@article{ahmed_karr_rouphail_chase_tanvir_2022, title={Characterizing lane changing behavior and identifying extreme lane changing traits}, volume={4}, ISSN={["1942-7875"]}, url={https://doi.org/10.1080/19427867.2022.2066856}, DOI={10.1080/19427867.2022.2066856}, abstractNote={ABSTRACT This study characterizes lane changing behavior of drivers under differing congestion levels and identifies extreme lane changing traits using high-resolution trajectory data. Total lane change frequency exhibited a reciprocal relationship with congestion level, but the distribution of lane change per vehicle remained unchanged as congestion increased. On average, the speed of trajectories increased by 5.4 ft/s after changing a lane. However, this gain significantly diminished as congestion worsened. Further, the average speed of lane changing vehicles was 3.9 ft/s higher than those that executed no lane changes. Two metrics were employed to identify extreme lane changing behavior: critical time-to-line-crossing (TLCc) and lane changes per unit distance. The lowest 1% TLCc varied between 0.71–1.57 seconds. The highest 1% of lane change rates for all lane changing vehicles was 2.5 lane changes per 1,000 ft traveled. Interestingly, no drivers in thisdataset had both excessive lane changes and lane changes with low TLCc.}, journal={TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH}, publisher={Informa UK Limited}, author={Ahmed, Ishtiak and Karr, Alan F. and Rouphail, Nagui M. and Chase, R. Thomas and Tanvir, Shams}, year={2022}, month={Apr} }
 @article{tanvir_chase_roupahil_2021, title={Development and analysis of eco-driving metrics for naturalistic instrumented vehicles}, volume={25}, ISSN={["1547-2442"]}, DOI={10.1080/15472450.2019.1615486}, abstractNote={Abstract This article is concerned with the development of eco-driving metrics for instrumented vehicles in a longitudinal study environment. Motivations for developing such metrics include an ability to distill driving style effects on fuel use from other confounding factors, to contrast and benchmark driving styles for a cohort of drivers and to ascertain the effects of information and/or incentives on fuel use both in the short and long term. High resolution (1 Hz) trip data were collected for a local sample of 35 drivers over a period of 2 years, yielding over 20 million second by second observations. To account for the difference in vehicle type choice, a standard vehicle was used to model fuel consumption based on instantaneous vehicle activity. Difference in route choice was accounted for using speed-bin dependent metrics. Two metrics were developed: a trip-based measure called the fuel efficiency score (FES), and a difference in fuel use metric that uses the second by second observations called the fuel use difference (FUD). FES varies from 20 to 100 while FUD covers positive and negative percentage differences from a speed-bin dependent mean value. Both measures passed the test of consistency so that, at the driver level, both revealed no temporal trend in the scores from month to month across a period of 2 years. Moreover, the FES metric passed the heterogeneity test. It was able to identify four distinct clusters of driving styles.}, number={3}, journal={JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS}, author={Tanvir, Shams and Chase, R. T. and Roupahil, N. M.}, year={2021}, month={May}, pages={235–248} }
 @article{avr_tanvir_rouphail_ahmed_2021, title={Dynamically Collected Local Density using Low-Cost Lidar and its Application to Traffic Models}, volume={5}, ISSN={["2169-4052"]}, DOI={10.1177/03611981211010184}, abstractNote={This article demonstrates the use of traffic density observations collected dynamically in the vicinity of probe vehicles. Fixed position sensors cannot capture the longitudinal evolution of local traffic density in the corridor. In this research, dynamic traffic density observations were collected in a naturalistic driving setting that was free of any controlled experiment biases. Speed from global positioning system and space headway from a light detection and ranging module was collected on one arterial and one freeway segment, 2 and 4 mi long, respectively. The combined data frequency was approximately 3 Hz. Space headway was used to estimate the local density and consequently to identify the density of a specific location in a corridor. Besides, driver behavior was characterized using the relationship between instantaneous speed and local density under different regimes of the Wiedemann car-following model. Macroscopic traffic stream models were used to investigate the relationship between dynamically collected instantaneous speed and local density. Using the longitudinal evolution of density, precise local density across the corridor can be obtained along with the leader and follower trajectories. A method to identify driver behavior across density ranges was developed for different facility types using a microscopic relationship between instantaneous speed and local density. Overall driving behavior on the freeway segment can be represented by translating the instantaneous speed and local density relationship to macroscopic stream models.}, journal={TRANSPORTATION RESEARCH RECORD}, author={Avr, Azhagan and Tanvir, Shams and Rouphail, Nagui M. and Ahmed, Ishtiak}, year={2021}, month={May} }
 @article{ahmed_karr_rouphail_chun_tanvir_2019, title={Characterizing Lane Changes via Digitized Infrastructure and Low-Cost GPS}, volume={2673}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85064917506&partnerID=MN8TOARS}, DOI={10.1177/0361198119841277}, abstractNote={With the expected increase in the availability of trajectory-level information from connected and autonomous vehicles, issues of lane changing behavior that were difficult to assess with traditional freeway detection systems can now begin to be addressed. This study presents the development and application of a lane change detection algorithm that uses trajectory data from a low-cost GPS-equipped fleet, supplemented with digitized lane markings. The proposed algorithm minimizes the effect of GPS errors by constraining the temporal duration and lateral displacement of a lane change detected using preliminary lane positioning. The algorithm was applied to 637 naturalistic trajectories traversing a long weaving segment and validated through a series of controlled lane change experiments. Analysis of naturalistic trajectory data revealed that ramp-to-freeway trips had the highest number of discretionary lane changes in excess of 1 lane change/vehicle. Overall, excessive lane change rates were highest between the two middle freeway lanes at 0.86 lane changes/vehicle. These results indicate that extreme lane changing behavior may significantly contribute to the peak-hour congestion at the site. The average lateral speed during lane change was 2.7 fps, consistent with the literature, with several freeway–freeway and ramp–ramp trajectories showing speeds up to 7.7 fps. All ramp-to-freeway vehicles executed their first mandatory lane change within 62.5% of the total weaving length, although other weaving lane changes were spread over the entire segment. These findings can be useful for implementing strategies to lessen abrupt and excessive lane changes through better lane pre-positioning.}, number={8}, journal={TRANSPORTATION RESEARCH RECORD}, author={Ahmed, Ishtiak and Karr, Alan and Rouphail, Nagui M. and Chun, Gyounghoon and Tanvir, Shams}, year={2019}, month={Aug}, pages={298–309} }
 @article{ahmed_rouphail_tanvir_2018, title={Characteristics and Temporal Stability of Recurring Bottlenecks}, volume={2672}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85060989618&partnerID=MN8TOARS}, DOI={10.1177/0361198118798991}, abstractNote={This study applies and updates a method which identifies and quantifies the extent of traffic congestion from recurring freeway bottlenecks. Additionally, the spatiotemporal stability of bottlenecks over an extended period was tested. Over time congestion at bottlenecks may increase, may decrease, or may migrate to other nearby locations. Analysis of stability is important since prioritizing and applying treatments at bottlenecks is a multiyear process. In addition, a robust method for selecting sensitivity based parameters to identify and quantify bottleneck effects is presented. Subsequently, a systematic framework is developed for tracking and archiving the spatiotemporal changes in the recurring bottlenecks. The proposed method is demonstrated on a case study on Interstate 40 in North Carolina using three years of probe data. A congestion speed ratio detection threshold of 0.7 and a probability of activation threshold of 33% for the study area were determined from a sensitivity test to ascertain their recurrence. The method identified 13 bottlenecks with their impacts ranging from 35 to 3,278 mi-hours of congestion per year. Eight bottlenecks either newly emerged or had their queues merged or shifted between successive years. Even spatially stable bottlenecks had significant variation in their activation frequency and queue length. Exploration of the changes in bottleneck severity and locations revealed the influence of a long-term work zone in the area and the effect of the rapid growth in traffic demand. Local agencies can use this method to shortlist recurring bottlenecks and track changes to plan mitigation strategies.}, number={42}, journal={TRANSPORTATION RESEARCH RECORD}, author={Ahmed, Ishtiak and Rouphail, Nagui M. and Tanvir, Shams}, year={2018}, month={Dec}, pages={235–246} }
 @article{tanvir_frey_rouphail_2018, title={Effect of Light Duty Vehicle Performance on a Driving Style Metric}, volume={2672}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85060916631&partnerID=MN8TOARS}, DOI={10.1177/0361198118796070}, abstractNote={Eco-driving involves alterations to driving style to improve energy efficiency. The observed driving style reflects the combined effects of roadway, traffic, driver, and vehicle performance. Although the effect of roadway and traffic characteristics can be inferred from microscale driving activity data, the effect of vehicle performance on driving style is not properly understood. This paper addresses two questions: (1) how different is an individual driver’s driving style when operating vehicles with differences in performance?; and (2) how dissimilar are the driving styles of different drivers when operating vehicles that have similar performance? To answer these questions, we have gathered microscale vehicle activity measurements from 17 controlled real-world driving schedules and two years of naturalistic driving data from five drivers. We also developed a metric for driving style termed “envelope deviation,” which is a distribution of gaps between microscale activity (1 Hz) and fleet average envelope. We found that there is significant inter-driver heterogeneity in driving styles when controlling for vehicle performance. However, no significant inter-vehicle heterogeneity was present in driving styles while controlling for the driver. Findings from this study imply that the choice of vehicle does not significantly alter the natural driving style of a driver.}, number={25}, journal={TRANSPORTATION RESEARCH RECORD}, author={Tanvir, Shams and Frey, H. Christopher and Rouphail, Nagui M.}, year={2018}, month={Dec}, pages={67–78} }
 @article{tanvir_karmakar_rouphail_schroeder_2016, title={Modeling freeway work zones with mesoscopic dynamic traffic simulator validation, gaps, and guidance}, number={2567}, journal={Transportation Research Record}, author={Tanvir, S. and Karmakar, N. and Rouphail, N. M. and Schroeder, B. J.}, year={2016}, pages={122–130} }
 @article{zhou_tanvir_lei_taylor_liu_rouphail_frey_2015, title={Integrating a simplified emission estimation model and mesoscopic dynamic traffic simulator to efficiently evaluate emission impacts of traffic management strategies}, volume={37}, ISSN={["1361-9209"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84941658996&partnerID=MN8TOARS}, DOI={10.1016/j.trd.2015.04.013}, abstractNote={This paper presents a computationally efficient and theoretically rigorous dynamic traffic assignment (DTA) model and its solution algorithm for a number of emerging emissions and fuel consumption related applications that require both effective microscopic and macroscopic traffic stream representations. The proposed model embeds a consistent cross-resolution traffic state representation based on Newell’s simplified kinematic wave and linear car following models. Tightly coupled with a computationally efficient emission estimation package MOVES Lite, a mesoscopic simulation-based dynamic network loading framework DTALite is adapted to evaluate traffic dynamics and vehicle emission/fuel consumption impact of different traffic management strategies.}, journal={TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT}, author={Zhou, Xuesong and Tanvir, Shams and Lei, Hao and Taylor, Jeffrey and Liu, Bin and Rouphail, Nagui M. and Frey, H. Christopher}, year={2015}, month={Jun}, pages={123–136} }