Sangkey Kim

Comparative Evaluation of Reported Speeds from Corresponding Fixed-Point and Probe-Based Detection Systems

Point-based traffic sensors, such as microwave radar and acoustic sensors, provide the valuable capability of sampling the entire traffic stream. However, full network coverage with point sensors requires a significant initial capital investment and ongoing maintenance expenditures. Probe-based sensors can cover an extensive roadway network at a much lower cost because roadway-based field equipment is not required. Decisions regarding the relative level of point sensor- versus probe-based deployment for traffic monitoring involve evaluating the trade-off between the value of comprehensive detection versus total system costs. An essential step in evaluating this trade-off involves directly comparing collocated point sensor and probe vehicle systems to understand how the derived traffic stream measures from the two approaches differ. This study compared 5-min speeds from microwave radar and acoustic sensors with link speeds from Global Positioning System (GPS) probes for both directions at five freeway locations. Systematic differences were found at one location. Floating car GPS runs were performed to confirm that the systematic error lay in the point speeds. The speed differences at all sites were normally distributed, with three locations indicating a mean speed difference greater than 5 mph. Nonsystematic speed differences were identified; the difference was more than 1.5 standard deviations lower than the mean difference. This difference may indicate inherent inaccuracies in reported GPS speeds under heavy congestion, including instances of time lag in recovering from congested speeds.

Dynamic Bandwidth Analysis for Coordinated Arterial Streets

A commonly used strategy for improving mobility along signalized arterials is to coordinate neighboring intersections to minimize vehicle stops by maximizing the duration of green bands, otherwise known as arterial bandwidth. Signal coordination has been researched, developed, and refined for five decades. In lieu of traditional methods that are based on the analysis of programmed green times (which assume all phases operate at their maximum settings), a dynamic bandwidth analysis method is presented that reproduces actual dynamic bandwidth durations using closed loop signal data. The analysis is intended to help assess the performance of semi-actuated coordinated signal systems on arterial streets. In addition, the study highlights the arterial progression benefits that result from changing coordinated intersection offsets based on optimizing the dynamic, rather than the programmed, bandwidths. Detailed analysis at three arterial sites revealed that coordinated green phase time distributions are complex and multimodal and cannot be represented by a single-valued statistic. Dynamic bandwidth analysis confirmed that programmed green bandwidth consistently underestimates the size of the actual dynamic bandwidth, and exhaustive search results highlighted the potential for further improvements in coordination. Future research will include field and simulation comparative studies and the development of efficient methods for dynamic bandwidth optimization.

Estimation of Saturation Headway in Work Zones on Urban Streets

Work zones and lane closures on urban arterials can cause significant disruptions to the traveling public, and methods are increasingly needed to estimate the reductions to saturation flow rates that result from work zones at signalized intersections. A set of statistical models that estimate saturation headways as a function of the presence and configuration of the work zone on signalized arterial streets is presented. More than 10,000 individual vehicular headway observations were collected from video observations in and after work zones at six study sites in North Carolina. Conventional multiple-regression and path-based-regression models (structural equation model) were used to develop the saturation headway models. Three models are provided at different aggregation levels of the collected data with identical work zone configurations. The models developed at cycle-length, 15-min, and full aggregation produced adjusted R-squared values of .3259, .7209, and .895, respectively. The proposed model incorporates the effects of lane configuration, pavement condition, turning percentage from shared lanes, work intensity, and number of closed exclusive turning lanes. Based on path analysis, the structural equation model satisfies all the rule-of-thumb criteria for goodness-of-fit indices. The model uses Highway Capacity Manual default values for turning-vehicle headway effect as its intercept coefficient value.

Application of High-Resolution Vehicle Data for Free-Flow Speed Estimation

The use of probe vehicle data for highway performance monitoring is increasingly being adopted in many countries. In the United States, third-party data provider entities such as Google, INRIX, HERE, and TomTom are delivering products to state and local transportation agencies that are enabling them to identify bottlenecks, incidents, and other key operational events on the basis of probe vehicle speed and travel time. However, the capacity analysis methods in the U.S. Highway Capacity Manual continue, for the most part, to rely on the analyst’s ability to gather data at fixed points, whether manually or from fixed point sensors. This paper explores the use of intelligence to drive (i2D) high-resolution vehicle data to assess several research questions related to free-flow speed (FFS) estimation, a key parameter in freeway segment analyses. On the basis of 1 year of high-resolution data collected from a local fleet of about 20 vehicles driven by volunteer drivers, researchers accumulated more than 20 million s of driving, which when filtered were used to evaluate research questions and develop enhanced predictive models for FFS. Speed limit and section ramp density (i.e., those ramps within the segment proper only) were found to have had a strong effect on the value of FFS. Driver familiarity was found to have an effect also, although this effect was not conclusive across 10 study sites. Finally, an FFS predictive model that incorporates speed limit and section ramp density was found to fit the high-resolution data quite well, generating an absolute error of only 1.3% across all sites. That finding compares with an error of 6.6% with the current Highway Capacity Manual 2010 model predictions.

Innovative Method for Remotely Fine-Tuning Offsets Along a Diverging Diamond Interchange Corridor

Diverging diamond interchanges (DDIs) are relatively new in the United States, and signal coordination between the crossovers and adjacent intersections is challenging. This paper provides a method for remotely fine-tuning offsets for a DDI and its adjacent intersections. The proposed method uses the dynamic bandwidth analysis tool (DBAT). The tool uses actuated phase times from the signal controller to optimize the dynamic bandwidth on the basis of that entry data set. Four performance measures evaluated the proposed method: delay, stop severity index, maximum queue, and vehicle trajectory plots. The test results confirmed that DBAT provided a better offset solution than other bandwidth optimization tools that generally optimized programmed bandwidth only and did not account for early return to green caused by skipped or gapped-out movements. Under the DBAT offsets, delay for the through movements on the corridor decreased by 52.8% for northbound vehicles and 46.83% for southbound vehicles. The average delay reduction over all measured paths for uncongested and congested scenarios was 13.88% and 3.50%, respectively. The proposed method and workflow can significantly reduce the offset retiming work process. Normally, this manual process takes more than a day, but the proposed method can be completed in less than an hour without visiting the study site. Furthermore, the proposed method can coordinate any set of movements, as well as multiple travel paths. The authors believe that the proposed method and workflow will significantly help both retiming and new timing of arterial signal coordination along DDI corridors and other signal systems.