@article{xu_rouphail_aghdashi_ahmed_elefteriadou_2020, title={Modeling Framework for Capacity Analysis of Freeway Segments: Application to Ramp Weaves}, volume={2674}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85085987562&partnerID=MN8TOARS}, DOI={10.1177/0361198119900157}, abstractNote={This research proposes a new modeling framework for the analysis of freeway segments. The framework provides a continuum from the operation of ramp weave segments to an equivalent basic segment serving the same traffic with the same number of lanes and free-flow speed. This approach distinguishes between congestion effects caused by high v/c ratios from turbulence caused by merging, diverging, and weaving traffic, thus greatly simplifying the model form, and its extensibility to other freeway segment types. The paper presents an application of this new framework to the analysis of ramp weaves, which were not sufficiently sampled in the development of the HCM6 methodology. The proposed model is shown to be superior to the HCM6 method both in relation to explaining field observations of speeds and in its simplicity in application. The results include a new formula for capacity estimation that is highly sensitive to segment length, and a speed estimation model that converges for low weaving volumes or at very high weaving segment lengths to that observed at a basic segment. Because the proposed model is calibrated with data mostly from North Carolina, it is recommended that data at additional sites be included in a larger calibration effort to ensure its applicability to a broader set of weaving segment configurations.}, number={1}, journal={TRANSPORTATION RESEARCH RECORD}, author={Xu, Dezhong and Rouphail, Nagui M. and Aghdashi, Behzad and Ahmed, Ishtiak and Elefteriadou, Lily}, year={2020}, month={Jan}, pages={148–159} }
 @article{aghdashi_davis_chase_cunningham_2020, title={Modeling and Validating Traffic Responsive Ramp Metering in the Highway Capacity Manual Context}, volume={2674}, ISSN={["2169-4052"]}, DOI={10.1177/0361198120949533}, abstractNote={This paper presents a methodology for modeling traffic responsive (or adaptive) ramp metering in the freeway facilities method based on the sixth edition of the Highway Capacity Manual (HCM6). Currently, the HCM only provides an option to meter on-ramps as user input using 15-min average flow rates with a focus on planning-level analyses. As a result, the possibilities for simulating and modeling ramp meters with any traffic responsive ramp metering algorithm in the HCM context are limited. Moreover, the freeway facilities methodology in the HCM plays a vital role in the analysis of travel time reliability, which is built on a set of operational scenarios. However, with the lack of traffic responsive ramp metering, analysts are burdened with the task of manually entering average effective ramp metering rates for each on-ramp within the set of reliability scenarios. This process can require a substantial amount of time, in addition to increasing the potential for inaccuracy and bias in freeway and performance measure estimations. As a result, this paper is designed to fill a significant research gap by providing a method for analyzing traffic responsive (or adaptive) ramp metering, an active traffic and demand management strategy, using the core freeway facilities methodology in the HCM. The direct application of the method focuses on the MaxView metering algorithm. However, the proposed framework can be used to model any traffic responsive ramp metering algorithm. The results are validated using real-world sites located on the I-540 westbound freeway corridor in North Carolina.}, number={12}, journal={TRANSPORTATION RESEARCH RECORD}, author={Aghdashi, Seyedbehzad and Davis, Joy and Chase, Thomas and Cunningham, Chris}, year={2020}, month={Dec}, pages={91–102} }
 @article{karmakar_aghdashi_rouphail_williams_2018, title={Validation and Calibration of Freeway Reliability Methodology in the Highway Capacity Manual: Method and Case Studies}, volume={2672}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85060939515&partnerID=MN8TOARS}, DOI={10.1177/0361198118798723}, abstractNote={Traffic congestion costs drivers an average of $1,200 a year in wasted fuel and time, with most travelers becoming less tolerant of unexpected delays. Substantial efforts have been made to account for the impact of non-recurring sources of congestion on travel time reliability. The 6th edition of the Highway Capacity Manual (HCM) provides a structured guidance on a step-by-step analysis to estimate reliability performance measures on freeway facilities. However, practical implementation of these methods poses its own challenges. Performing these analyses requires assimilation of data scattered in different platforms, and this assimilation is complicated further by the fact that data and data platforms differ from state to state. This paper focuses on practical calibration and validation methods of the core and reliability analyses described in the HCM. The main objective is to provide HCM users with guidance on collecting data for freeway reliability analysis as well as validating the reliability performance measures predictions of the HCM methodology. A real-world case study on three routes on Interstate 40 in the Raleigh-Durham area in North Carolina is used to describe the steps required for conducting this analysis. The travel time index (TTI) distribution, reported by the HCM models, was found to match those from probe-based travel time data closely up to the 80th percentile values. However, because of a mismatch between the actual and HCM estimated incident allocation patterns both spatially and temporally, and the fact that traffic demands in the HCM methods are by default insensitive to the occurrence of major incidents, the HCM approach tended to generate larger travel time values in the upper regions of the travel time distribution.}, number={15}, journal={TRANSPORTATION RESEARCH RECORD}, author={Karmakar, Nabaruna and Aghdashi, Seyedbehzad and Rouphail, Nagui M. and Williams, Billy M.}, year={2018}, month={Dec}, pages={93–104} }
 @article{rouphail_kim_aghdashi_2017, title={Application of high-resolution vehicle data for free-flow speed estimation}, number={2615}, journal={Transportation Research Record}, author={Rouphail, N. M. and Kim, S. and Aghdashi, S.}, year={2017}, pages={105–112} }
 @article{hajbabaie_aghdashi_rouphail_2016, title={Enhanced decision-making framework using reliability concepts for freeway facilities}, volume={142}, number={4}, journal={Journal of Transportation Engineering}, author={Hajbabaie, A. and Aghdashi, S. and Rouphail, N. M.}, year={2016} }
 @article{kim_song_rouphail_aghdashi_amaro_goncalves_2016, title={Exploring the association of rear-end crash propensity and micro-scale driver behavior}, volume={89}, ISSN={["1879-1042"]}, DOI={10.1016/j.ssci.2016.05.016}, abstractNote={The relationship between driver behavior at the tactical level and crash experience is a long sought association that has been elusive to explore. The availability of in-vehicle sensing devices capable of capturing and documenting micro-scale dynamic driver behavior offers the opportunity to begin such an exploration. This study integrates rear-end crash data experienced on a 63-mile section of I-40 in North Carolina over a four-year period with three months of micro-scale driving behavioral data gathered by an in-vehicle sensing system (i2D) that records and dispatches second by second vehicle dynamics data to a central database. The information collected by the i2D devices came from a fleet of about 20 vehicles driven by volunteers in their naturalistic driving environment. Additionally all crash and driver data were geo-located onto a link-based GIS environment. The objective of this study is to explore the association of crash propensity and micro-scale driving behavior. The initial findings of this research are promising. First, over 85% of all rear-end crashes occurred on 30 segments extending from 2000 feet upstream of an on-ramp to the on-ramp itself. Secondly, on those segments with high crash rates we have detected a high propensity of drivers to decelerate at high rates (4 m/s2 or more). We have also tested and confirmed that the sharp deceleration phenomenon is not confined to a few drivers, but appears to be common for the high-crash segments, using trip-based analyses.}, journal={SAFETY SCIENCE}, author={Kim, SangKey and Song, Tai-Jin and Rouphail, Nagui M. and Aghdashi, Seyedbehzad and Amaro, Ana and Goncalves, Goncalo}, year={2016}, month={Nov}, pages={45–54} }
 @article{aghdashi_hajbabaie_schroeder_trask_rouphail_2015, title={Generating scenarios of freeway reliability analysis hybrid approach}, number={2483}, journal={Transportation Research Record}, author={Aghdashi, S. and Hajbabaie, A. and Schroeder, B. J. and Trask, J. L. and Rouphail, N. M.}, year={2015}, pages={148–159} }
 @article{aghdashi_rouphail_hajbabaie_schroeder_2015, title={Generic speed-flow models for basic freeway segments on general-purpose and managed lanes in undersaturated flow conditions}, number={2483}, journal={Transportation Research Record}, author={Aghdashi, S. and Rouphail, N. M. and Hajbabaie, A. and Schroeder, B. J.}, year={2015}, pages={102–110} }
 @article{aghdashi_schroeder_rouphail_2014, title={Method for scenario selection and probability adjustment for reliability and active traffic management analysis in a highway capacity manual context}, number={2461}, journal={Transportation Research Record}, author={Aghdashi, S. and Schroeder, B. J. and Rouphail, N. M.}, year={2014}, pages={58–65} }
 @article{schroeder_rouphail_aghdashi_2013, title={Deterministic framework and methodology for evaluating travel time reliability on freeway facilities}, number={2396}, journal={Transportation Research Record}, author={Schroeder, B. J. and Rouphail, N. M. and Aghdashi, S.}, year={2013}, pages={61–70} }