Browsing by Author "Kluger, Robert"

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    A Connected Vehicle–Enabled Virtual Dynamic Message Sign System Demonstration and Evaluation on the Virginia Connected Vehicle Test Bed
    Park, Hyungjun; Babiceanu, Simona; Kluger, Robert; Smith, Brian L.; Recht, David (Connected Vehicle/Infrastructure University Transportation Center, 2016-03-15)
    Dynamic message signs (DMSs) are widely used to deliver traveler information. While these have proven to be effective, key limitations exist: (1) the locations of DMSs are fixed, (2) reading a DMS message is distracting to drivers, and (3) installation and maintenance of DMSs is expensive. To address these limitations, a smartphone-based virtual DMS (VDMS) application was developed in the first round of Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC) projects. This application used smartphones to provide audible “reading” of DMS messages to drivers. This project built upon previous work to develop a more advanced, second generation of the VDMS system, that is fully integrated in the Dedicated Short Range Communications (DSRC) environment of the Virginia Connected Vehicle Test Bed. The highlights of the enhanced VDMS system include (1) use of four of 40+ DSRC-based roadside equipment units (RSEs) on the Virginia Connected Vehicle Test Bed, and (2) software (VDMS Manager) that has the capability to virtually “build” new DMSs and to create modified and new messages for those DMSs. To evaluate the VDMS system as an information dissemination tool to support advanced traffic management, operational testing (including three surveys, entrance, post-incident, and exit) was carried out with actual operators at the McConnell Public Safety and Traffic Operations Center. It was observed that operators preferred the VDMS system due to its capability of providing more detailed and customized messages at more appropriate locations for motorists.
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    Infrastructure Safety Assessment in a Connected Vehicle Environment
    Smith, Brian L.; Kluger, Robert; Park, Hyungjun (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2015-12-15)
    The goal of the Infrastructure Safety Assessment in a Connected Vehicle (CV) Environment project was to develop a method to identify infrastructure safety “hot spots” using CV data. Using these basic safety messages to detect hot spots may allow for quicker discovery than traditional methods, such as police-reported crashes. The basic safety message may be able to detect events that police normally cannot obtain, including unreported crashes and near-crashes. The project successfully explored some models and algorithms to detect crashes and near-crashes and also designed a methodology to apply to hot spot identification. With the data available, conclusive results were not achieved; however, the models showed some potential. Three techniques were tested to predict crashes using vehicles’ kinematic data. To predict where a crash was occurring, multivariate adaptive regression splines, classification and regression trees, and a novel pattern matching approach were all tested. The models were able to identify the majority of 13 known crashes with different amounts of false positives. The pattern matching approach outperformed a simple acceleration threshold by identifying nearly 70% of crashes in a crash- only test set and 74% of near-crashes in a near-crash only test set. On the training set, it was able to identify more crashes than the thresholds without increasing the number of false positives observed. Based on the work described in this report, the CVI-UTC is fully prepared to apply the methodology to data collected on the field test bed.