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自动驾驶、激光雷达、自动泊车文集

自动驾驶、激光雷达、自动泊车文集,高级驾驶辅助系统 (ADAS) 和即将推出的自动驾驶汽车依靠对环境的准确感知来做出有关车辆轨迹的正确决策。在可能影响驾驶决策(例如照明)的不同情况下,这些系统必须具有特殊程度的鲁棒性。因此,用于汽车应用的感知系统的设计通常面向具有多种互补感官模式的拓扑结构。视觉系统很常见 [1],主要是因为它们能够提供外观信息。在可用的视觉设备中,立体视觉系统利用一对相隔固定距离的相机来获取有关环境的深度信息,作为一种经济高效的解决方案脱颖而出,能够提供额外的密集 3D 信息来模拟周围环境的车辆。另一方面,近年来 3D 激光扫描仪背后技术的快速发展使其在研究和工业驱动应用中得到广泛应用。与视觉系统相反,激光雷达距离测量的特点是精度高;此外,它们可以在完整的 360° 视野中提供信息。

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自动驾驶、激光雷达、自动泊车文集 文档列表

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Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:In Autonomous Vehicles (AVs), one fundamental pillar is perception,which leverages sensors like cameras and LiDARs (Light Detectionand Ranging) to understand the driving environment. Due to itsdirect impact on road safety, multiple prior efforts have been madeto study its the security of perception systems. In contrast to priorwork that concentrates on camera-based perception, in this workwe perform the first security study of LiDAR-based perception inAV settings, which is highly important but unexplored. We considerLiDAR spoofing attacks as the threat model and set the attack goalas spoofing obstacles close to the front of a victim AV. We findthat blindly applying LiDAR spoofing is insufficient to achieve thisgoal due to the machine learning-based object detection process. Thus, we then explore the possibility of strategically controlling thespoofed attack to fool the machine learning model. We formulatethis task as an optimization problem and design modeling methods for the input perturbation function and the objective function. We also identify the inherent limitations of directly solving theproblem using optimization and design an algorithm that combinesoptimization and global sampling, which improves the attack success rates to around 75%. As a case study to understand the attackimpact at the AV driving decision level, we construct and evaluatetwo attack scenarios that may damage road safety and mobility. We also discuss defense directions at the AV system, sensor, andmachine learning model levels.
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An Improved Strapdown Inertial Navigation System Initial Alignment Algorithm for Unmanned Vehicles
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Along with the development of computer technology and informatization, the unmannedvehicle has become an important equipment in military, civil and some other fields. The navigationsystem is the basis and core of realizing the autonomous control and completing the task for unmannedvehicles, and the Strapdown Inertial Navigation System (SINS) is the preferred due to its autonomyand independence. The initial alignment technique is the premise and the foundation of the SINS,whose performance is susceptible to system nonlinearity and uncertainty. To improving systemperformance for SINS, an improved initial alignment algorithm is proposed in this manuscript. In the procedure of this presented initial alignment algorithm, the original signal of inertial sensorsis denoised by utilizing the improved signal denoising method based on the Empirical ModeDecomposition (EMD) and the Extreme Learning Machine (ELM) firstly to suppress the high-frequencynoise on coarse alignment. Afterwards, the accuracy and reliability of initial alignment is furtherenhanced by utilizing an improved Robust Huber Cubarure Kalman Filer (RHCKF) method tominimize the influence of system nonlinearity and uncertainty on the fine alignment. In addition, realtests are used to verify the availability and superiority of this proposed initial alignment algorithm.
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An Optimization Design of Adaptive Cruise Control System Based on MPC and ADRC
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:In this paper, a novel adaptive cruise control (ACC) algorithm based on model predictivecontrol (MPC) and active disturbance rejection control (ADRC) is proposed. This paper uses an MPCalgorithm for the upper controller of the ACC system. Through comprehensive considerations, theupper controller will output desired acceleration to the lower controller. In addition, to increasethe accuracy of the predictive model in the MPC controller and to address fluctuations in thevehicle’s acceleration, an MPC aided by predictive estimation of acceleration is proposed. Due to theuncertainties of vehicle parameters and the road environment, it is difficult to establish an accuratevehicle dynamic model for the lower-level controller to control the throttle and brake actuators. Therefore, feed-forward control based on a vehicle dynamic model (VDM) and compensatory controlbased on ADRC is used to enhance the control precision and to suppress the influence of internal orexternal disturbance. Finally, the proposed optimal design of the ACC system was validated in roadtests. The results show that ACC with APE can accurately control the tracking of the host vehiclewith less acceleration fluctuation than that of the traditional ACC controller. Moreover, when themass of the vehicle and the slope of the road is changed, the ACC–APE–ADRC controller is still ableto control the vehicle to quickly and accurately track the desired acceleration.
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Automatic Extrinsic Calibration for Lidar-Stereo Vehicle Sensor Setups
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:—Sensor setups consisting of a combination of 3Drange scanner lasers and stereo vision systems are becominga popular choice for on-board perception systems in vehicles;however, the combined use of both sources of informationimplies a tedious calibration process. We present a method forextrinsic calibration of lidar-stereo camera pairs without userintervention. Our calibration approach is aimed to cope withthe constraints commonly found in automotive setups, such aslow-resolution and specific sensor poses. To demonstrate theperformance of our method, we also introduce a novel approachfor the quantitative assessment of the calibration results, basedon a simulation environment. Tests using real devices have beenconducted as well, proving the usability of the system and theimprovement over the existing approaches. Code is available athttp://wiki.ros.org/velo2cam calibration.
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Automatic Extrinsic Calibration of Vision and Lidar by Maximizing Mutual Information
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper reports on an algorithm for automatic, targetless, extrinsic calibration of a lidar and optical camera system based upon the maximization of mutual information between the sensor-measured surface intensities. The proposed method is completely data-driven and does not require any fiducial calibration targets—making in situ calibration easy. We calculate the Cramer-Rao lower bound (CRLB) of the estimated calibration param- ′ eter variance, and we show experimentally that the sample variance of the estimated parameters empirically approaches the CRLB when the amount of data used for calibration is sufficiently large. Furthermore, we compare the calibration results to independent ground-truth (where available) and observe that the mean error empirically approaches zero as the amount of data used for calibration is increased, thereby suggesting that the proposed estimator is a minimum variance unbiased estimate of the calibration parameters. Experimental results are presented for three different lidar-camera systems: (i) a three-dimensional (3D) lidar and omnidirectional camera, (ii) a 3D time-of-flight sensor and monocular camera, and (iii) a 2D lidar and monocular camera. C 2014 Wiley Periodicals, Inc.
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AUTOMATIC LASER CALIBRATION, MAPPING, AND LOCALIZATION FOR AUTONOMOUS VEHICLES
标签:自动驾驶激光雷达自动泊车
积分:1 类型:技术书籍上传者:太白金星上传时间:2021-08-31
简介:This dissertation presents several related algorithms that enable important capabilities forself-driving vehicles. Using a rotating multi-beam laser rangefinder to sense the world, our vehicle scans millions of 3D points every second. Calibrating these sensors plays a crucial role in accurateperception, but manual calibration is unreasonably tedious, and generally inaccurate. Asan alternative, we present an unsupervised algorithm for automatically calibrating both theintrinsics and extrinsics of the laser unit from only seconds of driving in an arbitrary andunknown environment. We show that the results are not only vastly easier to obtain thantraditional calibration techniques, they are also more accurate. A second key challenge in autonomous navigation is reliable localization in the faceof uncertainty. Using our calibrated sensors, we obtain high resolution infrared reflectivityreadings of the world. From these, we build large-scale self-consistent probabilistic lasermaps of urban scenes, and show that we can reliably localize a vehicle against these maps towithin centimeters, even in dynamic environments, by fusing noisy GPS and IMU readingswith the laser in realtime. We also present a localization algorithm that was used in theDARPA Urban Challenge, which operated without a prerecorded laser map, and allowedour vehicle to complete the entire six-hour course without a single localization failure. Finally, we present a collection of algorithms for the mapping and detection of traffic lights in realtime. These methods use a combination of computer-vision techniquesand probabilistic approaches to incorporating uncertainty in order to allow our vehicle toreliably ascertain the state of traffic-light-controlled intersections.
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Automatic Parallel Parking Algorithm for a Carlike Robot using Fuzzy PD+I Control
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:—In this work, the design, analysis, andimplementation of an algorithm for automatic parallel parkingfor a nonholonomic mobile robot is presented. The mobile robotis a four-wheeled scaled vehicle and it is assumed that there isspace limitation for the parking maneuver. The main objectivewas to design a parallel parking path trajectory avoidingcollisions. We designed a fuzzy PD+I controller for driving theerror generated between the real position and the previouslygenerated objective position to the origin. We presentedsimulations results to validate the analysis and demonstratinghow the fuzzy controller solved the tracking problem for thederived path trajectory to follow.
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Automatic Parking and Path Following Control for a Heavy-Duty Vehicle
标签:自动驾驶激光雷达自动泊车
积分:1 类型:技术书籍上传者:太白金星上传时间:2021-08-31
简介:The interest in autonomous vehicles has never been higher and there are several components that need to function for a vehicle to be fully autonomous; oneof which is the ability to perform a parking at the end of a mission. The objective of this thesis work is to develop and implement an automatic parking system (APS) for a heavy-duty vehicle (HDV). A delimitation in this thesis work isthat the parking lot has a known structure and the HDV is a truck without anytrailer and access to more computational power and sensors than today’s commercial trucks. An automatic system for searching the parking lot has been developed whichupdates an occupancy grid map (OGM) based on measurements from GPS andLIDAR sensors mounted on the truck. Based on the OGM and the known structure of the parking lot, the state of the parking spots is determined and a pathcan be computed between the current and desired position. Based on a kinematic model of the HDV, a gain-scheduled linear quadratic (LQ)controller with feedforward action is developed. The controller’s objective is tostabilize the lateral error dynamics of the system around a precomputed path. The LQ controller explicitly takes into account that there exist an input delayin the system. Due to minor complications with the precomputed path the LQcontroller causes the steering wheel turn too rapidly which makes the backupdriver nervous. To limit these rapid changes of the steering wheel a controllerbased on model predictive control (MPC) is developed with the goal of makingthe steering wheel behave more human-like. A constraint for maximum allowedchanges of the controller output is added to the MPC formulation as well asphysical restrictions and the resulting MPC controller is smoother and morehuman-like, but due to computational limitations the controller turns out lesseffective than desired. Development and testing of the two controllers are evaluated in three differentenvironments of varying complexity; the simplest simulation environment contains a basic vehicle model and serves as a proof of concept environment, thesecond simulation environment uses a more realistic vehicle model and finallythe controllers are evaluated on a full-scale HDV. Finally, system tests of the APS are performed and the HDV successfully parkswith the LQ controller as well as the MPC controller. The concept of a self-parkingHDV has been demonstrated even though more tuning and development needsto be done before the proposed APS can be used in a commercial HDV.
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AUTOMATIC PARKING OF SELF-DRIVING CAR BASED ON LIDAR
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the selfdriving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parkingspace according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improvedin two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle’sdynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realizethe stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automaticparking system is feasible and effective.
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Autonomous parking control for intelligent vehicles based on a novel algorithm
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Along with the increasing number of vehicles, parking space becomes narrow gradually, safety parking puts forwardhigher requirements on the driver’s driving technology. How to safely, quickly and accurately park the vehiclo to parkingspace right? This paper presents an automatic parking scheme based on trajectory planning, which analyzing themechanical model of the vehicle, establishing vehicle steering model and parking model, coming to the conclusion that it isthe turning radius is independent of the vehicle speed at low speed. The Matlab simulation environment verifies thecorrectness and effectiveness of the proposed algorithm for parking. A class of the automatic parking problem of intelligentvehicles is solved.
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Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:As a key technology for intelligent vehicles, automatic parking is becoming increasinglypopular in the area of research. Automatic parking technology is available for safe and quick parkingoperations without a driver, and improving the driving comfort while greatly reducing the probabilityof parking accidents. An automatic parking path planning and tracking control method is proposed inthis paper to resolve the following issues presented in the existing automatic parking systems, that is,low degree of automation in vehicle control; lack of conformity between segmented path planning andreal vehicle motion models; and low success rates of parking due to poor path tracking. To this end,this paper innovatively proposes preview correction which can be applied to parking path planning,and detects the curvature outliers in the parking path through the preview algorithm. In addition, it isalso available for correction in advance to optimize the reasonable parking path. Meanwhile, the dualsliding mode variable structure control algorithm is used to formulate path tracking control strategiesto improve the path tracking control effect and the vehicle control automation. Based on the abovealgorithm, an automatic parking system was developed and the real vehicle test was completed,thus exploring a highly intelligent automatic parking technology roadmap. This paper provides twokey aspects of system solutions for an automatic parking system, i.e., parking path planning and pathtracking control.
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Automatic Parking Vehicle System
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Vehicle automation, autonomy and connectivity is a subject of mechatronics integrating manyengineering disciplines including electrical, mechanical, control, and computer engineering (andtechnology). It is fundamentally changing the concept of automobile transportation andmanufacturing. Therefore, developing new, technologically progressive curricula and hands-onlab as well as student project materials is desired to prepare for the future workforce needs ofautonomous cars in the automotive industry. This “Automatic Vehicle Parking System” is aresearch and concept-proving project that will be prepared and extended to develop teachingmaterials for courses and students project on the subject of vehicle automation, autonomy andconnectivity. In this project, an RC (remote-controlled) toy car is modified by integratingultrasound sensors and Arduino with a high current shield to control the vehicle movements andthe parking processes. Parking strategies and the corresponding algorithms are explored andprogramed through Arduino. During testing, the car is able to move to detect the imitated “roadside” environment, judge a space suitable for parking or not, and then drive to parkautomatically. A 3D printer is utilized to build the parts needed for modification. Studentworking processes of design, hardware modification, as well as the algorithm and codingprocedures are observed and evaluated for systematic course material development.
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Design and construction of an electric autonomous driving vehicle
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:The objective of this project consisted on creating a vehicle able to repeat a trajectory it hadfollowed before, driven by a human. The system would have sensors to detect the obstaclesand to be able to react according to their position. Many extra sensors were used in order tomeasure the deformation of the suspensions, the wheel speed…It was also considered using a GPS, a gyroscope, an accelerometer… to compare theinformation given by them with the orders followed by the CPU, as well as a light sensor(LDR) to help deciding if the camera and the computer vision algorithm should be used. Without much light, it could consider parking in the nearest possible spot. It was alsoproposed using a spotlight. Also, a pressure sensor was considered to be located inside theseat, in order to detect if there was somebody sitting on it or not. If none was sitting, the carwould stop. However, some ideas were considered to not be primary and were saved for aposterior version of the vehicle. This project consists also on leading a group of Russian students, which were separated insix groups, two of them related with making the vehicle autonomous. With their help, thisproject could reach to its end and the autonomous vehicle was ended successfully.
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Development of electro-hydro automatic parking braking system for automotive system
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:A parking brake is an important tool of anyautomotive system. Conventional parking brake systems requiresthe driver to manually pull the lever if the brakes are to beapplied. To some extent, the vehicle is left without applying theparking brake due to the insensibility, which could make thevehicle in danger if there any gradient of the road and strongwind. The aim of this manuscript is to present an automaticelectro-hydro parking braking system which brakes once thevehicle park. This is developed by associating the wheel speedsensors, accelerator proximity sensors, controller, and a linearactuator. This electro-hydro automatic parking braking systemautomatically brakes the vehicle when it parks. It ensures thevehicle to remain stationary when it is parked and preventsvehicle rollaway or any unwanted movement that might occur. Itincreases the safety of the vehicle as well as others around it. Thelinear actuator displacement is controlled in this study by theauto-clamping system when the vehicle park. The model has beentested considering the road gradient 2-25%. The automaticparking braking system requires hydraulic pressure 383.66 kPato ensure the vehicle park on 25% gradient, which is 11% lessthan the vehicle to brake from speed of 35 km/h.
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Design and Development of Low Cost Automatic Parking Assistance System
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Parking cars is quite a challenge in congested parking baysand for inexperienced drivers. Automatic parking assistancesystems (APAS) are limited to high-end cars in India. Thispaper discusses the design of APAS for Hyundai Santro anddevelopment of an automatic parking assistant system for ascaled down prototype model using a stepper motor mountedultrasonic sensor to scan the obstacles. 3-point unequalrotating radius algorithm is used to identify parking pathshifting points and parking trajectory. Path shifting controlalgorithm based on timing and distance traversed is developedusing MPLAB IDE. A prototype is developed on a scaled down model of a vehicleand performance of the APAS system is verified. Accuracy ofthe system is ±10% which is acceptable for low cost solutiondeveloped. Repeatability of APAS is tested, which is ±15%. This can be improved with closed loop control in parkingprocess. Cost of the developed system is reduced by morethan 50% of the commercially available APAS systems. Fromthe results, APAS system can be used in any small segmentcars with little changes in logic. Path traversed can be used asfeedback to further improve the accuracy of APAS system.
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Design of Lidar-system
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This thesis is intended to be a first investigation into the design of a laser rangefinding system with sufficient performance to be able to be implemented in aLIDAR system. All parts of the system including the transmitting and receivingcircuitry as well as the optical setup is to be considered. An aim of this project isto use ordinary off-the-shelf components. A literature study on different laser range finding architectures and existingproducts has been performed, as well as a theoretical analysis of different photodetectors. Eye safety aspects when using lasers have been reviewed, and properprecautions were taken. The chosen circuit topology has been simulated to ensurecorrect operation and to fine tune component values. A first PCB layout was created and realised, and a second revision was doneto improve discovered shortcomings of the first revision. The performance of thetwo systems has been evaluated experimentally, especially the second revision. Performance wise, the designed system has been shown to measure distancesof up to 27 m with a standard deviation of 15 cm at an estimated measurementspeed of at least 8 kHz.
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Introduction to LiDAR
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:LiDAR uses electromagnetic (EM) waves in the optical and infraredwavelengths. It is an active sensor, meaning that it sends out an EM waveand receives the reflected signal back. It is similar to microwave radar,except at a much shorter wavelength. This means that it will have muchbetter angular resolution than radar but will not see through fog or clouds. It is similar to passive electro-optical (EO) sensors in wavelengths, exceptthat it provides its own radiation rather than using existing radiation,and has many more sensing modes due to control over the scene illumination. LiDAR brings its own flashlight and can therefore see at night usingnear-infrared wavelengths, whereas passive EO sensors have limitedcapability in the near infrared at night because of insufficient availablenear-infrared radiation. This means that LiDAR can have increased angularresolution associated with the shorter wavelengths and still operate 24 hoursper day. Figure 1.1 is a diagram showing the EM spectrum that puts LiDAR (andEO devices, in general) into the broader EM–wave context. We see that thevisible and infrared spectra have shorter wavelengths than radiowaves andmicrowaves, but longer wavelengths than x rays and gamma rays. This is alog scale, so the change in wavelength is large. A typical tracking microwaveradar might have a frequency of 10 GHz, which corresponds to a wavelengthof 3 cm. This is called X-band radar. A typical search radar may have afrequency of 1 GHz and a wavelength of 30 cm. This is called L-band radar. Since a typical eye-safe LiDAR will have a frequency of 200 THz and awavelength around 1.5 mm, a typical LiDAR will have a wavelength about20,000 times smaller than the X-band tracking radar, and 200,000 timessmaller than the L-band search radar, with corresponding increases incarrier frequency. X rays and gamma rays will be orders of magnitudeshorter in wavelength and higher in frequency than visible or infrared EMradiation.
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LIDAR – A new (self-driving) vehicle for introducing optics to broader engineering and non-engineeri
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Since Stanley, the self-driven Stanford car equipped with five SICK LIDAR sensors won the 2005 DARPA Challenge,the race to developing and deploying fully autonomous, self-driving vehicles has come to a full swing. By now, it hasengulfed all major automotive companies and suppliers, major trucking and taxi companies, not to mention companieslike Google (Waymo), Apple and Tesla. With the notable exception of the Tesla self-driving cars, a LIDAR (Light,Detection and Ranging) unit is a key component of the suit of sensors that allow autonomous vehicles to see and navigatethe world. The market space for lidar units is by now downright crowded, with a number of companies and their respectivetechnologies jockeying for long-run leading positions in the field. Major lidar technologies for autonomous driving includemechanical scanning (spinning) lidar, MEMS micro-mirror lidar, optical-phased array lidar, flash lidar, frequencymodulated continuous-wave (FMCW) lidar and others. A major technical specification of any lidar is the operatingwavelength. Many existing systems use 905 nm diode lasers, a wavelength compatible with CMOS-technology detectors. But other wavelengths (like 850 nm, 940 nm and 1550 nm) are also investigated and, in the long run, the telecom nearinfrared range (1550 nm) is expected to experience significant growth because it offers a larger detecting distance range(200-300 meters) within eye safety laser power limits while also offering potential better performance in bad weatherconditions. This paper discusses the above-mentioned technical (optics and photonics) aspects of the most common lidartechnologies, with the educational focus of identifying opportunities for employing such discussions in introducing opticsto broader engineering audiences, drawing in part on experiences and examples from Kettering University.
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LIDAR Based Vehicle Classification
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Vehicle classification data are used in many transportation applications, including: pavement design, environmental impact studies, traffic control, and traffic safety (FHWA, 2001). There are several classification methods, including: axle-based (e.g., pneumatic tube and piezoelectric detectors), vehicle length-based (e.g., dual loop and some wayside microwave detectors), as well as emerging machine vision based detection. Each sensor technology has its own strengths and weaknesses regarding costs, performance, and ease of use. Operating agencies spend millions of dollars to deploy vehicle classification stations to collect classified count data, yet very few of these stations are ever subjected to a rigorous performance evaluation to ensure that they are reporting accurate data. As noted in the Traffic Monitoring Guide (FHWA, 2001), the quality of data collected depends on the operating agency to periodically calibrate, test, and validate the performance of classification sensors, but few operating agencies have an on-going performance monitoring system to ensure that well tuned classification stations do not drift out of tune. Both one time and periodic performance monitoring have been prohibitively labor intensive because the only option has been to manually validate the performance, e.g., classifying a sample by hand. When these studies are conducted, the manual classifications are usually of limited value both because the manual data are prone to human error, and among the few studies that have been published, most employ the conventional reporting periods used by the stations (typically 15 min periods or longer), which are too coarse, allowing over-counting errors to cancel under-counting errors. In the present study we develop a classification performance monitoring system to allow operating agencies to rapidly assess the performance of existing classification stations on a per vehicle basis. We eliminate most of the labor demands and instead, deploy a portable non-intrusive vehicle classification system (PNVCS) to classify vehicles, concurrent with an existing classification station. For this study we use a side-fire LIDAR (light detection and ranging) based classifier from Lee and Coifman (2012a) for the PNVCS. Fig. 1 shows a flowchart of our performance evaluation system. The existing classification station normally follows the three boxes within the dashed region (top left of the figure) when it is not under evaluation. The PNVCS is shown immediately to the right of the dashed region. To prevent classification errors from canceling one another in aggregate, we record per-vehicle record (pvr) data in the field from both systems. After the field collection the classification results are evaluated on a per-vehicle basis. Algorithms for time synchronization and for matching observations of a given vehicle between the two classification systems are developed in this study. These algorithms automatically compare the vehicle classification between the existing classification station and the PNVCS for each vehicle. If the two systems agree, the given vehicle is automatically taken as a success by the classification station under the implicit assumptions: (i) That few vehicles will be misclassified the same way by the two independent classification systems. (ii) That the PNVCS has sufficient accuracy so that its data can be used as a benchmark for the existing classification station (in this case Lee and Coifman, 2012a, found that the LIDAR system classified vehicles with 99.5% accuracy on an evaluation set of 21,769 non-occluded vehicles). The temporary deployment includes a video camera mounted close to the LIDAR sensors and pointed at their detection zone (right-most path in Fig. 1) to allow a human to assess any discrepancies. A human only looks at a given vehicle when the two systems disagree, and for this task we have developed tools to semi-automate the manual validation process, greatly increasing the efficiency and accuracy of the human user. The data sets in this study take only a few minutes for the user to validate an hour of pvr data from a multi-lane facility.
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MEMS Mirrors for LiDAR A Review
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:: In recent years, Light Detection and Ranging (LiDAR) has been drawing extensive attentionboth in academia and industry because of the increasing demand for autonomous vehicles. LiDAR isbelieved to be the crucial sensor for autonomous driving and flying, as it can provide high-densitypoint clouds with accurate three-dimensional information. This review presents an extensive overviewof Microelectronechanical Systems (MEMS) scanning mirrors specifically for applications in LiDARsystems. MEMS mirror-based laser scanners have unrivalled advantages in terms of size, speed andcost over other types of laser scanners, making them ideal for LiDAR in a wide range of applications. A figure of merit (FoM) is defined for MEMS mirrors in LiDAR scanners in terms of aperture size,field of view (FoV) and resonant frequency. Various MEMS mirrors based on different actuationmechanisms are compared using the FoM. Finally, a preliminary assessment of off-the-shelf MEMSscanned LiDAR systems is given.
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Parking Slot Markings Recognition for Automatic Parking Assist System
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper describes a monocular vision basedparking-slot-markings recognition algorithm, whichis used to automate the target position selection ofautomatic parking assist system. Peak-pair detectionand clustering in Hough space recognize markinglines. Specially, one-dimensional filter in Houghspace is designed to utilize a priori knowledge aboutthe characteristics of marking lines in bird’s eyeview edge image. Modified distance between pointand line-segment is used to distinguish guidelinefrom recognized marking line-segments. Once theguideline is successfully recognized, T-shapetemplate matching easily recognizes dividingmarking line-segments. Experiments show thatproposed algorithm successfully recognizes parkingslots even when adjacent vehicles occlude parkingslot-markings severely.
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ParkSense Automatic Parking Positioning by Leveraging In-Vehicle Magnetic Field Variation
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Drivers often park their vehicles without consciously (physically or mentally) noting down theparked location which makes it hard and inconvenient for the users to later locate their vehicles. Existingsolutions either require users to explicitly note down the parked position on their mobile device by performinga certain action, such as pressing a button to turn on their global positioning system, or are erroneous andinaccurate. This paper attempts to build ParkSense, a system that allows a smart phone to accurately andautomatically ‘‘sense,’’ and later navigate to, the position at which the vehicle was parked. We propose tomake use of the variations of magnetic fields and electromagnetic fields inside the vehicles to detect whena user stops and turns off his or her vehicle. Our evaluation with an actual implementation of the system ondifferent mobile platforms and operating systems, tested on different mobile devices/phones and car models,shows the detection accuracy of more than 90%, confirming the feasibility of our approach.
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Performance Test of Autonomous Vehicle Lidar Sensors Under Different Weather Conditions
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper intends to analyze the Light Detection and Ranging (Lidar) sensor performance on detecting pedestrians under different weather conditions. Lidar sensor is the key sensor in autonomous vehicles, which can provide high-resolution objectinformation. Thus, it is important to analyze the performance of Lidar. This paper involves an autonomous bus operating several pedestrian detection tests in a parking lot at the University at Buffalo. By comparing the pedestrian detection results onrainy days with the results on sunny days, the evidence shows that the rain can cause unstable performance and even failuresof Lidar sensors to detect pedestrians in time. After analyzing the test data, three logit models are built to estimate the probability of Lidar detection failure. The rainy weather still plays an important role in affecting Lidar detection performance. Moreover, the distance between a vehicle and a pedestrian, as well as the autonomous vehicle velocity, are also important. This paper can provide a way to improve the Lidar detection performance in autonomous vehicles.
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Real time emergency auto parking system in driver lethargic state for accident preventing
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper is presenting a safety driving and accidentpreventing system which uses a vision sensor to detect driver drowsinessand lethargic states. The system notifies the driver in dangerous situations. Moreover, in case the driver is unable to conduct safe driving, emergencyparking system is to be activated. The system comprises two stages. First isa drowsiness detection stage which uses a smartphone or a tablet computeras a processing unit. The second stage is the vehicle emergency parkingcontrol system which uses a microcontroller unit (MCU). The MCU isconnected to an alarm system, hazard lights and a vehicle control interface. The experiment results showed realistic real time responses. Drowsinessdetection processing time average is about 480 ms / frame. Alarmingsystem is responding perfectly within 500 ms. Simulation results illustratethe effectiveness of the developed schemes for the auto parking system inreal time. The average time from drowsiness detection to fully parking, ifthe vehicle is moving at the speed of 100 km/s, is about 15s.
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Remote Attacks on Automated Vehicles Sensors Experiments on Camera and LiDAR
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Autonomous automated vehicles are the next evolution intransportation and will improve safety, traffic efficiency anddriving experience. Automated vehicles are equipped withmultiple sensors (LiDAR, radar, camera, etc.) enabling local awareness of their surroundings. A fully automated vehicle will unconditionally rely on its sensors readings to makeshort-term (i.e. safety-related) and long-term (i.e. planning)driving decisions. In this context, sensors have to be robustagainst intentional or unintentional attacks that aim at lowering sensor data quality to disrupt the automation system. This paper presents remote attacks on camera-based systemand LiDAR using commodity hardware. Results from laboratory experiments show effective blinding, jamming, replay, relay, and spoofing attacks. We propose software andhardware countermeasures that improve sensors resilienceagainst these attacks.
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Review of Electrical Architectures and Power Requirements for Automated Vehicles
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Automated vehicles require sensors and computerprocessing that can perceive the surrounding environment andmake real time decisions. These additional electrical loads expandthe auxiliary load profile, therefore reducing the range of an automated electric vehicle compared to a standard electric vehicle. Furthermore, a fully automated vehicle must be fail-safe fromsensor to vehicle control, thus demanding additional electricalloads due to redundancies in hardware throughout the vehicle. This paper presents a review of the sensors needed to makea vehicle automated, the power required for these additionalauxiliary loads, and the necessary electrical architectures forincreasing levels of robustness.
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Robust Auto-parking Reinforcement Learning based Real-time Planning Approach with Domain Template
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper presents an automatic parking for a passenger vehicle, with highlights on arobust real-time planning approach and on experimental results. We propose a frameworkthat leverages the strength of learning-based approaches for robustness to environmentsnoise and capability of dealing with challenging tasks, and rule-based approaches for itsversatility of handling normal tasks, by integrating simple rules with RL under a multi6 stage architecture, which is inspired by typical auto-parking template. By taking temporalinformation into consideration with using Long Short Term Memory (LSTM) network, ourapproach could facilitate to learn a robust and humanoid parking strategy efficiently. Wepresent preliminary results in a high-fidelity simulator to show our approach can outperforma geometric planning baseline in the robustness to environment noise and efficiency ofplanning.
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Simulation of the Automatic Parking Assist System as a Method of the Algorithm Development Thinking
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:The teaching of algorithm developmentand programming should develop not only practicalskills, theoretical knowledge and techniques, butalgorithmic thinking in particular. [1] The ability ofalgorithmic thinking can be cultivated throughimplementation of modeling and computersimulation of real phenomena into the teaching ofalgorithm development not only at universities, butalso at high schools and elementary schools. [2, 3]The process of complex problem solving leads thestudents to implement problem analysis in order tofigure out the given problem. Whole process of theproblem analysis, including its solution, strategy,algorithm development and creation of the computersimulation, is presented in the article in a step bystep form of the case study simulating a real process- the Automatic Active Parking Assist System. Computer simulation of this process is presented bymeans of robotic system LEGO? Mindstorms? andprogrammed in the integrated developmentenvironment of LEGO? Mindstorms? NXT-G.
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Study on an Automatic Parking Method Based on the Sliding Mode Variable Structure and Fuzzy Logical
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper discusses an automatic parking control method based on the combination ofthe sliding mode variable structure control (SMVSC) and fuzzy logical control. SMVSC is applied todrive the vehicle from a random initial position and pose, to the designated parking position andpose. Then, the vehicle is driven from the designated parking position to the target parking slotusing the method of fuzzy logical control, whose rules are limited to the range of the effective initialposition. To combine SMVSC with the fuzzy logical control, the experimental results demonstratethat effective parking can be guaranteed, even if the initial position is out of the effective parkingarea of the fuzzy logical control.
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THE ARGO AUTONOMOUS VEHICLE’S VISION AND CONTROL SYSTEMS
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:This paper presents the current status of the ARGO Project, whose main target is the development of an active safety system and an automatic pilot for a standard road vehicle. First the ARGO project is briefly described along with its main objectives, then the prototype vehicle and its functionalities are presented. The perception of the environment isperformed through the processing of images acquired from the vehicle; details about thedetection of lane markings, generic obstacles and leading vehicles are given. The paperdescribes the current implementation of the control system, based on a gain scheduledcontroller, which allows the vehicle to follow the road and/or other vehicles, while futurecontrol strategies (flatness approach) are presented with simulations results. The paperends with a description of the MilleMiglia in Automatico tour, a journey through Italyperformed in automatic driving, together with some concluding remarks.
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TI Designs LIDAR Pulsed Time of Flight Reference Design
标签:自动驾驶激光雷达自动泊车
积分:1 类型:应用文档上传者:太白金星上传时间:2021-08-31
简介:This reference design documents how to design thetime measurement back-end for LIDAR based on thetime-to-digital converter (TDC) as well as associatedfront-end.
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Vehicle Inertia Impact on Fuel Consumption of Conventional and Hybrid Electric Vehicles Using Accele
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:Vehicle Inertia Impact on Fuel Consumption ofConventional and Hybrid Electric Vehicles UsingAcceleration and Coast Driving Strategy
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Vision Based Automatic Parking Slot Detection for ADAS
标签:自动驾驶激光雷达自动泊车
积分:1 类型:学术论文上传者:太白金星上传时间:2021-08-31
简介:The fast increment of autos the need todiscover accessible parking spot in the most productive way, tododge activity clog in a stopping territory, is turning into aneed in auto stop administration. ADAS structure offersassistance to the driver and makes progress drivingfoundation. Current auto stop administration is subject toeither human work force monitoring the accessible auto stopspaces or a sensor based framework the establishment andsupport cost of a sensor construct framework is reliant withrespect to the quantity of sensors utilized as a part of an autostop. The picture division calculation utilized with theexpectation of complimentary space identification. Visionbased framework that can distinguish and demonstrate theaccessible parking spots by utilizing camera in vehicle.

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