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Dr. Yi Qi
Texas Southern University

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0 Mathmatics
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0 Machine and Deep Learning

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Journal article
Published: 12 July 2021 in Future Transportation
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The extent of the deployment of Intelligent Transportation Systems (ITSs) for work zone construction projects has increased in recent years. However, highway agencies are unable to meet the full demand of the deployment of ITSs in work zones in a fiscally constrained environment. Therefore, it is desirable to establish guidelines to help highway agencies to consider installing ITS in work zones as funding becomes available. The goal of this research is to develop a methodology and guideline to assist project designers in assessing whether a particular work zone construction or maintenance project should be considered for the deployment of one or more ITSs. If so, the guideline would assist in determining the ITSs that would be most appropriate for the project. To achieve this goal, the researchers: (1) investigated technologies and evaluated different ITSs that could be used in work zone projects, (2) selected the criteria that would have to be evaluated to identify the eligible work zone projects for the deployment of ITSs, and (3) developed a selection methodology to assist project designers in selecting one or more work zone ITSs in order to be deployed in the project. The outcomes of this study provide a guideline for use in selecting and implementing ITSs for a work zone construction or maintenance project.

ACS Style

Mehdi Azimi; Ibukunoluwa Oyelade; Akintola Aremu; Esmaeil Balal; Ruey Cheu; Yi Qi. Selection and Implementation of Intelligent Transportation Systems for Work Zone Construction Projects. Future Transportation 2021, 1, 169 -187.

AMA Style

Mehdi Azimi, Ibukunoluwa Oyelade, Akintola Aremu, Esmaeil Balal, Ruey Cheu, Yi Qi. Selection and Implementation of Intelligent Transportation Systems for Work Zone Construction Projects. Future Transportation. 2021; 1 (2):169-187.

Chicago/Turabian Style

Mehdi Azimi; Ibukunoluwa Oyelade; Akintola Aremu; Esmaeil Balal; Ruey Cheu; Yi Qi. 2021. "Selection and Implementation of Intelligent Transportation Systems for Work Zone Construction Projects." Future Transportation 1, no. 2: 169-187.

Journal article
Published: 02 June 2021 in Sustainability
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Contraflow Left-Turn Lanes (CLLs) have the potential of being a solution for mitigating congestions at signalized intersections where split phasing is recommended or required. However, the current signal timing strategy for the intersections with CLLs cannot be directly applied at the signalized intersections with split phasing (SIWSP). To address this problem, this study proposed an innovative signal timing strategy, which is referred to as Counterclockwise Split Phasing (CSP) signal timing, for implementing the CLLs at the SIWSPs. A traffic simulation-based case study was conducted and the results indicate that, by using the proposed CSP signal timing plan, CLLs can be implemented at the SIWSP and can significantly reduce the traffic congestions caused by the high left-turn demand at this type of intersection. In addition, since the proposed CSP signal timing design procedure has fully considered the clearance time requirements for the left-turn vehicles on the CLLs, the risk associated with the use of CLLs can be controlled which makes it safe to use this innovative intersection design at SIWSPs.

ACS Style

Rongwei Guo; Jinli Liu; Yi Qi. An Innovative Signal Timing Strategy for Implementing Contraflow Left-Turn Lanes at Signalized Intersections with Split Phasing. Sustainability 2021, 13, 6307 .

AMA Style

Rongwei Guo, Jinli Liu, Yi Qi. An Innovative Signal Timing Strategy for Implementing Contraflow Left-Turn Lanes at Signalized Intersections with Split Phasing. Sustainability. 2021; 13 (11):6307.

Chicago/Turabian Style

Rongwei Guo; Jinli Liu; Yi Qi. 2021. "An Innovative Signal Timing Strategy for Implementing Contraflow Left-Turn Lanes at Signalized Intersections with Split Phasing." Sustainability 13, no. 11: 6307.

Journal article
Published: 31 May 2021 in Research in Transportation Economics
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Taxi is one important component of ground transportation at airports. Taxi drivers face two options after dropping off passengers: waiting to pick up passengers at the airport or ditching the airport and searching elsewhere for their next trips. Understanding how taxi drivers make decisions will not only benefit themselves but also benefit passengers. In addition, policies can be made to balance the taxi supply and demand at airports. In this research, a M/M/1/∞/N model was developed to investigate taxi drivers' decision-making mechanism based on queueing theory. By comparing the net income of these two options in the same time period, a better strategy could be selected. The model was then validated by a case study conducted at Yaoqiang International Airport in Jinan, China. With the model established, drivers' decisions in different time periods could be determined. By analyzing the model results, it was found that the results obtained by the model were consistent with the real-world situations. Furthermore, it was also discovered that taxi drivers’ decisions were strongly influenced by the number of flights taking off and landing in a certain period.

ACS Style

Wen Jia; Yu-Lin Huang; Qun Zhao; Yi Qi. Modeling taxi drivers’ decisions at airport based on queueing theory. Research in Transportation Economics 2021, 101093 .

AMA Style

Wen Jia, Yu-Lin Huang, Qun Zhao, Yi Qi. Modeling taxi drivers’ decisions at airport based on queueing theory. Research in Transportation Economics. 2021; ():101093.

Chicago/Turabian Style

Wen Jia; Yu-Lin Huang; Qun Zhao; Yi Qi. 2021. "Modeling taxi drivers’ decisions at airport based on queueing theory." Research in Transportation Economics , no. : 101093.

Journal article
Published: 22 March 2021 in IEEE Access
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This paper investigates the partial anti-synchronization in a class of chaotic and hyper-chaotic systems. Firstly, the existence of the partial anti-synchronization for the chaotic system is proved. By a systematic method including two algorithms, all solutions of the partial anti-synchronization for a given chaotic system are then derived, and physical controllers are designed. Finally, some illustrative examples with numerical simulations are used to verify the validity and effectiveness of the theoretical results.

ACS Style

Rongwei Guo; Yi Qi. Partial Anti-Synchronization in a Class of Chaotic and Hyper-Chaotic Systems. IEEE Access 2021, 9, 46303 -46312.

AMA Style

Rongwei Guo, Yi Qi. Partial Anti-Synchronization in a Class of Chaotic and Hyper-Chaotic Systems. IEEE Access. 2021; 9 (99):46303-46312.

Chicago/Turabian Style

Rongwei Guo; Yi Qi. 2021. "Partial Anti-Synchronization in a Class of Chaotic and Hyper-Chaotic Systems." IEEE Access 9, no. 99: 46303-46312.

Journal article
Published: 08 March 2021 in Sustainability
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As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals.

ACS Style

Wenrui Qu; Tao Tao; Bo Xie; Yi Qi. A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals. Sustainability 2021, 13, 2917 .

AMA Style

Wenrui Qu, Tao Tao, Bo Xie, Yi Qi. A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals. Sustainability. 2021; 13 (5):2917.

Chicago/Turabian Style

Wenrui Qu; Tao Tao; Bo Xie; Yi Qi. 2021. "A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals." Sustainability 13, no. 5: 2917.

Journal article
Published: 01 March 2021 in Journal of Transportation Engineering, Part A: Systems
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Because continuous-flow intersections (CFIs) are a relatively new intersection design, there are few existing guidelines for designing signal timings for CFIs. An appropriate signal-timing plan will maximize the capacity of the intersection, reduce congestion, and improve safety. This research developed a new signal-timing strategy for CFIs that is based on traffic progression. This new CFI signal-timing strategy was evaluated by conducting traffic simulation-based experiments, and the results of the evaluation showed that it outperformed the signal-timing plan provided by a commonly used existing signal-timing optimization tool. The proposed signal-timing strategy can reduce average traffic delay by 24%, average vehicle travel time by 8.5%, and average queue length by 28.8% at the studied CFI.

ACS Style

Wenrui Qu; Shaojie Liu; Qun Zhao; Yi Qi. Development of a Progression-Based Signal-Timing Strategy for Continuous-Flow Intersections. Journal of Transportation Engineering, Part A: Systems 2021, 147, 04021002 .

AMA Style

Wenrui Qu, Shaojie Liu, Qun Zhao, Yi Qi. Development of a Progression-Based Signal-Timing Strategy for Continuous-Flow Intersections. Journal of Transportation Engineering, Part A: Systems. 2021; 147 (3):04021002.

Chicago/Turabian Style

Wenrui Qu; Shaojie Liu; Qun Zhao; Yi Qi. 2021. "Development of a Progression-Based Signal-Timing Strategy for Continuous-Flow Intersections." Journal of Transportation Engineering, Part A: Systems 147, no. 3: 04021002.

Research article
Published: 26 October 2020 in Journal of Advanced Transportation
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The goal of this study was to develop a new method for identifying the actual risky spots by using the geographic information system (GIS). For this purpose, in this study, three different methods for detecting hotspots are developed, i.e., (1) the annual average daily traffic (AADT) normalization method, (2) AK crashes (A is the incapacitating crash, and K is the fatal crash) percentage method, and (3) distribution difference method. To evaluate the performances of these three hotspot detection methods along with a baseline method that only considered the frequency of crashes, we applied these three methods to identify the top 20 hotspots for truck crashes in two representative areas in Texas. The results indicated that (1) all three proposed methods produced more reasonable results than the baseline method, and (2) the “distribution difference” method outperformed the other methods.

ACS Style

Wenrui Qu; Shaojie Liu; Qun Zhao; Yi Qi. Methods for Identifying Truck Crash Hotspots. Journal of Advanced Transportation 2020, 2020, 1 -9.

AMA Style

Wenrui Qu, Shaojie Liu, Qun Zhao, Yi Qi. Methods for Identifying Truck Crash Hotspots. Journal of Advanced Transportation. 2020; 2020 ():1-9.

Chicago/Turabian Style

Wenrui Qu; Shaojie Liu; Qun Zhao; Yi Qi. 2020. "Methods for Identifying Truck Crash Hotspots." Journal of Advanced Transportation 2020, no. : 1-9.

Journal article
Published: 22 October 2020 in Entropy
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Crashes that involved large trucks often result in immense human, economic, and social losses. To prevent and mitigate severe large truck crashes, factors contributing to the severity of these crashes need to be identified before appropriate countermeasures can be explored. In this research, we applied three tree-based machine learning (ML) techniques, i.e., random forest (RF), gradient boost decision tree (GBDT), and adaptive boosting (AdaBoost), to analyze the factors contributing to the severity of large truck crashes. Besides, a mixed logit model was developed as a baseline model to compare with the factors identified by the ML models. The analysis was performed based on the crash data collected from the Texas Crash Records Information System (CRIS) from 2011 to 2015. The results of this research demonstrated that the GBDT model outperforms other ML methods in terms of its prediction accuracy and its capability in identifying more contributing factors that were also identified by the mixed logit model as significant factors. Besides, the GBDT method can effectively identify both categorical and numerical factors, and the directions and magnitudes of the impacts of the factors identified by the GBDT model are all reasonable and explainable. Among the identified factors, driving under the influence of drugs, alcohol, and fatigue are the most important factors contributing to the severity of large truck crashes. In addition, the exists of curbs and medians and lanes and shoulders with sufficient width can prevent severe large truck crashes.

ACS Style

Jinhong Li; Jinli Liu; Pengfei Liu; Yi Qi. Analysis of Factors Contributing to the Severity of Large Truck Crashes. Entropy 2020, 22, 1191 .

AMA Style

Jinhong Li, Jinli Liu, Pengfei Liu, Yi Qi. Analysis of Factors Contributing to the Severity of Large Truck Crashes. Entropy. 2020; 22 (11):1191.

Chicago/Turabian Style

Jinhong Li; Jinli Liu; Pengfei Liu; Yi Qi. 2020. "Analysis of Factors Contributing to the Severity of Large Truck Crashes." Entropy 22, no. 11: 1191.

Journal article
Published: 02 October 2020 in Sustainability
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The intersection is a bottleneck in an urban roadway network. As traffic demand increases, there is a growing congestion problem at urban intersections. Short-term traffic flow forecasting is crucial for advanced trip planning and traffic management. However, there are only a handful of existing models for forecasting intersection traffic flow. In addition, previous short-term traffic flow forecasting models usually were for predicting roadway conditions in a very short period, such as one minute or five minutes, which is often too late given that a driver may well be approaching the bottleneck already. Being able to accurately predict traffic congestions in about half-hour advance is very critical for advanced trip planning and traffic management. To fill this gap, this research develops a two-layer stacking model for intersection short-term traffic flow forecasting by integrating the K-nearest neighbor (KNN) and Elman Neural Network modeling methods. It was developed using the 24-h cycle by cycle traffic data collected at a signalized intersection in Jinan, China. The developed model is evaluated by applying it to the same intersection for forecasting the short-term traffic conditions in a different set of days. The prediction performance of this model was compared with four other models developed using some existing non-parametric modeling and machine learning methods, including clustering, backpropagation (BP) neural network, KNN, and Elman Neural Network. The results of this study indicate that the proposed model outperforms other existing models in terms of its prediction accuracy.

ACS Style

Wenrui Qu; Jinhong Li; Lu Yang; Delin Li; Shasha Liu; Qun Zhao; Yi Qi. Short-Term Intersection Traffic Flow Forecasting. Sustainability 2020, 12, 8158 .

AMA Style

Wenrui Qu, Jinhong Li, Lu Yang, Delin Li, Shasha Liu, Qun Zhao, Yi Qi. Short-Term Intersection Traffic Flow Forecasting. Sustainability. 2020; 12 (19):8158.

Chicago/Turabian Style

Wenrui Qu; Jinhong Li; Lu Yang; Delin Li; Shasha Liu; Qun Zhao; Yi Qi. 2020. "Short-Term Intersection Traffic Flow Forecasting." Sustainability 12, no. 19: 8158.

Journal article
Published: 04 September 2020 in International Journal of Environmental Research and Public Health
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Displaced left-turn (DLT) intersections are designed to increase the mobility of vehicles by relocating the left-turn lane (lanes) to the far-left side of the road upstream of the main signalized intersection. Since DLT is a relatively new design and very limited crash data are available, previous studies have focused mainly on the analysis of its operational performance rather than its safety performance. To fill this gap, in this study, we investigated the safety performance of two DLT intersections located in San Marcos, Texas. Crash data from 2011 to April 2018 were extracted from the TxDOT Crash Record Information System (CRIS). These crash data were analyzed using two different approaches, i.e., statistical analysis and collision diagram-based analysis. The results of this study indicated that DLT did not increase the overall crash frequencies at the studied intersections. Traffic crashes related to left turns and right turns were reduced significantly by DLT. Meanwhile, it also caused safety issues related to traffic signage, traffic signal, geometric design, and access management at DLT intersections. Thus, in the implementation of DLT intersections, traffic engineers need to carefully consider different aspects of the DLT intersection design, including access management, traffic signal coordination, and driver acceptance. As a result of these analyses, recommendations were provided for the safe implementation of the DLT design in the future.

ACS Style

Wenrui Qu; Qiao Sun; Qun Zhao; Tao Tao; Yi Qi. Statistical Analysis of Safety Performance of Displaced Left-Turn Intersections: Case Studies in San Marcos, Texas. International Journal of Environmental Research and Public Health 2020, 17, 6446 .

AMA Style

Wenrui Qu, Qiao Sun, Qun Zhao, Tao Tao, Yi Qi. Statistical Analysis of Safety Performance of Displaced Left-Turn Intersections: Case Studies in San Marcos, Texas. International Journal of Environmental Research and Public Health. 2020; 17 (18):6446.

Chicago/Turabian Style

Wenrui Qu; Qiao Sun; Qun Zhao; Tao Tao; Yi Qi. 2020. "Statistical Analysis of Safety Performance of Displaced Left-Turn Intersections: Case Studies in San Marcos, Texas." International Journal of Environmental Research and Public Health 17, no. 18: 6446.

Research article
Published: 22 July 2020 in Mathematical Problems in Engineering
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In this paper, a new synchronization phenomenon, that is, the simultaneity of synchronization and antisynchronization, is investigated for a class of chaotic systems. First, for a given chaotic system, necessary and sufficient conditions for the simultaneity of synchronization and antisynchronization are proved. Then, based on these conditions, all solutions of such synchronization phenomenon for a given chaotic system are derived. After that, physical controllers that are not only simple but also implementable are designed to realize the simultaneity of synchronization and antisynchronization in the above system. Finally, illustrative examples based on numerical simulations are used to verify the validity and effectiveness of the above theoretical results.

ACS Style

Zhi Liu; Rongwei Guo; Yi Qi; Cuimei Jiang. Simultaneity of Synchronization and Antisynchronization in a Class of Chaotic Systems. Mathematical Problems in Engineering 2020, 2020, 1 -8.

AMA Style

Zhi Liu, Rongwei Guo, Yi Qi, Cuimei Jiang. Simultaneity of Synchronization and Antisynchronization in a Class of Chaotic Systems. Mathematical Problems in Engineering. 2020; 2020 ():1-8.

Chicago/Turabian Style

Zhi Liu; Rongwei Guo; Yi Qi; Cuimei Jiang. 2020. "Simultaneity of Synchronization and Antisynchronization in a Class of Chaotic Systems." Mathematical Problems in Engineering 2020, no. : 1-8.

Journal article
Published: 04 May 2020 in Journal of Safety Research
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Due to their size and weight, trucks require more space and time to make left turns when exiting or entering a roadway. Therefore, appropriate median treatments are critical for roadways with substantial truck traffic. The two-way left-turn lane (TWLTL) and raised median (RM) are the two types of median most commonly used to improve roadway mobility and manage roadway accessibility. However, previous studies on these median treatments have focused primarily on the general traffic conditions and geometric roadway features without considering the truck traffic impact. To fill this gap, this study investigates the truck impacts on TWLTL and RM by considering two major influencing factors – truck percentage and roadway access point density. First, a negative binomial regression is developed to analyze the relationship between crash frequency and various influencing factors. Next, the crash rate difference analysis between the TWLTL and RM is conducted to identify critical points for these two factors. The findings indicate that, compared with RM, TWLTL has significantly higher crash frequency, especially for roadways with a higher percentage of trucks. This suggests that the percentage of trucks should be taken into consideration when selecting an appropriate type of roadway median.

ACS Style

Wenrui Qu; Tao Tao; Qun Zhao; Qiao Sun; Yi Qi. Two-way left turn lane or raised median? A truck safety based study. Journal of Safety Research 2020, 74, 109 -117.

AMA Style

Wenrui Qu, Tao Tao, Qun Zhao, Qiao Sun, Yi Qi. Two-way left turn lane or raised median? A truck safety based study. Journal of Safety Research. 2020; 74 ():109-117.

Chicago/Turabian Style

Wenrui Qu; Tao Tao; Qun Zhao; Qiao Sun; Yi Qi. 2020. "Two-way left turn lane or raised median? A truck safety based study." Journal of Safety Research 74, no. : 109-117.

Journal article
Published: 27 March 2020 in IEEE Access
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This paper investigates the stabilization of a class of chaotic systems with both model uncertainty and external disturbance. By combining the dynamic feedback control method, and the uncertainty and disturbance estimator (UDE)-based control method, a new UDE-based control method is developed. By using this method, the system stabilization can be achieved by three steps. Illustrative examples using numerical simulations verify the soundness and effectiveness of the proposed method.

ACS Style

Xiaofeng Yi; Rongwei Guo; Yi Qi. Stabilization of Chaotic Systems With Both Uncertainty and Disturbance by the UDE-Based Control Method. IEEE Access 2020, 8, 62471 -62477.

AMA Style

Xiaofeng Yi, Rongwei Guo, Yi Qi. Stabilization of Chaotic Systems With Both Uncertainty and Disturbance by the UDE-Based Control Method. IEEE Access. 2020; 8 (99):62471-62477.

Chicago/Turabian Style

Xiaofeng Yi; Rongwei Guo; Yi Qi. 2020. "Stabilization of Chaotic Systems With Both Uncertainty and Disturbance by the UDE-Based Control Method." IEEE Access 8, no. 99: 62471-62477.

Preprint
Published: 13 May 2019
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In spite of its importance, passenger demand prediction is a highly challenging problem, because the demand is simultaneously influenced by the complex interactions among many spatial and temporal factors and other external factors such as weather. To address this problem, we propose a Spatio-TEmporal Fuzzy neural Network (STEF-Net) to accurately predict passenger demands incorporating the complex interactions of all known important factors. We design an end-to-end learning framework with different neural networks modeling different factors. Specifically, we propose to capture spatio-temporal feature interactions via a convolutional long short-term memory network and model external factors via a fuzzy neural network that handles data uncertainty significantly better than deterministic methods. To keep the temporal relations when fusing two networks and emphasize discriminative spatio-temporal feature interactions, we employ a novel feature fusion method with a convolution operation and an attention layer. As far as we know, our work is the first to fuse a deep recurrent neural network and a fuzzy neural network to model complex spatial-temporal feature interactions with additional uncertain input features for predictive learning. Experiments on a large-scale real-world dataset show that our model achieves more than 10% improvement over the state-of-the-art approaches.

ACS Style

Xiaoyuan Liang; Guiling Wang; Martin Renqiang Min; Yi Qi; Zhu Han. A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction. 2019, 1 .

AMA Style

Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han. A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction. . 2019; ():1.

Chicago/Turabian Style

Xiaoyuan Liang; Guiling Wang; Martin Renqiang Min; Yi Qi; Zhu Han. 2019. "A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction." , no. : 1.

Articles
Published: 12 February 2019 in Journal of the Air & Waste Management Association
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Signalized intersections have been identified as vehicle emission hotspots, where drivers decelerate, idle, and accelerate their vehicles in response to signal changes. Advanced traffic signal status warning systems (ATSSWSs) can be applied to reduce traffic emissions at intersections by mitigating unnecessary braking and acceleration. In this study, two types of ATSSWSs - variable message sign (VMS)-based and vehicle-to-infrastructure (V2I)-based were designed, and their environmental effectiveness was evaluated through driving simulator-based experiments. Three scenarios were designed and tested: 1) baseline without an ATSSWS, 2) with the VMS-based ATSSWS, and 3) with the V2I-based ATSSWS. The Motor Vehicle Emission Simulator model was used to evaluate and compare the environmental effectiveness of these two types of ATSSWSs. The results indicate that the proposed ATSSWSs can reduce traffic emissions at signalized intersections. In particular, the V2I-based ATSSWS can substantially reduce CO2, NOx, CO, and HC emissions. The results will help transportation practitioners with implementing advanced driver information systems and decision-makings on emission reduction policies.

ACS Style

Xiaofei Sun; Xumei Chen; Yi Qi; Bimin Mao; Lei Yu; Peijia Tang. Effects of advanced traffic signal status warning systems on vehicle emission reductions at signalized intersections. Journal of the Air & Waste Management Association 2019, 69, 391 -401.

AMA Style

Xiaofei Sun, Xumei Chen, Yi Qi, Bimin Mao, Lei Yu, Peijia Tang. Effects of advanced traffic signal status warning systems on vehicle emission reductions at signalized intersections. Journal of the Air & Waste Management Association. 2019; 69 (4):391-401.

Chicago/Turabian Style

Xiaofei Sun; Xumei Chen; Yi Qi; Bimin Mao; Lei Yu; Peijia Tang. 2019. "Effects of advanced traffic signal status warning systems on vehicle emission reductions at signalized intersections." Journal of the Air & Waste Management Association 69, no. 4: 391-401.

Research article
Published: 29 August 2018 in Transportation Research Record: Journal of the Transportation Research Board
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Since 1994, Texas has had the highest number of fatal crashes involving large trucks in the United States, and this number increased by 82% from 2009 to 2012. Due to the size and weight of large trucks, their crashes usually are very destructive. Although large trucks have a significant impact on traffic safety in Texas, very little analysis has been conducted of the risk factors associated with crashes involving large trucks, especially the roadway-related risk factors. In this paper, the results of a collision-diagram-based analysis are presented for selected areas in Texas where frequent crashes of large trucks occur. First, historical data related to large truck crashes from 2011 through 2015 were extracted and entered into ArcGIS to identify areas within a 0.5-mi radius of where large truck crashes occur frequently, which were named hot spots. Then, based on the results of the identified hot spots, we identified hot areas, that is, areas with clusters of hot spots. Police reports of all of the crashes that occurred in the selected hot areas were then reviewed, and collision diagrams were developed. By analyzing all of the collision diagrams that were developed, five roadway-related risk factors were identified, and potential effective countermeasures were proposed to prevent or mitigate crashes involving large trucks.

ACS Style

Qun Zhao; Tyrie Goodman; Mehdi Azimi; Yi Qi. Roadway-Related Truck Crash Risk Analysis: Case Studies in Texas. Transportation Research Record: Journal of the Transportation Research Board 2018, 2672, 20 -28.

AMA Style

Qun Zhao, Tyrie Goodman, Mehdi Azimi, Yi Qi. Roadway-Related Truck Crash Risk Analysis: Case Studies in Texas. Transportation Research Record: Journal of the Transportation Research Board. 2018; 2672 (34):20-28.

Chicago/Turabian Style

Qun Zhao; Tyrie Goodman; Mehdi Azimi; Yi Qi. 2018. "Roadway-Related Truck Crash Risk Analysis: Case Studies in Texas." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 34: 20-28.

Articles
Published: 22 March 2018 in Transportation Planning and Technology
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Auxiliary lanes connecting freeway entrance and exit ramps provide additional space for entering and exiting vehicles to change lanes. The method of dropping auxiliary lanes is critical in the design of freeway auxiliary lanes. This study investigates the performance of different methods of dropping auxiliary lanes. Case studies were conducted at two selected freeway segments with successive entrance or exit ramps in the City of Houston. Traffic simulation analysis results of these two case studies show that additional operational benefits can be achieved by extending an auxiliary lane beyond the freeway weaving segment. The study also found that if the weaving segment is followed by an entrance/exit ramp and this ramp has high traffic volume, it can be less operationally favorable to extend and terminate the auxiliary lane at this entrance/exit ramp location. Instead, dropping the auxiliary lane before this entrance/exit ramp represents a more operationally effective option.

ACS Style

Yi Qi; Yubian Wang; Xiaoming Sammy Chen; Ruey Long Cheu; Lei Yu; Hualiang Teng. Methods of dropping auxiliary lanes at freeway weaving segments. Transportation Planning and Technology 2018, 41, 1 -13.

AMA Style

Yi Qi, Yubian Wang, Xiaoming Sammy Chen, Ruey Long Cheu, Lei Yu, Hualiang Teng. Methods of dropping auxiliary lanes at freeway weaving segments. Transportation Planning and Technology. 2018; 41 (4):1-13.

Chicago/Turabian Style

Yi Qi; Yubian Wang; Xiaoming Sammy Chen; Ruey Long Cheu; Lei Yu; Hualiang Teng. 2018. "Methods of dropping auxiliary lanes at freeway weaving segments." Transportation Planning and Technology 41, no. 4: 1-13.

Conference paper
Published: 18 January 2018 in CICTP 2017
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Passenger cars easily get in conflict with buses and non-motor vehicles near curbside bus stops. To analyze the difference of car delays between peak and off-peak hours under the influence of the mixed traffic flow near a curbside bus stop, the survival analysis method was introduced. The Cox’s proportional hazard (CPH) model was used. Traffic volume and traffic behavior data related with passenger cars, buses, and non-motor vehicles were considered in the CPH model. The results indicated that bus dwelling violation and percentage of electric bicycles influenced the car delays significantly during peak hours, while made no difference during off-peak hours. The estimated models can be used to forecast the delay time of cars near curbside bus stops during peak and off-peak hours respectively under mixed traffic flow. The study is useful for bus stop station design and management with the consideration of car delays nearby.

ACS Style

Aihua Fan; Xumei Chen; Xiaobao Yang; Weibin Kou; Yi Qi. Traffic Delay Analysis near the Curbside Bus Stop Based on CPH Model. CICTP 2017 2018, 1 .

AMA Style

Aihua Fan, Xumei Chen, Xiaobao Yang, Weibin Kou, Yi Qi. Traffic Delay Analysis near the Curbside Bus Stop Based on CPH Model. CICTP 2017. 2018; ():1.

Chicago/Turabian Style

Aihua Fan; Xumei Chen; Xiaobao Yang; Weibin Kou; Yi Qi. 2018. "Traffic Delay Analysis near the Curbside Bus Stop Based on CPH Model." CICTP 2017 , no. : 1.

Original articles
Published: 18 April 2017 in Transportation Planning and Technology
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Lane closures due to highway work zones present many challenges to the goal of ensuring smooth traffic operations and a safe environment for both drivers and workers. Late merge behavior at a work zone closure is a dangerous behavior that impacts the traffic conflicts upstream of work zone closures. This paper analyzes the safety impacts of using a signalized lane control strategy at the work zone merge points. To achieve the objective of this research, a field study has been conducted at a highway work zone to collect traffic and driver behavior data, and a two-stage, simulation-based approach is used to analyze the safety impacts of implementing a signalized lane merge control strategy at the studied work zone. In the first stage, micro-simulation models are developed and calibrated based on field data to generate vehicle trajectories. In the second stage, the U.S. Federal Highway Administration’s Surrogate Safety Assessment Model is employed to identify potential conflicts under different traffic conditions. The paper concludes that a proposed signal control device could significantly reduce lane-change conflicts at work zone merge points. In addition, recommendations on the signal cycle length and timing splits are provided.

ACS Style

Yi Qi; Qun Zhao. Safety impacts of signalized lane merge control at highway work zones. Transportation Planning and Technology 2017, 869, 1 -15.

AMA Style

Yi Qi, Qun Zhao. Safety impacts of signalized lane merge control at highway work zones. Transportation Planning and Technology. 2017; 869 (5):1-15.

Chicago/Turabian Style

Yi Qi; Qun Zhao. 2017. "Safety impacts of signalized lane merge control at highway work zones." Transportation Planning and Technology 869, no. 5: 1-15.

Technical papers
Published: 02 June 2016 in Journal of the Air & Waste Management Association
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The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO2 emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation. Implications: This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.

ACS Style

Yi Qi; Ameena Padiath; Qun Zhao; Lei Yu. Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES. Journal of the Air & Waste Management Association 2016, 66, 1003 -1011.

AMA Style

Yi Qi, Ameena Padiath, Qun Zhao, Lei Yu. Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES. Journal of the Air & Waste Management Association. 2016; 66 (10):1003-1011.

Chicago/Turabian Style

Yi Qi; Ameena Padiath; Qun Zhao; Lei Yu. 2016. "Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES." Journal of the Air & Waste Management Association 66, no. 10: 1003-1011.