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Richmond, VA, United States

Jun J.,401 East Broad Street
Transportation Research Part C: Emerging Technologies | Year: 2010

Understanding the variability of speed patterns and congestion characteristics of interstate freeway systems caused by holiday traffic is beneficial because appropriate countermeasures for safety improvement and congestion mitigation can be prepared and drivers can avoid traffic congestion and change their holiday travel schedules. This study evaluated the traffic congestion patterns during the Thanksgiving holiday period in 2006 using a Gaussian mixture speed distribution estimated by the Expectation-Maximization (EM) algorithm. This mathematical approach showed the potential of improving freeway operational performance evaluation schemes for holiday periods (even non-holiday periods). This study suggested that a Gaussian mixture model using the EM algorithm could be used to properly characterize the severity and the variability of congestion on certain interstate roadway systems. However, this study also pointed out that the fundamental limitations of the mixture model and the statistical significance test about the mixture components should be well understood and need to be further investigated. In addition, because this study investigated the changing patterns of speed distributions with only one interstate freeway system, I-95 northbound, other freeway systems with both directions need to be evaluated so that a more broad and confident analysis on holiday traffic can be achieved. © 2010. Source

So J.,TU Munich | Lim I.-K.,401 East Broad Street | Kweon Y.-J.,Virginia Center for Transportation Innovation and Research
Transportation Research Record | Year: 2015

This study explored potential use of a traffic conflict-based surrogate safety assessment as an alternative way of evaluating the safety performance of roads and identifying potential sites for safety improvement. The study compared two major safety assessment streams (a statistical modeling method and a traffic conflict-based method) in their evaluation of crash risk to investigate the performance of the traffic conflict-based method as an alternative to the crash-based method in identification of hot spots. The empirical Bayes (EB) method coupled with the safety performance function (SPF), called the EB-SPF method, was used as a benchmark, and the conventional crash frequency method was used as a comparison supplement These two methods were viewed as the crash-based methods becau.sc they relied on crash data. Traffic conflicts were estimated through the microscopic traffic simulation model VISSIM. The safety evaluation was performed separately for 24 signalized intersections and 86 segments in the Tysons Corner, Virginia, area. The safety measures estimated by the three methods (i.e., EB-SPF, crash frequency, and traffic conflict) were compared through Pearson correlation analysis, and hot spot identification results were compared through the use of rank-based mean absolute error values. Results showed that the conflict-based method had a fairly high correlation and a coefficient of 0.71 with the EB-SPF method in the resulting outcomes and performed better than the crash frequency method in identifying hot spots. Therefore, the conflict-based method can serve as a viable option for safety performance evaluation and hot spot identification, especially when sufficient crash data arc not obtainable. Source

Lim I.-K.,401 East Broad Street | Kweon Y.-J.,Virginia Center for Transportation Innovation and Research
Transportation Research Record | Year: 2013

Identifying high-crash-risk locations, called hot spots, is an important step in improving roadway safety. Use of the empirical Bayes (EB) method coupled with the use of safety performance functions (SPFs) is considered the state of the practice in identifying such locations. However, application of the EB-SPF method requires considerable resources in preparing data, as well as statistical expertise. As a consequence, many highway agencies still rely on traditional methods that use crash frequency and crash rate to identify locations for potential safety improvements without knowing the accuracy of such methods. This study examined four traditional methods commonly used in identifying potential locations for safety improvements and compared them with the EB-SPF method. The four methods evaluated were crash frequency, crash rate, rate-quality control, and equivalent property damage only. The study was limited to four-leg intersections with either a traffic signal or two-way stop control; 2004 to 2008 data were collected for 1,670 such intersections. The study found that the crash frequency method performed the best of the four in correctly identifying the top 1% of unsafe intersections. However, the method tended to flag top hot spots incorrectly. The rate-quality control method performed the best in identifying the top 5% and 10% of unsafe intersections. The findings are expected to help highway agencies that continue to use the traditional methods choose the most appropriate method so that scarce resources available for safety improvement can be invested effectively. Source

Daoulas J.C.,401 East Broad Street
Geotechnical Special Publication | Year: 2011

The use of the design-build procurement process by transportation agencies has become increasingly popular to accelerate advertisement of projects. The risks associated with this type of procurement process differ from the traditional design-bid-build process. This is particularly true for geo-engineering risks. These risks are of concern for both agencies and design-builders since they can result in escalation of contingency costs in the price proposal and unforeseen costs after award if not properly identified and mitigated. The purpose of this paper is to provide insight on how this particular issue is being addressed by the Virginia Department of Transportation (VDOT) in their DB program. The paper addresses key elements that should be considered in assessing geo-engineering risks and methods that can be used to mitigate these risks. The paper also addresses the importance in development of technical requirements to clearly define the project objectives to ensure greater uniformity and fairness in preparation of price proposals. © 2011 ASCE. Source

Son S.,Old Dominion University | Khattak A.,Old Dominion University | Wang X.,Old Dominion University | Chen J.-Y.,401 East Broad Street
Transportation Research Record | Year: 2013

Identifying and minimizing potential errors in household travel surveys can facilitate collecting more representative and accurate data. Through a comparison of two recent travel surveys with census data, this paper presents how sampling, noncoverage, nonresponse, and measurement errors work their way into surveys. The 2009 National Household Travel Survey (NHTS) Add-On in Virginia was implemented with a comprehensive survey instrument and random-digit-dial (RDD) sampling. The 2008 National Capital Region Household Travel Survey collected behavioral data with a concise instrument, while adopting address-based sampling (ADD). Focusing on a common area of Northern Virginia, this study examined differences in sociodemographics and travel behavior of the extracted samples (N = 597 and N = 3,581, respectively). Results show that the ADD survey collected data on more single-person households, younger individuals, and Hispanics and Mexicans, which are generally identified as hard-to-reach groups. A comparison of the two samples with the census data shows that the ADD sample was more representative of the population and area, partly because of the inclusion of mobile phone-only households (28%), which were not fully covered in RDD. To quantify a measurement error, this study estimated rigorous statistical models in regard to reported trip frequency. Results show that the NHTS captured 10% more trips, partly as a result of diary instructions and the presence of walking and biking questions in the instrument. Details of other errors and implications for reducing key survey errors are discussed. Source

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