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Статті в журналах з теми "Multi-Lane trajectory"

Автор: Grafiati

Опубліковано: 23 вересня 2022

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1

Luo, Yugong, Gang Yang, Mingchang Xu, Zhaobo Qin, and Keqiang Li. "Cooperative Lane-Change Maneuver for Multiple Automated Vehicles on a Highway." Automotive Innovation 2, no. 3 (2019): 157–68. http://dx.doi.org/10.1007/s42154-019-00073-1.

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Abstract With the development of vehicle-to-vehicle (V2V) communication, it is possible to share information among multiple vehicles. However, the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information. Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency. Therefore, a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed. In these scenarios, same-direction an

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2

Hou, Quanshan, Yanan Zhang, Shuai Zhao, Yunhao Hu, and Yongwang Shen. "Tracking Control of Intelligent Vehicle Lane Change Based on RLMPC." E3S Web of Conferences 233 (2021): 04019. http://dx.doi.org/10.1051/e3sconf/202123304019.

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Autonomous lane changing, as a key module to realize high-level automatic driving, has important practical significance for improving the driving safety, comfort and commuting efficiency of vehicles. Traditional controllers have disadvantages such as weak scene adaptability and difficulty in balancing multi-objective optimization. In this paper, combined with the excellent self-learning ability of reinforcement learning, an interactive model predictive control algorithm is designed to realize the tracking control of the lane change trajectory. At the same time, two typical scenarios are verifi

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3

Tian, Wei, Songtao Wang, Zehan Wang, Mingzhi Wu, Sihong Zhou, and Xin Bi. "Multi-Modal Vehicle Trajectory Prediction by Collaborative Learning of Lane Orientation, Vehicle Interaction, and Intention." Sensors 22, no. 11 (2022): 4295. http://dx.doi.org/10.3390/s22114295.

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Accurate trajectory prediction is an essential task in automated driving, which is achieved by sensing and analyzing the behavior of surrounding vehicles. Although plenty of research works have been invested in this field, it is still a challenging subject due to the environment’s complexity and the driving intention uncertainty. In this paper, we propose a joint learning architecture to incorporate the lane orientation, vehicle interaction, and driving intention in vehicle trajectory forecasting. This work employs a coordinate transform to encode the vehicle trajectory with lane orientation i

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4

Yao, Handong, and Xiaopeng Li. "Lane-change-aware connected automated vehicle trajectory optimization at a signalized intersection with multi-lane roads." Transportation Research Part C: Emerging Technologies 129 (August 2021): 103182. http://dx.doi.org/10.1016/j.trc.2021.103182.

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5

Yong, Huang, Fang Daqing, Tan Fuliang, Tao Minglu, Si Daoguang, and Shu Yang. "Research on Vehicle Lane Changing Characteristics of Multi-lane Type Highway Maintenance Operation Area Based on Vehicle Trajectory." IOP Conference Series: Materials Science and Engineering 792 (June 3, 2020): 012011. http://dx.doi.org/10.1088/1757-899x/792/1/012011.

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6

Liang, Yang, Zhishuai Yin, and Linzhen Nie. "Shared Steering Control for Lane Keeping and Obstacle Avoidance Based on Multi-Objective MPC." Sensors 21, no. 14 (2021): 4671. http://dx.doi.org/10.3390/s21144671.

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This paper presents a shared steering control framework for lane keeping and obstacle avoidance based on multi-objective model predictive control. One of the control objectives is to track the reference trajectory, which is updated continuously by the trajectory planning module; whereas the other is to track the driver’s current steering command, so as to consider the driver’s intention. By adding the two control objectives to the cost function of an MPC shared controller, a smooth combination of the commands of the driver and the automation can be achieved through the optimization. The author

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7

Xia, Yulan, Yaqin Qin, Xiaobing Li, and Jiming Xie. "Risk Identification and Conflict Prediction from Videos Based on TTC-ML of a Multi-Lane Weaving Area." Sustainability 14, no. 8 (2022): 4620. http://dx.doi.org/10.3390/su14084620.

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Crash risk identification and prediction are expected to play an important role in traffic accident prevention. However, most of the existing studies focus only on highways, not on multi-lane weaving areas. In this paper, a potential collision risk identification and conflict prediction model based on extending Time-to-Collision-Machine Learning (TTC-ML) for multi-lane weaving zone was proposed. The model can accurately learn various features, such as vehicle operation characteristics, risk and conflict distributions, and physical zoning characteristics in the weaving area. Specifically, TTC w

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8

Zong, Fang, Zhengbing He, Meng Zeng, and Yixuan Liu. "Dynamic lane changing trajectory planning for CAV: A multi-agent model with path preplanning." Transportmetrica B: Transport Dynamics 10, no. 1 (2021): 266–92. http://dx.doi.org/10.1080/21680566.2021.1989079.

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9

Gaddam, Hari Krishna, and K. Ramachandra Rao. "Modelling vehicular behaviour using trajectory data under non-lane based heterogeneous traffic conditions." Archives of Transport 52, no. 4 (2019): 95–108. http://dx.doi.org/10.5604/01.3001.0014.0211.

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The present study aims to understand the interaction between different vehicle classes using various vehicle attributes and thereby obtain useful parameters for modelling traffic flow under non-lane based heterogeneous traffic conditions. To achieve this, a separate coordinate system has been developed to extract relevant data from vehicle trajectories. Statistical analysis results show that bi-modal and multi-modal distributions are accurate in representing vehicle lateral placement behaviour. These distributions help in improving the accuracy of microscopic simulation models in predicting ve

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10

Gharibi, Mirmojtaba, Zahra Gharibi, Raouf Boutaba, and Steven L. Waslander. "A Density-Based and Lane-Free Microscopic Traffic Flow Model Applied to Unmanned Aerial Vehicles." Drones 5, no. 4 (2021): 116. http://dx.doi.org/10.3390/drones5040116.

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In this work, we introduce a microscopic traffic flow model called Scalar Capacity Model (SCM) which can be used to study the formation of traffic on an airway link for autonomous Unmanned Aerial Vehicles (UAVs) as well as for the ground vehicles on the road. Given the 3D trajectory of UAV flights (as opposed to the 2D trajectory of ground vehicles), the main novelty in our model is to eliminate the commonly used notion of lanes and replace it with a notion of density and capacity of flow, but in such a way that individual vehicle motions can still be modeled. We name this a Density/Capacity V

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11

Peng, Tao, Xingliang Liu, Rui Fang, et al. "Lane-change path planning and control method for self-driving articulated trucks." Journal of Intelligent and Connected Vehicles 3, no. 2 (2020): 49–66. http://dx.doi.org/10.1108/jicv-10-2019-0013.

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Purpose This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety. Design/methodology/approach The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the autho

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12

Mohamed Ahmed, M. M., and Aziz Naamane. "Multi-lane trajectory control for autonomous vehicle convoy based on a longitudinal and lateral control coupled approach." International Journal of Simulation and Process Modelling 17, no. 2/3 (2021): 214. http://dx.doi.org/10.1504/ijspm.2021.10045924.

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13

Ahmed, M. M. Mohamed, and Aziz Naamane. "Multi-lane trajectory control for autonomous vehicle convoy based on a longitudinal and lateral control coupled approach." International Journal of Simulation and Process Modelling 17, no. 2/3 (2021): 214. http://dx.doi.org/10.1504/ijspm.2021.121720.

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14

Jiang, Haobin, Jie Zhou, Aoxue Li, Xinchen Zhou, and Shidian Ma. "Human-like trapezoidal steering angle model on two-lane urban curves." International Journal of Advanced Robotic Systems 16, no. 4 (2019): 172988141986761. http://dx.doi.org/10.1177/1729881419867614.

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With the rapid development of automated vehicles, there is currently a significant amount of automated driving research. Giving automated vehicles capabilities similar to those of experienced drivers will allow them to share the road harmoniously with manned vehicles, especially on two-lane urban curves. To represent the steering behavior of experienced drivers, a series of curve feature distances are proposed, which is determined by multi-regression. These series of curve feature distances are used to generate a trapezoidal steering angle model which imitates the steering behavior of the expe

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15

Li, Hexuan, Kanuric Tarik, Sadegh Arefnezhad, et al. "Phenomenological Modelling of Camera Performance for Road Marking Detection." Energies 15, no. 1 (2021): 194. http://dx.doi.org/10.3390/en15010194.

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With the development of autonomous driving technology, the requirements for machine perception have increased significantly. In particular, camera-based lane detection plays an essential role in autonomous vehicle trajectory planning. However, lane detection is subject to high complexity, and it is sensitive to illumination variation, appearance, and age of lane marking. In addition, the sheer infinite number of test cases for highly automated vehicles requires an increasing portion of test and validation to be performed in simulation and X-in-the-loop testing. To model the complexity of camer

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16

Liang, Xiao (Joyce), S. Ilgin Guler, and Vikash V. Gayah. "Signal Timing Optimization with Connected Vehicle Technology: Platooning to Improve Computational Efficiency." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 18 (2018): 81–92. http://dx.doi.org/10.1177/0361198118786842.

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This paper develops a real-time traffic signal optimization algorithm in the presence of connected and autonomous vehicles (CAVs). The proposed algorithm leverages information from connected vehicles (CVs) arriving at an intersection to identify naturally occurring platoons that consist of both CVs and non-CVs. Signal timings are then selected to optimize the sequence at which these platoons are allowed to discharge through the intersection to minimize total vehicle delay. Longitudinal trajectory guidance that explicitly accounts for vehicle acceleration and deceleration behavior is provided t

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17

Makantasis, Konstantinos, and Markos Papageorgiou. "Motorway Path Planning for Automated Road Vehicles Based on Optimal Control Methods." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 19 (2018): 112–23. http://dx.doi.org/10.1177/0361198118780710.

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A path-planning algorithm for automated road vehicles on multi-lane motorways is derived from the opportune formulation of an optimal control problem. In this framework, the objective function to be minimized contains appropriate respective terms to reflect: the goals of the vehicle advancement; passenger comfort; prevailing traffic rules (e.g., overtaking only from left); and the avoidance of obstacles (other moving vehicles) and of the vehicle departing from the road. Each term is coupled with a weighting factor that reflects its comparative importance. For the numerical solution of the opti

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18

Lu, Wenjie, Sergio A. Rodríguez F., Emmanuel Seignez, and Roger Reynaud. "Lane Marking-Based Vehicle Localization Using Low-Cost GPS and Open Source Map." Unmanned Systems 03, no. 04 (2015): 239–51. http://dx.doi.org/10.1142/s2301385015400014.

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Autonomous Vehicle applications and Advanced Driving Assistance Systems (ADAS) need scene understanding processes, allowing high-level systems to carry out decision. For such systems, the localization of a vehicle evolving in a structured dynamic environment constitutes a complex problem of crucial importance. However, the low accuracy of the global positioning system (GPS) system in urban environments makes its localization unreliable for further treatments. The combination of GPS data and additional sensors (WSS, IMU or Camera) can improve the localization precision. More and more, digital m

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19

van Erp, Paul B. C., Victor L. Knoop, Erik-Sander Smits, Chris Tampère, and Serge P. Hoogendoorn. "Estimation of the Change in Cumulative Flow over Probe Trajectories using Detector Data." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (2020): 649–61. http://dx.doi.org/10.1177/0361198120948057.

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Detector data can be used to construct cumulative flow curves, which in turn can be used to estimate the traffic state. However, this approach is subject to the cumulative error problem. Multiple studies propose to mitigate the cumulative error problem using probe trajectory data. These studies often assume “no overtaking” and thus that the cumulative flow is zero over probe trajectories. However, in multi-lane traffic this assumption is often violated. Therefore, we present an approach to estimate the change in cumulative flow along probe trajectories between detectors based on disaggregated

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20

Gu, Shangding, Guang Chen, Lijun Zhang, Jing Hou, Yingbai Hu, and Alois Knoll. "Constrained Reinforcement Learning for Vehicle Motion Planning with Topological Reachability Analysis." Robotics 11, no. 4 (2022): 81. http://dx.doi.org/10.3390/robotics11040081.

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Rule-based traditional motion planning methods usually perform well with prior knowledge of the macro-scale environments but encounter challenges in unknown and uncertain environments. Deep reinforcement learning (DRL) is a solution that can effectively deal with micro-scale unknown and uncertain environments. Nevertheless, DRL is unstable and lacks interpretability. Therefore, it raises a new challenge: how to combine the effectiveness and overcome the drawbacks of the two methods while guaranteeing stability in uncertain environments. In this study, a multi-constraint and multi-scale motion

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21

Humoody, Mohammad Ahmad, and Nada Abdullah Younis. "Congestion Identification for Multilane Highway by Vehicle Lane Change as Driver Behavior." Tikrit Journal of Engineering Sciences 29, no. 1 (2022): 46–58. http://dx.doi.org/10.25130/tjes.29.1.5.

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    This work introduces a new way to assess the condition of highways and classify them as congested or uncongested highways. This was done by recording a video and sorting the number of lane change orders instead of finding the traffic density, delay, and flow rate. Then extracting data from the video and performing a microscopic simulation for it to study the driver's behavior and create the statistical model. Thus, obtaining the mathematical relationships and coefficients that illustrate that process, after verifying the reliability and calibration of these variable

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22

Wang, Qinzheng, Xianfeng (Terry) Yang, Zhitong Huang, and Yun Yuan. "Multi-Vehicle Trajectory Design During Cooperative Adaptive Cruise Control Platoon Formation." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (2020): 30–41. http://dx.doi.org/10.1177/0361198120913290.

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Cooperative adaptive cruise control (CACC) organizes connected and automated vehicles (CAVs) in platoons to improve traffic flow and reduce fuel consumption. Platoon formation involves a very complex process, however, because lateral and longitudinal misbehavior of CAVs results in greater fuel consumption and risk of collision. This study aims to design optimal vehicle trajectories of CAVs during CACC platoon formation. First, a basic scenario and a destination-based protocol are described to determine vehicle sequence in the platoon. A space-time lattice based model is then formulated to cons

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23

Rahman, Md Mijanoor, Mohd Tahir Ismail, Norhashidah Awang, and Majid Khan Majahar Ali. "A New Parametric Function-Based Dynamic Lane Changing Trajectory Planning and Simulation Model." Pertanika Journal of Science and Technology 29, no. 1 (2021). http://dx.doi.org/10.47836/pjst.29.1.12.

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Lane-changing (LC) problem may cause serious accidents or create a painful traffic jam at multi-lane roads. Existing LC simulation model was created with some limitations (less fitted, without velocity and acceleration profiles, high curvature) by using well known trajectory curve such as Hyperbolic Tangent Curve (HTC), Sine-Based Curve (SC), Polynomial Curve (PC). In this study, a new parametric curve had been proposed by using curvilinear coordinate system and fitted against Next Generation Simulation (NGSIM) real dataset. Further, new profiles of velocity and acceleration were designed usin

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24

Karimi, Shahab, and Ardalan Vahidi. "Monte Carlo Tree Search and Cognitive Hierarchy Theory for Interactive-Behavior Prediction in Fast Trajectory Planning and Automated Lane Change." Journal of Autonomous Vehicles and Systems 1, no. 1 (2021). http://dx.doi.org/10.1115/1.4050042.

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AbstractPredicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communications and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. The main goal of this paper is to develop a fast algorithm that predicts the future states of the neighboring vehicles. The proposed workflow employs Monte Carlo Tree Search (MCT

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25

Fang, Peijun, Yingfeng Cai, Long Chen, et al. "A high-performance neural network vehicle dynamics model for trajectory tracking control." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, May 2, 2022, 095440702210956. http://dx.doi.org/10.1177/09544070221095660.

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Traditional models of vehicle dynamics engineered from physical principles are usually simplified and assumed, resulting in the model cannot accurately reflect the actual dynamic characteristics of the vehicle under some working conditions, affecting the control accuracy and even safety. In view of this, inspired by the single-track model, this paper uses the data-driven methods to establish a new high-performance time-delay feedback neural network vehicle dynamics model. The feedback connection of a network can describe complex dynamics. The multi-time-step input of the state and control can

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26

Deng, Zhao-wen, Yong-hui Jin, Wei Gao, and Bao-hua Wang. "A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, September 15, 2022, 095440702211218. http://dx.doi.org/10.1177/09544070221121859.

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To improve the directional performance of articulated heavy vehicles (AHV), three previewed points driver model and LQR active trailer steering (ATS) strategy are proposed and examined using closed-loop driver/vehicle dynamics simulation. Firstly, a simplified linear three-degree-of-freedom (3-DOF) yaw plane model for AHV is established and validated. Secondly, based on the multi-point preview-predictor following strategy, the weighted-average error of three previewed points of the tractor is defined as the final lateral previewed displacement error. According to the assumption of constant yaw

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27

Zhang, Yuexia, and Ying Zhou. "An adaptive message return strategy for same direction multilane in vehicular networks." Wireless Networks, April 8, 2022. http://dx.doi.org/10.1007/s11276-022-02957-3.

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AbstractDue to the roadside unit can not fully achieve seamless coverage and the dynamic change of network topology in vehicular networks, problems such as the interruption of vehicle service, poor stability of communication link, and high network delay will be caused. To solve these problems, this paper proposes a codirectional multilane adaptive message return (CMAMR) strategy based on edge computing. Firstly, we establish a CMAMR communication model. Then, according to the movement trajectory of the receiving node, we propose a single-hop and a multi-hop message return link strategy. The fo

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28

Novitz, Julian. "“Too Broad and Deep for the Small Screen”: Doctor Who's New Adventures in the 1990s." M/C Journal 21, no. 5 (2018). http://dx.doi.org/10.5204/mcj.1474.

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Introduction: Doctor Who's “Wilderness Years”1989 saw the cancellation of the BBC's long-running science fiction television series Doctor Who (1965 -). The 1990s were largely bereft of original Doctor Who television content, leading fans to characterise that decade as the “wilderness years” for the franchise (McNaughton 194). From another perspective, though, the 1990s was an unprecedented time of production for Doctor Who media. From 1991 to 1997, Virgin Publishing was licensed by the BBC's merchandising division to publish a series of original Doctor Who novels, which they produced and marke

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29

Raj, Senthorun. "Impacting on Intimacy: Negotiating the Marriage Equality Debate." M/C Journal 14, no. 6 (2011). http://dx.doi.org/10.5204/mcj.350.

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Introduction How do we measure intimacy? What are its impacts on our social, political and personal lives? Can we claim a politics to our intimate lives that escapes the normative confines of archaic institutions, while making social justice claims for relationship recognition? Negotiating some of these disparate questions requires us to think more broadly in contemporary public debates on equality and relationship recognition. Specifically, by outlining the impacts of the popular "gay marriage" debate, this paper examines the impacts of queer theory in association with public policy and commu

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