Academic literature on the topic 'Connected vehicle (CV)'
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Journal articles on the topic "Connected vehicle (CV)"
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Wang, Xingmin, Shengyin Shen, Debra Bezzina, James R. Sayer, Henry X. Liu, and Yiheng Feng. "Data Infrastructure for Connected Vehicle Applications." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 5 (April 9, 2020): 85–96. http://dx.doi.org/10.1177/0361198120912424.
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Ann Arbor Connected Vehicle Test Environment (AACVTE) is the world’s largest operational, real-world deployment of connected vehicles (CVs) and connected infrastructure, with over 2,500 vehicles and 74 infrastructure sites, including intersections, midblocks, and highway ramps. The AACVTE generates a massive amount of data on a scale not seen in the traditional transportation systems, which provides a unique opportunity for developing a wide range of connected vehicle (CV) applications. This paper introduces a data infrastructure that processes the CV data and provides interfaces to support real-time or near real-time CV applications. There are three major components of the data infrastructure: data receiving, data pre-processing, and visualization including the performance measurements generation. The data processing algorithms include signal phasing and timing (SPaT) data compression, lane phase mapping identification, trajectory data map matching, and global positioning system (GPS) coordinates conversion. Simple performance measures are derived from the processed data, including the time–space diagram, vehicle delay, and observed queue length. Finally, a web-based interface is designed to visualize the data. A list of potential CV applications including traffic state estimation, traffic control, and safety, which can be built on this connected data infrastructure is discussed.
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Shao, Yunli, Mohd Azrin Mohd Zulkefli, and Zongxuan Sun. "Vehicle and Powertrain Optimization for Autonomous and Connected Vehicles." Mechanical Engineering 139, no. 09 (September 1, 2017): S19—S23. http://dx.doi.org/10.1115/1.2017-sep-6.
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This article discusses the potential of using autonomous and connected vehicle (CV) technologies to save energy. It also focuses on the potential energy savings of internal combustion engine-based vehicles (ICVs) and hybrid electric vehicles (HEVs). An example of vehicle and powertrain co-optimization for HEV eco-approaching and departure is also given. CV technologies are gaining increasing attention around the world. Vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication enable real-time access to traffic information that was not available before, including preceding vehicles’ location, speed, pedal position, traffic signal phasing and timing (SPaT). The example shown in this article demonstrates the potential benefits from vehicle and powertrain co-optimization by investigating an eco-approaching and departure application. More research in this area can offer more mature solutions to implement such optimization in a real-production vehicle.
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Wei, Lu, Jin-hong Li, Li-wen Xu, Lei Gao, and Jian Yang. "Queue Length Estimation for Signalized Intersections under Partially Connected Vehicle Environment." Journal of Advanced Transportation 2022 (May 2, 2022): 1–11. http://dx.doi.org/10.1155/2022/9568723.
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Queue length is a crucial measurement of traffic signal control at urban intersections. Conventional queue length estimation methods mostly still rely on fixed detectors. The development of connected vehicles (CV) provides massive amounts of vehicle trajectory data, and the queue length estimation based on CV data has received considerable attention in recent years. However, most existing CV-based methods require the prior knowledge of the penetration rate of CV and vehicle arrivals, but the estimation of these prior distributions has not been well studied. To address this issue, this paper proposes a cycle-based queue length estimation method under partially connected vehicle (CV) environment, with the prior vehicle arrivals being unknown. The empirical Bayes method is adopted to estimate the arrival rate by leveraging the observed queued CV information such as the number and positions. The hyperparameter estimation problem of the prior distribution is solved by the maximum likelihood estimation (MLE) method. To validate the proposed queue length estimation method, a simulation environment with partially connected vehicles is established using VISSIM and Python for data generating. The results in terms of normalized mean absolute errors (NMAE) and normalized root mean square errors (NRMSE) show that the proposed method could produce accurate and reliable estimated queue length under various CV penetration rates.
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Miao, Zuoyu, K. Larry Head, and Byungho Beak. "Vehicle Reidentification in a Connected Vehicle Environment using Machine Learning Algorithms." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 45 (May 30, 2018): 160–72. http://dx.doi.org/10.1177/0361198118774691.
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Deployment of connected vehicles will become possible for most American cities in the next 10 to 20 years. Connected vehicle (CV) applications (e.g., mobility, safety, environment) are constantly receiving vehicle data. The current ID protection mechanism assumes a vehicle’s ID changes every 5 minutes, so the topic of rematching vehicles is of interest in privacy protection and performance measure research. This paper explores the possibility of rematching connected vehicles’ IDs using popular machine learning techniques, including logistic regression (LR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), linear and nonlinear support vector machine (SVM) and nearest neighbor algorithms. An experiment is conducted using a microscopic traffic simulation model through a software-in-the-loop technique. The best average mismatching rate is 14%. To assess potential factors’ effects on matching accuracy, a Poisson mixed regression model is analyzed under the Bayesian inference framework. Findings are: different matching algorithms vary in matching performance and the linear SVM, the QDA and the LDA have the best accuracy results; traffic volume and market penetration rate have little impact on matching results; location and number of vehicles to be matched are considered significant. The results make the performance measurement of future CV applications feasible and also suggest that more secure mechanisms are needed to protect the public.
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Chen, Bo, Darrell Robinette, Mahdi Shahbakhti, Kuilin Zhang, Jeff Naber, Jeremy Worm, Christopher Pinnow, and Christopher Morgan. "Connected Vehicles and Powertrain Optimization." Mechanical Engineering 139, no. 09 (September 1, 2017): S12—S18. http://dx.doi.org/10.1115/1.2017-sep-5.
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This article discusses the basic concept of connected and automated vehicles (CAV) technology. The common methods to improve fuel economy are also introduced. The effects of connectivity on vehicle/powertrain control and optimization are also elaborated. The Michigan Tech NEXTCAR project is also presented to provide a more detailed view of predictive vehicle/powertrain control enabled by CAV technologies. The U.S. Department of transportation (DOT) and other federal/state funding agencies have supported research and pilot deployment efforts to develop crosscutting CV technologies and evaluate the effectiveness of CV technologies in real-world transportation systems. The concurrent development of connected and automated vehicle technologies is anticipated to provide synergistic benefits to improve traffic safety, mobility, and energy efficiency. It is observed that increased CAV technologies are being deployed in real-world transportation systems.
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Finley, Melisa D., Cameron R. Mott, Kevin N. Balke, Hassan Charara, Purser K. Sturgeon, David Florence, and Chiara Silvestri Dobrovolny. "Development and Testing of Connected Vehicle Wrong-Way Driving Applications." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 4 (April 2019): 59–69. http://dx.doi.org/10.1177/0361198119839986.
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The Texas A&M Transportation Institute (TTI) and Southwest Research Institute (SwRI) recently developed connected vehicle (CV) applications that detect wrong-way vehicles, warn wrong-way drivers, notify traffic management agencies and law enforcement, and alert affected travelers. The research team reviewed the state of the practice regarding intelligent transportation systems (ITS) and CV technologies being applied as wrong-way driving (WWD) countermeasures. Next, the research team identified user needs associated with the implementation of CV WWD applications, and developed a concept of operations and functional requirements for CV WWD applications. The research team then built, tested, and successfully conducted a proof-of-concept demonstration of the CV WWD applications at the Texas A&M University RELLIS Campus.
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Chandan, Kancharla Kamal Keerthi, Álvaro Jorge Maia Seco, and Ana Maria César Bastos Silva. "A Real-time Traffic Signal Control Strategy Under Partially Connected Vehicle Environment." PROMET - Traffic&Transportation 31, no. 1 (February 27, 2019): 61–73. http://dx.doi.org/10.7307/ptt.v31i1.2832.
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The performance of a traffic system tends to improve as the percentage of connected vehicles (CV) in total flow increases. However, due to low CV penetration in the current vehicle market, improving the traffic signal operation remains a challenging task. In an effort to improve the performance of CV applications at low penetration rates, the authors develop a new method to estimate the speeds and positions of non-connected vehicles (NCV) along a signalized intersection. The algorithm uses CV information and initial speeds and positions of the NCVs from loop detectors and estimates the forward movements of the NCVs using the Gipps’ car-following model. Calibration parameters of the Gipps’ model were determined using a solver optimization tool. The estimation algorithm was applied to a previously developed connected vehicle signal control (CVSC) strategy on two different isolated intersections. Simulations in VISSIM showed the estimation accuracy higher for the intersection with less lanes. Estimation error increased with the decrease in CV penetration and decreased with the decrease in traffic demand. The CVSC strategy with 40% and higher CV penetration (for Intersection 1) and with 20% and higher CV penetration (for Intersection 2) showed better performance in reducing travel time delay and number of stops than the EPICS adaptive control.
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Bertini, Robert L., Haizhong Wang, and Kevin Carstens. "Preparing Oregon for Connected Vehicle Deployment: Application Prioritization Process." Transportation Research Record: Journal of the Transportation Research Board 2615, no. 1 (January 2017): 1–10. http://dx.doi.org/10.3141/2615-01.
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To build on a project recently completed for the Oregon Department of Transportation (DOT), processes and tools were developed to prioritize the implementation of connected vehicle (CV) applications. Internal mechanisms for addressing CV development and deployment at the Oregon DOT were assessed; the technical maturity of each potential CV application was scanned, reviewed, and assessed; preliminary goals were developed; prospective CV applications were linked; and applications that fit with the potential role of the Oregon DOT in advancing these initiatives were refined, prioritized, and ranked. A shared vision and business plan that prioritizes CV applications for Oregon is recommended. An internal effort aimed at producing a small set of priority CV applications for further development is described. This effort culminated in a CV application prioritization workshop that included a priority mapping exercise, discussion of the CV concept, and an initial mapping of goals and applications. The workshop identified seven near-term priority CV applications for the Oregon DOT; 12 applications that the Oregon DOT will monitor (and possibly collaborate on with others in the future); and eight applications that the Oregon DOT will monitor but that will be led by others. The Oregon DOT has used the results of this effort as a springboard for hiring new staff dedicated to CV policy, forming a CV steering team, and launching a CV business plan. The process and tools can be used by other states and transportation agencies in their CV application prioritization processes.
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Rahman, Md Sharikur, Mohamed Abdel-Aty, Ling Wang, and Jaeyoung Lee. "Understanding the Highway Safety Benefits of Different Approaches of Connected Vehicles in Reduced Visibility Conditions." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 19 (June 11, 2018): 91–101. http://dx.doi.org/10.1177/0361198118776113.
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This study evaluated the effectiveness of connected vehicle (CV) technologies in adverse visibility conditions using microscopic traffic simulation. Traffic flow characteristics deteriorate significantly in reduced visibility conditions resulting in high crash risks. This study applied CV technologies on a segment of Interstate I-4 in Florida to improve traffic safety under fog conditions. Two types of CV approaches (i.e., connected vehicles without platooning (CVWPL) and connected vehicles with platooning (CVPL) were applied to reduce the crash risk in terms of three surrogate measures of safety: the standard deviation of speed, the standard deviation of headway, and rear-end crash risk index (RCRI). This study implemented vehicle-to-vehicle (V2V) communication technologies of CVs to acquire real-time traffic data using the microsimulation software VISSIM. A car-following model for both CV approaches was used with an assumption that the CVs would follow this car-following behavior in fog conditions. The model performances were evaluated under different CV market penetration rates (MPRs). The results showed that both CV approaches improved safety significantly in fog conditions as MPRs increase. To be more specific, the minimum MPR should be 30% to provide significant safety benefits in terms of surrogate measures of safety for both CV approaches over the base scenario (non-CV scenario). In terms of surrogate safety measures, CVPL significantly outperformed CVWPL when MPRs were equal to or higher than 50%. The results also indicated a significant improvement in the traffic operation characteristics in terms of average speed.
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Chowdhury, Mashrur, Mizanur Rahman, Anjan Rayamajhi, Sakib Mahmud Khan, Mhafuzul Islam, Zadid Khan, and James Martin. "Lessons Learned from the Real-World Deployment of a Connected Vehicle Testbed." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 22 (October 6, 2018): 10–23. http://dx.doi.org/10.1177/0361198118799034.
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The connected vehicle (CV) system promises unprecedented safety, mobility, environmental, economic, and social benefits, which can be unlocked using the enormous amount of data shared between vehicles and infrastructure (e.g., traffic signals, centers). Real-world CV deployments, including pilot deployments, help solve technical issues and observe potential benefits, both of which support the broader adoption of the CV system. This study focused on the Clemson University Connected Vehicle Testbed (CU-CVT) with the goal of sharing the lessons learned from the CU-CVT deployment. The motivation of this study was to enhance early CV deployments with the objective of depicting the lessons learned from the CU-CVT testbed, which includes unique features to support multiple CV applications running simultaneously. The lessons learned in the CU-CVT testbed are described at three different levels: (i) the development of system architecture and prototyping in a controlled environment, (ii) the deployment of the CU-CVT testbed, and (iii) the validation of the CV application experiments in the CU-CVT. Field experiments with CV applications validated the functionalities needed for running multiple diverse CV applications simultaneously using heterogeneous wireless networking, and meeting real-time and non-real-time application requirements. The unique deployment experiences, related to heterogeneous wireless networks, real-time data aggregation, data dissemination and processing using a broker system, and data archiving with big data management tools, gained from the CU-CVT testbed, could be used to advance CV research and guide public and private agencies for the deployment of CVs in the real world.
Dissertations / Theses on the topic "Connected vehicle (CV)"
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Iqbal, Md Shahadat. "Data Support of Advanced Traveler Information System Considering Connected Vehicle Technology." FIU Digital Commons, 2017. https://digitalcommons.fiu.edu/etd/3495.
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Traveler information systems play a significant role in most travelers’ daily trips. These systems assist travelers in choosing the best routes to reach their destinations and possibly select suitable departure times and modes for their trips. Connected Vehicle (CV) technologies are now in the pilot program stage. Vehicle-to-Infrastructure (V2I) communications will be an important source of data for traffic agencies. If this data is processed properly, then agencies will be able to better determine traffic conditions, allowing them to take proper countermeasures to remedy transportation system problems under different conditions.
This research focuses on developing methods to assess the potential of utilizing CV data to support the traveler information system data collection process. The results from the assessment can be used to establish a timeline indicating when an agency can stop investing, at least partially, in traditional technologies, and instead rely on CV technologies for traveler information system support. This research utilizes real-world vehicle trajectory data collected under the Next Generation Simulation (NGSIM) program and simulation modeling to emulate the use of connected vehicle data to support the traveler information system. NGSIM datasets collected from an arterial segment and a freeway segment are used in this research. Microscopic simulation modeling is also used to generate required trajectory data, allowing further analysis, which is not possible using NGSIM data.
The first step is to predict the market penetration of connected vehicles in future years. This estimated market penetration is then used for the evaluation of the effectiveness of CV-based data for travel time and volume estimation, which are two important inputs for the traveler information system. The travel times are estimated at different market penetrations of CV. The quality of the estimation is assessed by investigating the accuracy and reliability with different CV deployment scenarios. The quality of volume estimates is also assessed using the same data with different future scenarios of CV deployment and partial or no detector data. Such assessment supports the identification of a timeline indicating when CV data can be used to support the traveler information system.
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Mjogolo, Festo. "Operational effectiveness of connected vehicle smartphone technology on a signalized corridor." UNF Digital Commons, 2019. https://digitalcommons.unf.edu/etd/877.
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Over the last decade, extensive research efforts have been placed on performance evaluation and the benefits of innovative CV applications. Findings indicate that CV technology can effectively mitigate the safety, mobility, and environmental challenges experienced on transportation networks. Most of research evaluated CV technology through simulation studies. However, a field study provides a more ideal method of assessing CV technology effectiveness. Therefore, a field study to obtain the actual effectiveness of CV technology was warranted, to validate previous findings, and to add to the body of knowledge surrounding this topic. This thesis presents both a field study and simulation evaluation of the effectiveness of CV smartphone technology on a 1.1 mile segment of State Road 121, containing five intersections, in Gainesville, Florida. Field observations were conducted using a CV application, developed by Connected Signals, Inc., that uses a smartphone application, called EnLighten, to communicate intersection information to driver’s smartphone, which serves as a vehicle on-board unit.
Traffic operation and safety performance was evaluated using start-up lost time, discharge distribution model, and speed harmonization. Findings show that the CV smartphone technology improved intersection performance with a reduction in start-up lost time of approximately 86%. Additionally, driving safety improved with a reduction in speed variability by nearly 61% between vehicles in a specific lane for a 100% CV penetration rate. Cost analyses of deploying CV smartphone technology indicate that implementation may result in an average total economic cost savings associated with crashes of nearly $6.8 million at the study site, and approximately $5.6 billion statewide.
Findings of the simulation evaluation revealed that the CV technology improved performance of intersections operating at a Level of Service (LOS) B or better, compared to lower operating levels. Operational performance improved at intersections operating at a LOS C with a 30% to 60% CV penetration rate.
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Ahmed, Md Salman. "An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etd/3214.
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A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model.
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Aarflot, Markus, and Pontus Jangstam. "Future Logistical Services from Connected Vehicles : A Case Study at Scania CV AB." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64013.
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The road based transportation operations are growing rapidly, but the current infrastructure cannot sustain the entire growth. At the same time vehicle utilisation and fill rates are low. Improved efficiency of the operations is a necessary way forward for road based transportation. Parallel to this, heavy vehicle producers are currently improving the efficiency with services accompanying the product that are focused on the driver and the vehicle performance. However, the data from connected vehicles required for these services only entail a small amount of the operational data generated by connected vehicles. The case study aims to answer how to use connected vehicle operational data in order to suggest value adding services in a dynamic road distribution system. The applied methodology is an inductive study with an explanatory approach to map the current and future service offerings of the case company. This knowledge is combined with an exploratory approach with interviews of transport planners and theories of Lean and fleet management. Primarily, it is concluded that the perspective of operational data requires widening. Considering not only driver and vehicle operations but rather the entire transport operation of a company. It is also concluded that value creation with operational data is possible during three phases of fleet management. First, if knowledge about order data is accessible, the planning of transportations can be improved using route optimisation and operations research. Secondly, it is possible to create value during the execution phase, throughless manual supervision and communication by transport planners. Lastly, both the currently used operational data and further data usage can contribute to a better understanding of the performance of a fleet operation and facilitate for continuous improvements during an evaluation phase.
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Rahimi, Tariq Rahim. "Potential Impacts of Connected Vehicles in Urban Traffic: A Case Study." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1525457750006016.
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Azmat, Muhammad, Sebastian Kummer, Moura Lara T, Gennaro Federico Di, and Rene Moser. "Future Outlook of Highway Operations with Implementation of Innovative Technologies Like AV, CV, IoT and Big Data." MDPI, 2019. http://dx.doi.org/10.3390/logistics3020015.
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In the last couple of decades, there has been an unparalleled growth in number of people who can afford motorized vehicles. This is increasing the number of vehicles on roads at an alarming rate and existing infrastructure and conventional methods of traffic management are becoming inefficient both on highways and in urban areas. It is very important that our highways are up and running 24/7 as they not only provide a passage for human beings to move from one place to another, but also are the most important mode for intercity or international transfer of goods. There is an utter need of adapting the new world order, where daily processes are driven with the help of innovative technologies. It is highly likely that technological advancements like autonomous or connected vehicles, big data and the Internet of things can provide highway operators with a solution that might resolve unforeseeable challenges. This investigative exploratory research identifies and highlights the impact of new technological advancements in the automotive industry on highways and highway operators. The data for this research was collected on a Likert scale type online survey, from different organizations around the world (actively or passively involved in highway operations). The data was further tested for its empirical significance with non-parametric binomial and Wilcoxon signed rank tests, supported by a descriptive analysis. The results of this study are in line with theoretical and conceptual work done by several independent corporations and academic researchers. It is evident form the opinions of seasoned professionals that these technological advancements withhold the potential to resolve all potential challenges and revolutionize highway operations.
Conference papers on the topic "Connected vehicle (CV)"
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Mohd Zulkefli, Mohd Azrin, and Zongxuan Sun. "Real-Time Powertrain Optimization Strategy for Connected Hybrid Electrical Vehicle." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9727.
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Connected Vehicle (CV) technology, which allows traffic information sharing, and Hybrid Electrical Vehicles (HEV) can be combined to improve vehicle fuel efficiency. However, transient traffic information in CV environment necessitates a fast HEV powertrain optimization for real-time implementation. Model Predictive Control (MPC) with Linearization is proposed, but the computational effort is still prohibitive. The Equivalent Consumption Minimization Strategy (ECMS) and Adaptive-ECMS are proposed to minimize computation time, but unable to guarantee charge-sustaining-operation (CS). Fast analytical result from Pontryagin’s Minimum Principles (PMP) is possible but the input has to be unconstrained. Numerical solutions with Linear Programming (LP) are proposed, but over-simplifications of the cost and constraint functions limit the performance of such methods. In this paper, a nonlinear CS constraint is transformed into linear form with input variable change. With linear input and CS constraints, the problem is solved with Separable Programming by approximating the nonlinear cost with accurate linear piecewise functions which are convex. The piecewise-linear functions introduce new dimensionless variables which are solved as a large-dimension constrained linear problem with efficient LP solvers. Comparable fuel economy with Dynamic Programming (DP) is shown, with maximum fuel savings of 7% and 21.4% over PMP and Rule-Based (RB) optimizations. Simulations with different levels of vehicle speed prediction uncertainties to emulate CV settings are presented.
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Al-Hitmi, Mohammed, Atif Iqbal, Anwarul Hassan, Abdul Shakoor, and Ramazan Kahraman. "Multiple Output Contactless Inductive Power Transfer System for Electric Vehicle Battery Charging Station." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0022.
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The proposed system is designed to charge the three different duty vehicles (based on the charging power): heavy-duty vehicle, medium-duty vehicle and small duty vehicle through three different modules (Module-A, B and C) which are connected to one common DC bus. In the proposed system, each module consists of two inductive coils. One is embedded into EV body along with a rectifier and DC-DC converter as a receiver. However, another coil is embedded into the road (on the ground) along with DC-DC converter and high-frequency inverter as a transmitter. Additionally, each module consists of two matching networks with a compensation circuit for effective power transfer. For the analysis and designing of rapid fast charger for different duty range EV, the typical specification of different duty range EV are used. For fast charging of heavyduty range EV, required charging voltage and current are high (600A/550A) as compared to medium (350V/135A) and low (200V/125A) range EV. To achieve these requirements, different ratings of the converter are utilized in the respective charger. In the proposed system, the dedicated qZS boost converter is utilized to boost the input voltage up to required high voltage demand. However, the receiver buck converter steps down the voltage (step current) to the required level to charge the battery. In the proposed system, by controlling the buck converter the battery is charged either in CC or CV mode. Additionally, the two matching networks together compensate for the capacitive reactance of the coupling plates. The proposed system provides rapid DC charging for different duty range EVs from the AC grid along with a controlled rectifier or DC grid thereby reducing the cost, volume density, and complexity of the charging system.
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Loganathan, Yaamini Devi. "A Case for Connected Vehicles in reducing Total Cost of Ownership in Indian CV Industry." In SAE 2015 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2015. http://dx.doi.org/10.4271/2015-01-0293.
Full textReports on the topic "Connected vehicle (CV)"
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Li, Howell, Tom Platte, Jijo K. Mathew, W. Benjamin Smith, Enrique Saldivar-Carranza, and Darcy M. Bullock. Using Connected Vehicle Data to Reassess Dilemma Zone Performance of Heavy Vehicles. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317321.
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The rate of fatalities at signalized intersections involving heavy vehicles is nearly five times higher than for passenger vehicles in the US. Previous studies in the US have found that heavy vehicles are twice as likely to violate a red light compared with passenger vehicles. Current technologies leverage setback detection to extend green time for a particular phase and are based upon typical deceleration rates for passenger cars. Furthermore, dilemma zone detectors are not effective when the max out time expires and forces the onset of yellow. This study proposes the use of connected vehicle (CV) technology to trigger force gap out (FGO) before a vehicle is expected to arrive within the dilemma zone limit at max out time. The method leverages position data from basic safety messages (BSMs) to map-match virtual waypoints located up to 1,050 ft in advance of the stop bar. For a 55 mph approach, field tests determined that using a 6 ft waypoint radius at 50 ft spacings would be sufficient to match 95% of BSM data within a 5% lag threshold of 0.59 s. The study estimates that FGOs reduce dilemma zone incursions by 34% for one approach and had no impact for the other. For both approaches, the total dilemma zone incursions decreased from 310 to 225. Although virtual waypoints were used for evaluating FGO, the study concludes by recommending that trajectory-based processing logic be incorporated into controllers for more robust support of dilemma zone and other emerging CV applications.