Mark E Hallenbeck

Extracting Roadway Background Image: Mode-Based Approach

Traffic monitoring cameras are widely installed on streets and freeways in U.S. metropolitan areas. Video images captured from these video cameras can be used to extract many valuable traffic parameters through video image processing. A popular way to capture traffic data is to compare the current traffic images with the background image, which contains no vehicles or other moving objects, just background such as pavement. Once the moving vehicle images are separated from the background image, measurements of their number, speed, and so on can be obtained. Typically, background images are extracted from a video stream through image processing because it may be hard to find a frame without any vehicles for normal traffic streams on urban streets. This paper introduces a new method that can quickly extract the background image from traffic video streams for both freeways and intersections in a variety of prevailing traffic conditions. This method has been tested with field data, and the results are promising.

ITS Devices Used to Collect Truck Data for Performance Benchmarks

This paper documents the development of data collection methodologies that can be used to measure truck movements along specific roadway corridors in Washington State cost-effectively. The intent of this study was to design and test methodologies that could provide information to ascertain the performance of freight mobility roadway improvement projects. The benchmarks created would be used to report on speed and volume improvements that resulted from completed roadway projects. One technology tested consisted of Commercial Vehicle Information System and Networks electronic truck transponders, which were mounted on the windshields of approximately 30,000 trucks traveling in Washington. These transponders were used at weigh stations across the state to improve the efficiency of truck regulatory compliance checks. With transponder reads from sites anywhere in the state being linked through software, the transponder-equipped trucks can become a travel time probe fleet. The second technology tested involved G...

Sensitivity of Axle Load Spectra in the Mechanistic-Empirical Pavement Design Guide for Washington State

The Guide for Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures [referred to as the Mechanistic–Empirical Pavement Design Guide (MEPDG)] is proposed as an advanced pavement design tool that integrates up-to-date pavement practices. The use of axle load spectra instead of the equivalent single-axle load is a dramatic change. However, the collection of an adequate amount of data over years is required for the accurate characterization of future traffic for design; this gives primary importance to pavement designers having a good understanding of the axle load spectra. This paper presents the typical truck load spectra that satisfy the MEPDG requirements for the Washington State Department of Transportation (WSDOT) and that were developed on the basis of the data collected from selected WSDOT weigh-in-motion stations. Sensitivity analysis was conducted with various typical design parameters of WSDOT flexible pavements. The significant findings are that (a) one type of axle load spectrum can present load characteristics for WSDOT in MEPDG, (b) MEPDG is moderately sensitive to the axle load spectra for typical WSDOT pavement designs, and (c) WSDOT needs to calibrate MEPDG before use. The results have been verified in the calibration of the flexible pavement distress models for WSDOT. It is recommended that agencies that lack data resources test and use the default MEPDG axle load spectral inputs and that the bias may be corrected through model calibration efforts.

DEVELOPMENT OF A SYSTEM FOR COLLECTING LOOP-DETECTOR EVENT DATA FOR INDIVIDUAL VEHICLES

Typical freeway inductive loop detection systems, under normal operation, aggregate individual loop-detector actuations sampled at 60 Hz into 20-s or 30-s averages of velocity, flow, and lane-occupancy measurements. While such aggregations are appropriate for serving as inputs to control system algorithms, and they save disk space for archiving loop data, a large amount of useful data regarding individual vehicles is lost. For single-loop detectors, the lost information includes individual vehicle arrival, departure, and presence times. For speed traps, the lost information also includes the calculated individual vehicle speed and length. Yet this information about individual vehicles is desirable to transportation researchers and planners. The unavailability of this information makes in-depth investigation of detector errors difficult or even impossible. A system for collecting detector event data is proposed. This system can sample loop actuations with sampling rates of 60 Hz or higher and then save, process, and present the collected event data in real time without interfering with the detector controller’s normal operation. A stand-alone Windows program was developed for performing real-time high-frequency loop event data collection. A system reliability test and field application indicate that the system can collect realtime detector event data at a high sampling rate (60 Hz or higher). Additionally, this system makes real-time loop data quality evaluation, loop malfunction identification, and loop error correction feasible.

Evaluation of arterial and freeway interaction for determining the feasibility of traffic diversion

Traffic congestion is a common phenomenon in our daily lives that greatly costs society. A better understanding of the interaction between freeways and arterial streets may help traffic engineers and researchers improve the operation of existing facilities and deploy feasible traffic diversion plans to improve the usage of existing road capacity within a traffic network. This paper proposes a novel two-step approach to evaluate the interaction between freeways and arterial streets by comparing their performances. The first step is to identify freeway and arterial travel time pattern similarities via template matching techniques commonly used in computer vision. The interaction is quantified in the second step by using conditional probability theory. The result of the two-step process allows analysts to determine whether traffic diversion is possible or likely between freeways and parallel arterials. The city of Bellevue, Washington was selected as a case study site because of the availability of traffic s...

Impacts of Freeway Traffic Congestion on En-Route Traveler's Diversion

Traveler information delivered through variable message signs and other mobile devices has been proved beneficial for traffic network performance. Understanding travelers’ en-route responses to real-time traffic conditions is essential for integrated corridor management and strategic investment in Intelligent Transportation Systems (ITS) targeting congestion mitigation. Identifying the availability of spare capacity on alternative routes is the indispensable first step for diversion guidance on congested routes. Otherwise, diversion may not be beneficial for either the travelers who made the decision or the roadway network because diverting to an alternative route without spare capacity will aggravate the congestion and further delay the travel. In order to evaluate traveler’s diversion and its impact, many studies have tried various approaches, such as survey study and traffic simulations. This paper describes a threshold-based method to replicate different scenarios using loop detector data on freeways and arterials. Unlike the traffic simulation approaches, the threshold-based method can quantitatively capture en-route travelers’ real-time decision on diversion and the diversion’s impact on the alternative route without the need for theoretical assumptions. By monitoring the freeway congestion level, the proposed method extracts three types of scenarios, normal congestion, worse-than-expect, and abrupt-traffic-change condition to investigate travelers’ decisions on diversion. This method was applied to the City of Bellevue in WA and achieved encouraging results.