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Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections
作者 Biao Xu,Xuegang Jeff Ban,Yougang Bian,Wan Li,Jianqiang Wang,Shengbo Eben Li
出版年份 2019 引用
摘要
Signalized intersections play an important role in transportation efficiency and vehicle fuel economy in urban areas. This paper proposes a cooperative method of traffic signal control and vehicle sp...展开全文
Signalized intersections play an important role in transportation efficiency and vehicle fuel economy in urban areas. This paper proposes a cooperative method of traffic signal control and vehicle speed optimization for connected automated vehicles, which optimizes the traffic signal timing and vehicles' speed trajectories at the same time. The method consists of two levels, i.e., roadside traffic signal optimization and onboard vehicle speed control. The former calculates the optimal traffic signal timing and vehicles' arrival time to minimize the total travel time of all vehicles; the latter optimizes the engine power and brake force to minimize the fuel consumption of individual vehicles. The enumeration method and the pseudospectral method are applied in roadside and onboard optimization, respectively. Simulation studies are conducted to compare the proposed method with benchmark methods. The results show significant improvement of transportation efficiency and fuel economy by the cooperation method.
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Maneuver Prediction and Planning for Automated and Connected Vehicles based on Interaction and Gaming Awareness under Uncertainty
作者 Manjiang Hu,Guotao Xie,Hongbo Gao,Dongpu Cao,Li Qiang
出版年份 2018 引用
摘要
The complex and mixed traffic environment makes it a challenge for the widespread use of automated and connected vehicles (ACVs). It is necessary for these systems to have a better understandin...展开全文
The complex and mixed traffic environment makes it a challenge for the widespread use of automated and connected vehicles (ACVs). It is necessary for these systems to have a better understanding of the traffic environment including interaction and gaming between multiple vehicles. In this study, a maneuver prediction and planning framework is proposed on the basis of game theories for complex and mixed traffic scenarios via Vehicle-to-Everything (V2X) communication. In this framework, the interaction and gaming between multiple vehicles are considered by employing the extensive form game theories. In the payoff function, the risk assessment model based on trajectory prediction under uncertainty is employed to assess collision risks. Driving efficiency and preference are also combined in the payoff function. Uncertainty elements, including estimation and prediction, are considered to predict and plan by using Nash equilibrium of the extensive form game theory in mixed and behavioral strategies.Finally,this framework is applied and proved in different lane-changes cenarios.There sults show that this framework could predict other vehicles’ driving maneuvers and plan maneuvers for ego vehicles by considering interaction and gaming between multiple vehicles, which helps ACVs understand the environment better and make the cooperative maneuver planning in complex traffic scenarios.
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The Technology of Intelligent Driving Visual Perception Based on Driving Brain
作者 Xinyu Zhang,Hongbo Gao,Guotao Xie,Buyun Gao,Deyi Li
出版年份 2018 引用
摘要

A Driving Behavior Awareness Model based on a Dynamic Bayesian Network and Distributed Genetic Algorithm
作者 Guotao Xie,Hongbo Gao,Bin Huang,Lijun Qian,Jianqiang Wang
出版年份 2018 引用
摘要
It is necessary for automated vehicles (AVs) and advanced driver assistance systems (ADASs) to have a better understanding of the traffic environment including driving behaviors. This study aim...展开全文
It is necessary for automated vehicles (AVs) and advanced driver assistance systems (ADASs) to have a better understanding of the traffic environment including driving behaviors. This study aims to build a driving behavior awareness (DBA) model that can infer driving behaviors such as lane change. In this study, a dynamic Bayesian network DBA model is proposed, which includes three layers, namely, the observation, hidden and behavior layer. To enhance the performance of the DBA model, the network structure is optimized by employing a distributed genetic algorithm (GA). Using naturalistic driving data in Beijing, the comparison between the optimized model and other non-optimized models such as the hidden Markov model (HMM) and HMM with a mixture of Gaussian outputs (GM-HMM) indicates that the optimized model could estimate driving behaviors earlier and more accurately.
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Vehicle Trajectory Prediction by Integrating Physics- and Maneuver-Based Approaches Using Interactive Multiple Models
作者 Guotao Xie, Hongbo Gao,Lijun Qian,Bin Huang,Keqiang Li,Jianqiang Wang
出版年份 2018 引用
摘要
Vehicle trajectory prediction helps automated vehicles and advanced driver-assistance systems have a better understanding of traffic environment and perform tasks such as criticality assessment in a...展开全文
Vehicle trajectory prediction helps automated vehicles and advanced driver-assistance systems have a better understanding of traffic environment and perform tasks such as criticality assessment in advance. In this study, an integrated vehicle trajectory prediction method is proposed by combining physics- and maneuver-based approaches. These two methods were combined for the reason that the physics-based trajectory prediction method could ensure accuracy in the short term with the consideration of vehicle running dynamic parameters, and the maneuver-based prediction approach has a long-term insight into future trajectories with maneuver estimation. In this study, the interactive multiple model trajectory prediction (IMMTP) method is proposed by combining the two predicting models. The probability of each model in the interactive multiple models could recursively adjust according to the predicting variance of each model. In addition, prediction uncertainty is considered by employing unscented Kalman filters in the physics-based prediction model. To the maneuver-based method, random elements for uncertainty are introduced to the trajectory of each maneuver inferred by using the dynamic Bayesian network. The approach is applied and analyzed in the lane-changing scenario by using naturalistic driving data. Comparison results indicate that IMMTP could achieve a more accurate prediction trajectory with a long prediction horizon.
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A Novel Three-Planetary-Gear Power-Split Hybrid Powertrain for Tracked Vehicles
作者 Zhaobo Qin,Yugong Luo,Zhong Cao,Keqiang Li
出版年份 2018 引用
摘要
Tracked vehicles are widely used for agriculture, construction and many other areas. Due to high emissions, hybrid electric driveline has been applied to tracked vehicles. The hybrid powertrain des...展开全文
Tracked vehicles are widely used for agriculture, construction and many other areas. Due to high emissions, hybrid electric driveline has been applied to tracked vehicles. The hybrid powertrain design for the tracked vehicle has been researched for years. Different from wheeled vehicles, the tracked vehicle not only requires high mobility while straight driving, but also pursues strong steering performance. The paper takes the hybrid track-type dozers (TTDs) as an example and proposes an optimal design of a novel power-split powertrain for TTDs. The commercial hybrid TTD usually adopts the series hybrid powertrain, and sometimes with an extra steering mechanism, which has led to low efficiency and made the structure more complicated. The proposed three-planetary-gear power-split hybrid powertrain can overcome the problems above by utilizing the characteristics of planetary gear sets. The proposed powertrain has two outputs connected to the left and right track respectively, which can provide the accurate torque to both sides of tracks when straight driving, skid steering, or driving backwards. The paper gives the dynamic characteristic matrices to search the big pool of designs with three planetary gear sets more simple. An analytically-based method is used to classify the feasible modes into three groups which have superior dynamic features respectively. Dual-mode designs with two clutches are presented using mode-combination method. A near-optimal control rapid strategy, power-weighted efficiency analysis for rapid sizing (PEARS+), is used as the control strategy. The control results show that the novel design has better drivability and fuel economy than the series hybrid benchmark. The proposed new kind of powertrain has shown good potential which can be considered for future industrial application.
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Simultaneous optimization of topology, control and size for multi-mode hybrid tracked vehicles
作者 Zhaobo Qin,Yugong Luo,Weichao Zhuang,Ziheng Pan,Keqiang Li,Huei Peng
出版年份 2018 引用
摘要
Hybrid tracked vehicles have become increasingly popular for off-road applications due to their better fuel economy and higher output power. Currently, the most popular in the production of tracked ...展开全文
Hybrid tracked vehicles have become increasingly popular for off-road applications due to their better fuel economy and higher output power. Currently, the most popular in the production of tracked vehicles are the series hybrid,because of the simple powertrain designs. However,they suffer from high energy conversion losses and large propulsion motors. To overcome these issues, multi-mode hybrid tracked vehicles are employed since they have high efficiency and excellent overall performance. The proposed multi-mode hybrid powertrain can realize straight driving, turning, and driving backwards without any additional steering mechanism. To systematically explore all the possible designs of multi-mode hybrid designs with planetary gears, a topology -control-size-integrated optimization approach is presented. A novel near-optimal energy management strategy, Efficiency Evaluation Real-time Control Strategy (EERCS), is proposed to rapidly calculate near-optimal control rules for design candidates. The EERCS is confirmed to achieve results similar to those of Dynamic Programming (DP),yet the computation time is over 50 times less.With the help of EERCS,the optimal design together with its parameters is computed using multi-objective optimization based on a meta-heuristic algorithm. Results of a case study show that the optimized design with downsized components produces improved drivability and fuel economy compared to the series hybrid benchmark.
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Optimal Design of Single-Mode Power-Split Hybrid Tracked Vehicles
作者 Zhaobo Qin,Yugong Luo,Keqiang Li,Huei Peng
出版年份 2018 引用
摘要
Hybrid tracked vehicles are common in construction, agriculture, and military applications. Most use a series hybrid powertrain with large motors and operate at a relatively low efficiency. Alth...展开全文
Hybrid tracked vehicles are common in construction, agriculture, and military applications. Most use a series hybrid powertrain with large motors and operate at a relatively low efficiency. Although some researchers have proposed power-split powertrains, most of these would require an additional mechanism to achieve skid steering. To solve this problem and enhance drivability, a single-mode power-split hybrid powertrain for tracked vehicles with two outputs connected to the left and right tracks is proposed. The powertrain with three planetary gears (PGs) would then be able to control the torque on the two tracks independently and achieve skid steering. This powertrain has three degrees-of-freedom (DOF), allowing for control of the output torques and the engine speed independently from the vehicle running speed. All design candidates with three PGs are exhaustively searched by analyzing the dynamic characteristics and control to obtain the optimal design. Efficient topology design selection with parameter sizing and component sizing is accomplished using the enhanced progressive iteration approach to achieve better fuel economy using downsized components.
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