people per station, such as those in which one person using binoculars reads the license plates aloud to another person doing the data entry. The results of this preliminary testing are definitely promising and have indicated that this method for license plate data collection is feasible at this time.

Integrated Simulation-Based Method for Estimating Arrival Type for Signalized Arterial Planning Applications

One of the primary determinants of signalized intersection delay, and consequently signalized arterial level of service, is progression quality. Progression quality is represented by an arrival-type variable in the Highway Capacity Manual (HCM) procedure for calculating signal delay. Ideally, the arrival type is estimated from collected field data, in particular the percentage of vehicles that arrive at an intersection approach while that approach has the green signal indication. The Florida Department of Transportation prescribes the use of its ARTPLAN software program for planning-level analyses of signalized arterial level of service in the state of Florida. This software is a planning-level implementation of the arterial analysis methodology contained in Chapter 15 of the 2000 HCM. One of the inputs to this software program is arrival type. Given the significant impact this variable can have on delay, and subsequently level-of-service results, it is prudent to have as good an estimate of its value as possible. However, collecting accurate data on progression quality is very difficult, and the intent behind a planning-level analysis is that detailed field data should not be required. Consequently, the blanket HCM recommendations for arrival type are often applied in these analyses without much consideration of how appropriate these values really are for the specified roadway, traffic, and control conditions. A method developed to estimate arrival-type values with a simulation-based approach from the planning-level inputs of ARTPLAN is described. Also provided is a summary of simulation-derived arrival-type values from a large number of sample data sets.

Freeway Capacity Estimation Method for Planning Applications

The capacity of a freeway segment is a critical factor for the planning, design, and analysis of freeway facilities. The Highway Capacity Manual (HCM) is considered to be one of the authoritative sources on capacity values for a variety of roadway types in the United States, particularly for planning purposes. For basic freeway segments, a single set of capacity values are provided as a function of free-flow speed. Although these values are considered to be reasonably representative values for freeways located throughout the United States, the HCM does not provide any guidance on how its recommended values can be adjusted to reflect significant differences in capacity due to local conditions, nor how to directly measure or estimate capacity values. With the recent development of a statewide freeway traffic data archive in Florida, the Florida Department of Transportation (FDOT) desired to use these data to determine if the freeway capacity values in the HCM were appropriate for Florida freeway level of service analyses for planning and preliminary engineering applications. This study evaluated two previously published methods for estimating freeway capacity, identified their advantages and disadvantages for use in planning applications, and ultimately recommended a method for use by FDOT. One of the chosen methods determines capacity from a mathematical function generated from speed-flow data points and the other chosen method uses the concept of breakdown probability distribution to determine capacity. Neither of these methods proved desirable for planning applications due to computational burden; thus, an alternate, simplified approach was developed that used a simple averaging method of highest flow rates to determine capacity.

Revised Version of the Automobile Level-of-Service Methodology for Urban Streets in the Highway Capacity Manual 2010

The Highway Capacity Manual 2010 (HCM 2010) contains a significantly revised automobile analysis and level-of-service (LOS) methodology for arterials. This study compared the arterial LOS results of the HCM 2000 and HCM 2010 methodologies for an experimental set of arterial segments and analyzed the effects of the revised methodology. In addition, existing Florida field data sets were also analyzed with arterial segments obtained from Gainesville, Tallahassee, and Tampa, all in Florida, as well as data received from the Florida Department of Transportation Districts 2 and 3. The HCM 2010 results showed that for shorter, lower-speed arterial segments [such as in central business districts (CBDs)] it was not possible to obtain LOS Ratings A or B. Therefore, many CBD arterials that had good LOS values under the HCM 2000 methodology would now have moderate to poor LOS values. Consequently, the research team tested several revisions of the HCM 2010 methodology to find an approach that would not be as punitive to arterials with shorter segment lengths and that would provide a good balance of LOS values across a range of segment lengths, posted speeds, and traffic demands. Suggested revisions to the HCM 2010 methodology that allowed this objective to be achieved consisted of the following: the use of two classes instead of one (on the basis of the posted speed); the use of the average travel speed as the service measure instead of the ratio of the average travel speed to the base free-flow speed; and the setting of the free-flow speed to equal the posted speed plus 5 mph, instead of using the free-flow speed computations in the HCM 2010 methodology.