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2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)最新文献

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Intelligence Assessment of Automated Driving Systems Based on Driving Intelligence Quotient * 基于驾驶智商的自动驾驶系统智能评估*
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661123
Yulei Wang, Meng Li, Yanjun Huang, Hong Chen
{"title":"Intelligence Assessment of Automated Driving Systems Based on Driving Intelligence Quotient *","authors":"Yulei Wang, Meng Li, Yanjun Huang, Hong Chen","doi":"10.1109/CVCI54083.2021.9661123","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661123","url":null,"abstract":"When design, test and validate an intelligent agent, assessing its intelligence is essential. While autonomous vehicles (AVs) are deployed to a certain degree, it is still hard to assess their intelligence because it highly depends on tested scenarios but in real world tested scenarios are limited and far away from edges. Therefore, this paper attempts to propose an intelligence assessment approach for automated driving systems (ADS) based on behavior index (BI) and scenario complexity (SC). The main contributions of the scheme consist of three aspects: 1) proposing an intelligence assessment framework by following the idea of Turing test, 2) presenting a scenario bank for scenario complexity (SC) and behavior metrics for behavior index (BI), and 3) constructing a definition of driving intelligence quotient (DIQ) by the product of SC and BI. Finally, we present a lane-change scenario bank in Monte Carlo simulations to demonstrate the proposed assessment approach.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131801504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Kernel Point Non-local Networks for LiDAR Semantic Segmentation 激光雷达语义分割的核点非局部网络
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661234
Yan Xu, Li Liu, Yu Meng, Chaoda Zheng, Wen Yang, Chen Sun, Rui Zhou, Dongpu Cao
{"title":"Kernel Point Non-local Networks for LiDAR Semantic Segmentation","authors":"Yan Xu, Li Liu, Yu Meng, Chaoda Zheng, Wen Yang, Chen Sun, Rui Zhou, Dongpu Cao","doi":"10.1109/CVCI54083.2021.9661234","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661234","url":null,"abstract":"LiDAR point cloud semantic segmentation based on convolutional neural networks has become an effective way to understand traffic scenes. Previous works mainly focus on projecting point clouds onto a plane and then use efficient 2D CNN to achieve efficient feature extraction. However, the projection process is accompanied by 3D information loss, challenging to adapt to the complex traffic environment. In this paper, we propose a point-based segmentation network based on three-dimensional convolution, which directly takes the point cloud as input, integrates a variety of distributed kernel point convolutions and introduces an attention mechanism to learn 3d point features efficiently. To evaluate our algorithm, we conducted sufficient experiments on the widely used public dataset SemanticKITTI [1]. The results show that our proposed Kernel Point Non-local module improving the accuracy of KPConv [2] from 58.8% to 61.5%, leading to new state-of-the-art among point-based methods.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133190752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
AGV Research Based on Inertial Navigation and Vision Fusion 基于惯性导航与视觉融合的AGV研究
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661175
Gaojian Cui, Yang Bai, Shaosong Li
{"title":"AGV Research Based on Inertial Navigation and Vision Fusion","authors":"Gaojian Cui, Yang Bai, Shaosong Li","doi":"10.1109/CVCI54083.2021.9661175","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661175","url":null,"abstract":"To improve the guidance flexibility and navigation accuracy of an AGV, an improved inertial guidance system is designed. The system is based on the single chip microcomputer and the motion model of the AGV. A DM code correction module is introduced to eliminate the accumulated error of the inertial navigation system. Then, a controller is designed on the basis of the fuzzy PID controller and the optimal deviation path controller. The lateral deviation and course angle deviation of the AGV are taken as the input values to obtain the control values of the left and right wheels’ speed. The speed of the two current AGV wheels is adjusted to realize deviation correction. The experimental results show that the system can smoothly and quickly eliminate the lateral and course deviations, and the guidance accuracy is nearly 15% higher than that of the traditional rail guidance system. This outcome verifies that the system can better meet the stability and effectiveness of operation.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131360571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Artificial Steering Feel for Teleoperated Road Vehicle with Disturbance Observer 带干扰观测器的遥控道路车辆人工转向感觉
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661125
Chengrui Su, Huanghe Li, Xiaodong Wu
{"title":"Artificial Steering Feel for Teleoperated Road Vehicle with Disturbance Observer","authors":"Chengrui Su, Huanghe Li, Xiaodong Wu","doi":"10.1109/CVCI54083.2021.9661125","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661125","url":null,"abstract":"Teleoperated driving is regarded as an alternative technology to fully autonomous driving. Drivers in teleoperated driving need haptic feedback to control the remote vehicle. To provide driver steering feel, this paper proposes an artificial steering feel model for teleoperated driving. During the dynamics modeling, the structure of teleoperated steering system (TSS) is separated as a local steering module and a remote steering actuation module. The handwheel torque generating steering feel in the local steering module consists of two parts: aligning torque and equivalent friction torque. Aligning torque is obtained by estimating rack force utilizing an extended disturbance observer. To achieve the customizable steering feel, a mathematical model with weighting function is introduced. Objective evaluation method is adopted to evaluate the performance of the designed steering feel and decide the variable parameter values of the model. Hardware-in-the-loop experiments are conducted on a self-designed driving simulator. By comparing with the conventional steering system, the experiment results indicate that the proposed model can be tuned to have the desired steering feel for teleoperated road vehicles.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129246467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Energy management strategy of extended-range hybrid electric vehicle considering time-domain features of optimization targets 考虑优化目标时域特征的增程混合动力汽车能量管理策略
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661131
Xu Wang, Ying Huang, Yongliang Li
{"title":"Energy management strategy of extended-range hybrid electric vehicle considering time-domain features of optimization targets","authors":"Xu Wang, Ying Huang, Yongliang Li","doi":"10.1109/CVCI54083.2021.9661131","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661131","url":null,"abstract":"An adaptive equivalent fuel consumption minimization strategy (A-ECMS) considering time domain characteristics of the optimization targets is proposed in this paper. Vehicle speed prediction in short time domain is used to adjust the penalty coefficient related to transient conditions, so as to reduce the adverse effects of frequent engine transients. The stored long-time domain historical vehicle speed data is used to adjust the penalty coefficient related to SOC trajectory, so that the SOC can be maintained while ensuring better fuel economy. Comparing the ECMS with the A-ECMS proposed in this paper, the simulation results show that setting up the penalty coefficients of different targets in different time domains can improve the fuel economy and effectively reduce the number of engine starts and stops, thus achieving the purpose of reducing pollutant emissions.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122214168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Lidar-based Simultaneous Localization and Mapping in Dynamic Environments 动态环境下基于激光雷达的同步定位与制图
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661215
Binbin Feng, Chunyun Fu, L. Liao, Yun Zhu
{"title":"Lidar-based Simultaneous Localization and Mapping in Dynamic Environments","authors":"Binbin Feng, Chunyun Fu, L. Liao, Yun Zhu","doi":"10.1109/CVCI54083.2021.9661215","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661215","url":null,"abstract":"In this paper, we propose a method of simultaneous localization and mapping (SLAM) based on Lidar, which can improve the accuracy of vehicle pose estimation in a dynamic environment. This method is composed of three modules. The first module is a Lidar odometry with static weight, namely Static Weight Normal Distribution Transform (SW-NDT). Static weight describes the probability that a point cloud belongs to a static object. To reduce the adverse effects of point clouds generated by dynamic objects on pose estimation, static weights are added to Normal Distribution Transform (NDT). The second module is back-end optimization. Scan Context is applied to detect whether a closed loop is formed between the current and historical frames. If a closed loop is detected, pose graph optimization is performed to optimize the poses of all key frames in the closed loop. The third module joins point clouds of the key frames to form a global map according to the optimized poses. For validation of the method proposed in this paper, KITTI dataset is utilized. The results show that the method proposed herein outperforms the other three methods in positioning accuracy.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115643819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Feedforward and Feedback Integrated Control for Handling Characteristics Adjustment of Multi-axle Heavy-duty Vehicles Using Independent-drive Electric Wheels 独立驱动电动轮多轴重型车辆操纵特性调整前馈反馈集成控制
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661250
Jiayi Hu, Jianqiu Li, Hang Li, Jiachen Dong, Zunyan Hu, Liangfei Xu, M. Ouyang
{"title":"Feedforward and Feedback Integrated Control for Handling Characteristics Adjustment of Multi-axle Heavy-duty Vehicles Using Independent-drive Electric Wheels","authors":"Jiayi Hu, Jianqiu Li, Hang Li, Jiachen Dong, Zunyan Hu, Liangfei Xu, M. Ouyang","doi":"10.1109/CVCI54083.2021.9661250","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661250","url":null,"abstract":"Electric vehicles with independent-drive electric wheels provide flexibility in vehicle dynamics control. In this paper, a controller is designed for an independent-drive multi-axle heavy-duty vehicle, aiming at adjusting its handling characteristics by external yaw moment. A hierarchical control structure is adopted, including a feedforward and feedback integrated high-level control block, middle-level control allocation, and low-level traction control system. The stability factor of a multi-axle vehicle is studied, and a feedforward part is designed based on the bicycle model analysis. The sliding mode control is used in the feedback part of the high-level control. Simulation results show that the heavy-duty vehicle’s yaw rate response can be adjusted in a wide range.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123408011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Direct 2.5D LiDAR SLAM in Outdoor Dynamic Environment for Autonomous Driving* 直接2.5D激光雷达SLAM在室外动态环境中的自动驾驶*
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661117
Xuebo Tian, Jun Li, Junqiao Zhao, Chen Ye
{"title":"Direct 2.5D LiDAR SLAM in Outdoor Dynamic Environment for Autonomous Driving*","authors":"Xuebo Tian, Jun Li, Junqiao Zhao, Chen Ye","doi":"10.1109/CVCI54083.2021.9661117","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661117","url":null,"abstract":"Robust localization and mapping in outdoor road scenes is challenging for autonomous driving because moving objects can have a huge impact on the accuracy and robustness of existing simultaneous localization and mapping (SLAM) methods. In this paper, a 2.5D LiDAR SLAM method based on direct method for dynamic scenes is proposed. This method can recognize and track dynamic objects and gradually integrate static potential dynamic object into SLAM optimization. This method first maps the 3D scan of the surrounding environment to a 2.5D height map. Object detection is then conducted to remove all the points that belong to potential dynamic objects (PDOs). High performance LiDAR odometry and loop detection are then implemented using direct height map matching and 2.5D descriptor-based matching, respectively. At the same time, through data association and tracking, the gradual separation of dynamic and static PDOs is achieved. Points that belong to the static PDOs are then gradually integrated into the SLAM system. Therefore, using as much static scene information as possible for SLAM can significantly improve the robustness and accuracy of SLAM. In addition, the resulting ego-poses are further used to accurately track PDOs, thereby improving their trajectory and speed estimation. Experiments on public dataset and our campus datasets shown that our method achieves better accuracy than SUMA++.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128525872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An intelligent pedestrian-vehicle collision avoidance strategy based on evolutionary game 基于进化博弈的智能人车避碰策略
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661124
Ziwei Wang, Guo-dong Yin, Shangjie Li, Min Qian, Pai Peng, Keke Geng
{"title":"An intelligent pedestrian-vehicle collision avoidance strategy based on evolutionary game","authors":"Ziwei Wang, Guo-dong Yin, Shangjie Li, Min Qian, Pai Peng, Keke Geng","doi":"10.1109/CVCI54083.2021.9661124","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661124","url":null,"abstract":"It is very important for intelligent vehicles to make reasonable collision avoidance strategy when facing crossing pedestrians. In this paper, an evolutionary dynamics model of the conflict between pedestrians and intelligent vehicles is proposed for the scenario that intelligent vehicles perceive pedestrian crossing street and predict that a collision may occur. Considering factors such as vehicle type and the radical degree of pedestrian behavior, values are assigned to the parameters of the game matrix of the conflict between pedestrians and intelligent vehicles. Then their evolutionary paths are analyzed to predict whether pedestrians will pass or not. On this basis, strategy is made on whether the intelligent vehicle will pass. This paper also simulates the evolutionary path according to the determined parameters. Results show that the method of making decisions on the behavior of intelligent vehicles according to the evolutionary process so as to avoid colliding with pedestrians crossing the street is reasonable and effective.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128561258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Predictive Cruise Control of Connected Vehicle With Online Parameters Learning 基于在线参数学习的互联汽车预测巡航控制
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2021-10-29 DOI: 10.1109/CVCI54083.2021.9661240
Yuhao Wang, X. Gong, Jiamei Lin, Yunfeng Hu, Hong Chen
{"title":"Predictive Cruise Control of Connected Vehicle With Online Parameters Learning","authors":"Yuhao Wang, X. Gong, Jiamei Lin, Yunfeng Hu, Hong Chen","doi":"10.1109/CVCI54083.2021.9661240","DOIUrl":"https://doi.org/10.1109/CVCI54083.2021.9661240","url":null,"abstract":"The acquisition of multi-dimensional traffic information and constantly increasing computational power enable sophisticated control techniques to be applied in cruise control system. This study proposes a predictive cruise control (PCC) scheme based on model predictive control, which is formulated as a multi-objective nonlinear optimization problem. In order to facilitate the proposed PCC to deal with different driving conditions, a clustering method is used to identify the driving state of the preceding vehicle. Then, Bayesian optimization method is adopted to learn the optimal weighting parameters in the multi-objective optimization function, which can improve the control performance. Simulation results show that 2.83% fuel-saving rate can be obtained by applying Bayesian optimization method compared to fixed weighting parameters while maintaining good tracking ability and driving comfort.","PeriodicalId":419836,"journal":{"name":"2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128575020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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