Browse Topic: Lidar

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Background Filtering and Target Detection for Traffic Objects with Roadside LiDAR Point Cloud Data2025-01-719303/19/2025
Roadside perception technology is an essential component of traffic perception technology, primarily relying on various high-performance sensors. Among these, LiDAR stands out as one of the most effective sensors due to its high precision and wide detection range, offering extensive application prospects. This study proposes a voxel density-nearest neighbor background filtering method for roadside LiDAR point cloud data. Firstly, based on the relatively fixed nature of roadside background point clouds, a point cloud filtering method combining voxel density and nearest neighbor is proposed. This method involves voxelizing the point cloud data and using voxel grid density to filter background point clouds, then the results are processed through a neighbor point frame sequence to calculate the average distance of the specified points and compare with a distance threshold to complete accurate background filtering. Secondly, a VGG16-Pointpillars model is proposed, incorporating a CNN
Liu, Zhiyuan, Rui, Yikang
SAE TOMORROW TODAY: How AI Alignment Makes AVs Safer1349501/10/2025
In order for AVs to perform safely and reliably, we need to teach them the language of human preference and expectations--and accelerating AI alignment can do just that. Enter Kognic, the industry-leading annotation platform for sensor-fusion datasets (e.g., camera, radar, and LIDAR data). By helping companies gather, organize, and refine massive datasets used for training AI models, Kognic is helping to ensure that AD/ADAS perform reliably and meet safety standards--all while minimizing costs and optimizing teams. To learn more, we sat down with Daniel Langkilde, Co-Founder and CEO, to discuss why the future of autonomous driving depends on effectively managing AI-driven datasets and how Kognic is leading dataset management for safety-critical AI. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in
Hineman, Marcie
Bi-directional adjustable holder for LiDAR sensor - Assembly findings and solutions2024-26-002401/16/2024
LiDAR stands for Light Detection and Ranging and it works on the Principle of reflection of light. LiDAR is one among the other sensors like radar and camera to achieve a high level (Level 3 & above) of Autonomous driving capabilities. LiDAR, as a sensor, is used to perceive the environment in 3D by calculating the 'Time of flight' of the Laser beam transmitted from LiDAR and the rays reflected from the Object, along with the intensity of reflection from the object. The frame of perception is plotted as a point Cloud. LiDAR is assembled/ integrated on the roof of the vehicle/grill position of car having a high vantage point to perceive the environment in order to extract the best possible sensor performance. LiDAR sensor needs to be held in the front panel cutout with uniform gap however due to tolerance reasons it may have following issues: Function of the sensor can be affected if it is not aligned center to the cutout because the view cones will interfere with grill cutout edges
Pratap, Amit, Rangarej, Sanjeev
Reducing LiDAR Cabin Noise with Damped Elastomers: a Novel Method for Predicting Performance and Durability2025-01-011405/05/2023
Mechanical LiDAR units utilize spinning lasers to scan surrounding areas to enable limited autonomous driving. The motors within the LiDAR modules create noise that can leak into the cabin of a vehicle. Decoupling the module from the body of the vehicle with highly damped elastomers can reduce the acoustic noise in the cabin and improve the driving experience. Damped elastomers work by absorbing the vibrational energy and dispelling it as latent heat, which creates challenges in an unpredictable automotive environment. Throughout the development process with vehicle OEMs and LiDAR ODMs, highly damped elastomers were able to effectively reduce the noise created by the scanning LiDAR modules in a laboratory environment. It was unproven that these elastomers would be as effective in extreme heat, cold, or humid environments. Extensive bench and vehicle tests were conducted, but confidence was low without a model to predict behavior at edge-cases. By creating a unique test method to model
Russell, Casey, Masterson, Peter, O'Connell, Kerry
Panoptic Based Camera and Lidar Fusion for Distance Estimation in Autonomous Driving Vehicles2022-28-030710/05/2022
Position estimation of the surrounding objects seen by the sensors mounted on an autonomous vehicle is a key module and it is typically carried out with the camera-lidar fusion owing to the high accuracy in depth estimation from lidar point cloud. In typical automotive LIDAR with 64 scanner points or less, at distances above 100m, the object detection with LIDAR is not dependable as the number of LIDAR clusters will be sparse, while the high-resolution camera can offer better detection even at the distances above 100m. Calculation of the position can be best achieved if there is a reliable means to get the corresponding LIDAR points for the detection in camera. To address this, we are proposing a novel a grid-based approach, in which a grid is created in the point cloud by calculating object’s position derived from camera detections. The correspondence between Camera pixels and LIDAR point cloud tends to suffer when the object of interest is occluded (eg.by other vehicles, guard rails
Jose, Edwin, P, Aparna M, Patil, Mrinalini, Thayyil Ravi, Arunkrishna, Rajan, Manoj
Synthetic LiDAR Point Cloud Data Generation Tool and Deep Learning Validation2022-01-017703/29/2022
LiDAR sensors are set to become common in automated driving due to their high accuracy. However, LiDAR processing algorithm development suffers from lack of training data, partly due to the sensors' high cost. The few public datasets (e.g. KITTI) offer poor coverage of edge case scenarios, whereas these are essential to address to support safe self-driving. We address the unmet need for abundant, high-quality LiDAR data with the development of an artificial LiDAR point cloud generation tool and validate this tool's performance against the PIXOR model, which was trained on the KITTI dataset. The tool makes use of a single camera raycasting process to generate synthetic data and is used in conjunction with filtering techniques to create segmented and filtered object class-specific datasets . The tool has the potential to support the low-cost generation of accurate bulk data in support of training advanced self-driving algorithms, with configurability to simulate commercial and yet-to-be
Karur, Karthik, Pappas, Georgios, Siegel, Joshua, Zhang, Mi
Infrastructure-Based LiDAR Monitoring for Assessing Automated Driving Safety2022-01-008603/29/2022
The successful deployment of automated vehicles (AVs) could include the use of off-board sensors for assessments to be made of AV operational safety. Many intersections and roadways have monocular cameras used primarily for traffic monitoring; however, monocular cameras may not be sufficient to allow for useful AV operational safety assessments to be made in all operational design domains (ODDs) such as low ambient light and inclement weather conditions. Additional sensor modalities such as Light Detecting And Ranging (LiDAR) sensors allow for a wider range of scenarios to be accommodated, but may also provide improved measurements of the Operational Safety Assessment (OSA) metrics previously introduced by the Institute of Automated Mobility (IAM). Building on earlier work from the IAM in creating an infrastructure-based sensor system to evaluate the OSA metrics in real-world scenarios, this paper presents an approach for real-time localization and velocity estimation for AVs using a
Srinivasan, Anshuman, Mahartayasa, Yoga, Jammula, Varun Chandra, lu, Duo, Como, Steven, Wishart, Jeffrey, Elli, Maria, Yang, Yezhou, Yu, Hongbin
A Comparison of Mobile Phone Lidar Capture and Established Ground based 3d Scanning Methodologies.2022-01-098803/29/2022
Ground-based LiDAR using FARO 3d scanners and other brands of scanners have been shown to be an accurate way to capture the geometry of accident scenes, accident vehicles and exemplar vehicles, as well as corresponding evidence from these sources such as roadway gouge marks, vehicle crush depth, and burn areas. However, ground-based scanners do require expensive and larger equipment to be brought on-site, as well as other materials that may be required depending on the scenario. New technologies, such as Apple’s mobile phone LiDAR capture, have been released recently in their newer model phones, and they offer a chance to obtain similar results but with less cumbersome and less expensive equipment. This technology embeds photos with lidar data that can then be exported into point cloud data using different applications available in the app store. This paper will investigate the accuracy of Apple mobile phone LiDAR on obtaining geometry from multiple exemplar vehicles. This mobile LiDAR
Miller, Seth Higgins, Hashemian, Alireza, Gillihan, Robert, Helms, Ethan
Improvement of Black Car Paint for Enhanced Visibility to LiDAR Systems 2022-01-041303/29/2022
One of the most revolutionary technological developments in recent years has been the invention and improvements of autonomous vehicles. LiDAR (Light Detecting and Ranging) sensors, which can generate distance measurement with precision on the order of cm, have been increasingly evaluated and used in the detection of various objects, including vehicles, for transportation safety application and the future adoption and deployment of autonomous vehicles. However, not all objects a vehicle encounters on the road are equally reflective to infrared light used in the LiDAR sensors. In particular, black cars, which make up a significant portion of the market, are minimally reflective to infrared light, and can become invisible to LiDAR systems for certain orientations. Thus black vehicles present a significant challenge to the deployment of autonomous vehicles. The goal of this paper was to develop a novel method for making black car paints more visible to LiDAR systems. Our approach was to
Block, Claire, Hays, Patrick, Rogel, Cindy, Yu, Hongbin
Dynamically Adjustable LiDAR with SPAD Array and Scanner2021-01-009104/06/2021
An important function of an Automated Driving (AD) system is to detect objects including vehicles and pedestrians on the road. Typical devices for detecting those objects include cameras, millimeter-wave RADAR, and light detection and ranging (LiDAR). LiDAR uses the flight time of a short-wavelength electromagnetic wave. Because of that LiDAR is expected to find even small objects such as tire fragments on a road in high resolution. The detection performance required for LiDAR depends on the operational design domain (ODD). For example, while a vehicle is travelling at high speeds, LiDAR needs to detect apparently small objects at long distances, and while it is travelling at low speeds, LiDAR has to detect objects over a wide angular range. Conventional LiDAR is developed to satisfy all requirements, providing performance including detection distance, resolution, and angle of view tends to expose issues such as cost and size when it is mounted onboard. To solve these problems, we have
Nakajima, Masato, Hata, Takehiro, Ueno, Akifumi, Ozaki, Noriyuki, Mizuno, Fumiaki, Kashiwada, Shinji, Yanai, Kenichi
Development of Fault Detection and Emergency Control for Application to Autonomous Vehicle2021-01-007504/06/2021
This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely. The Adaptive
Jong Min, Lee, Oh, Kwang Seok, Song, Taejun
Research on Automatic Joint Calibration Method of Multi 3D-LIDARs and Inertial Measurement Unit2021-01-007004/06/2021
In the field of automatic driving, the combination of 3D LIDAR and inertial measurement unit (IMU) is a common sensor configuration scheme in laser point-cloud localization, high-precision map making and point-cloud target detection. So it is critical to calibrate LIDAR and IMU accurately. At present, due to the large volume and high cost of 3D LIDAR with high-line-number(Such as 64 lines or 128 lines), the configuration scheme of using multiple low-line-number 3D LIDARs appears in the automatic driving vehicle sensing system. However, the common calibration methods are not suitable for multi 3D LIDARs and IMU parameters calibration on autonomous vehicle, which have the disadvantages of cumbersome implementation and low accuracy. In this paper, a joint calibration test platform composed of dual LIDARs and IMU is assembled, and a method of precise automatic calibration based on GPS/RTK data is proposed. Firstly, the initial parameters of the main 3D LIDAR and IMU are obtained by hand
Zhang, Jinghua, He, Rui, Wu, Jian, Li, Shuai, Chen, Xuesong, Du, Zhiqiang, Chen, Guosheng, Chen, Zhicheng
Impact of Fog Particles on 1.55 μm Automotive LiDAR Sensor Performance: An Experimental Study in an Enclosed Chamber2021-01-008104/06/2021
To achieve full automation in self-driving vehicles, environmental perception sensing accuracy is critically important. However, ambient particles in adverse weather like foggy, rainy, or snowy conditions can significantly scatter the incident laser beam, and therefore contaminate the intensity and accuracy of light detection and ranging (LiDAR) sensors. Especially compared to the rapidity of technology development in self-driving vehicles, there is a significant lack of documented research on LiDAR systems with wavelength longer than 1 μm for application in Advanced Driver-Assistance Systems. In this work, experimental studies were performed with a state-of-the-art 1.55 μm wavelength automotive-grade LiDAR system in a controlled laboratory fog chamber. The goal of the research is to correlate laser attenuation and the optical properties of fog particles. In this work, a thorough multistep procedure for LiDAR data analysis is presented including spatial averaging of the object
Zhan, Lu, Northrop, William F.
Multi-Sensor Fusion in Slow Lanes for Lane Keep Assist System2021-01-008404/06/2021
Implementing Advanced Driver Assistance Systems (ADAS) features that are available in all road scenarios and weather conditions is a big challenge for automotive companies and considered key enablers to achieve autonomous Level 4 (L4) vehicles. One important feature is the Lane Keep Assist System (LKAS). Most LKAS systems are based on lane line detection cameras and lane coefficient estimations by the camera is the key point for LKAS where the camera recognizes the lane lines using edge detection. But when the lane markers are not available due to high traffic and slow driving on the roads, another source of data for the lane lines needs to be available for the LKAS. In this paper a multi-sensor fusion approach based on camera, Lidar, and GPS is used to allow the vehicle to maintain its lateral location within the lane. The lateral distances of the lane lines are measured by LiDAR detection of the markers based on the intensity and fused with lane line information from the HD Map after
Alrousan, Qusay, Matta, Sherif, Tasky, Tom
Add LiDAR to ADAS for Pedestrian SafetyTBMG-3863003/01/2021
Most new vehicles sold in the United States today include Advanced Driver Assistance Systems (ADAS) equipped with Pedestrian Automatic Emergency Braking (PAEB) as either a standard or optional feature. While state-of-the-art ADAS has improved freeway and high-speed driving, the basic need for collision mitigation with pedestrians and bicyclists has mostly remained unaddressed.
SAE TOMORROW TODAY: Self-Driving For The Long Haul with Kodiak Robotics1293102/19/2021
Kodiak Robotics is delivering more than freight, it's delivering the future. We spoke with Andreas Wendel, Vice President of Engineering at Kodiak Robotics, to discuss how they became a developer of reliable, highway-tested, self-driving long haul trucks and the elements required to create safe vehicles that perform consistently, delivering freight to commercial customers with a 100% on-time delivery record. Discover the difference between range of visibility and range of confidence across cameras, lidar and radar, and why this three-pronged approach allows Kodiak to develop the software and technology that enables zero disengagements across 800 miles.
Hineman, Marcie
Sensitive Optical Receivers for SpaceTBMG-3850302/01/2021
Communications in space demand the most sensitive receivers possible for maximum reach, while also requiring high-bit-rate operations. A concept for laser beam-based communications using an almost noiseless optical preamplifier in the receiver has been developed. The free-space optical transmission system relies on an optical amplifier that, in principle, does not add any excess noise, in contrast to all other pre-existing optical amplifiers referred to as phase-sensitive amplifiers (PSAs).
Kodiak 3D LiDARTBMG-3849102/01/2021
High-orbit satellite servicing and planetary science missions are presented with unique challenges including a harsh environment and long mission life, coupled with the need for long-range, high-speed, accurate measurements. Conventional systems suffer from high costs of bringing other solutions to market and questionable reliability.
Special Section: The Winners of the 2020 'Create the Future' Design ContestTBMG-3828312/01/2020
The , launched in 2002 by Tech Briefs Media Group (publishers of Tech Briefs magazine), recognizes and rewards engineering innovations that benefit humanity, the environment, and the economy. The annual contest draws product designs from engineers, students, and entrepreneurs worldwide.
SAE TOMORROW TODAY: How Velodyne Became a Leader in LiDAR1291411/05/2020
Today's episode is a special chat between host Grayson Brulte and Anand Gopalan, CEO of Velodyne LiDAR.Grayson and Anand discuss the early days of Velodyne, being the CEO of a publicly-traded company, and the growth of the LiDAR market. Enjoy this episode!
Hineman, Marcie
Ambient Light Alters Refraction in 2D MaterialTBMG-3801411/01/2020
Microscopic crystals in tantalum disulfide have a starring role in what could become a hit for 3D displays, virtual reality and even self-driving vehicles. A two-dimensional array of the material has unique optical characteristics that can be controlled in ambient conditions and under general illumination.
Pseudo-Random Coding Technique for 3D ImagingTBMG-3746508/01/2020
NASA Goddard Space Flight Center has developed a high-resolution 3D imaging LiDAR system using a resolution-enhanced pseudo-random code technique that improves the ranging resolution by an order of magnitude with the same transmitted optical power. This new approach uses a spread spectrum time-resolved method, which has been widely used in the field of radar and telecommunications and the technique is also known as random-modulation continuous-wave (RM-CW).
Making Data Logging, Replay and Prototyping More Efficient20AVEP07_0507/01/2020
High levels of continuity and compatibility are vital to avoid interruptions in the development process - and reduce cost. The development of advanced driver assistance (ADAS) and highly automated driving systems poses great challenges for OEM and supplier engineers. It is important, therefore, that powerful, flexibly configurable development systems optimally support the various use cases in data-driven development to make it as efficient as possible. In the case of functionality for both ADAS autonomous driving, the chain of effects can be divided into several steps, starting with environment detection with the aid of extensive sensor technology - including camera, radar, lidar and ultrasonics - and ending with the final implementation of the driving strategy and actuator control (Fig. 2).
Mertens, Frank, Müller, Marius
Optical In-Line VCSEL TestingTBMG-3718707/01/2020
The market for laser diodes has recently experienced strong growth. The drivers of the enormous increase in demand are new applications and new technology concepts. Examples are face recognition in entertainment electronics, LiDAR (light detection and ranging) in automotive applications, and high-performance diode lasers that consist of several laser diodes and are increasingly replacing conventional laser systems in material processing.
Photonic Microwave Generation Using On-Chip Optical Frequency Combs20AERP06_0606/01/2020
In our information society, the synthesis, distribution, and processing of radio and microwave signals happen ubiquitously in wireless networks, telecommunications, and radars. The current tendency is to use carriers in higher frequency bands, especially with looming bandwidth bottlenecks due to demands for 5G and the Internet of Things. Microwave photonics, a combination of microwave engineering and optoelectronics, might offer a solution. A key building block of microwave photonics is optical frequency combs, which provide hundreds of equidistant and mutually coherent laser lines. They are ultrashort optical pulses emitted with a stable repetition rate that corresponds precisely to the frequency spacing of comb lines. The photodetection of the pulses produces a microwave carrier.
Photonic Microwave Generation Using On-Chip Optical Frequency CombsTBMG-3710706/01/2020
In our information society, the synthesis, distribution, and processing of radio and microwave signals happen ubiquitously in wireless networks, telecommunications, and radars. The current tendency is to use carriers in higher frequency bands, especially with looming bandwidth bottlenecks due to demands for 5G and the Internet of Things. Microwave photonics, a combination of microwave engineering and optoelectronics, might offer a solution.
New Graphene-Based Metasurface Capable of Independent Amplitude and Phase Control of LightTBMG-3688005/01/2020
Researchers described a new strategy of designing metamolecules that incorporates two independently controllable subwavelength meta-atoms. This two-parametric control of the metamolecule secures the complete control of both amplitude and the phase of light.
Real-Time Motion Classification of LiDAR Point Detection for Automated Vehicles2020-01-070304/14/2020
A Light Detection And Ranging (LiDAR) is now becoming an essential sensor for an autonomous vehicle. The LiDAR provides the surrounding environment information of the vehicle in the form of a point cloud. A decision-making system of the autonomous car is able to determine a safe and comfort maneuver by utilizing the detected LiDAR point cloud. The LiDAR points on the cloud are classified as dynamic or static class depending on the movement of the object being detected. If the movement class (dynamic or static) of detected points can be provided by LiDAR, the decision-making system is able to plan the appropriate motion of the autonomous vehicle according to the movement of the object. This paper proposes a real-time process to segment the motion states of LiDAR points. The basic principle of the classification algorithm is to classify the point-wise movement of a target point cloud through the other point clouds and sensor poses. First, a fixed size buffer store the LiDAR point clouds
Jo, Kichun, Kim, Chansoo, Cho, Sungjin, Sunwoo, Myoungho
Autonomous Vehicle Multi-Sensors Localization in Unstructured Environment2020-01-102904/14/2020
Autonomous driving in unstructured environments is a significant challenge due to the inconsistency of important information for localization such as lane markings. To reduce the uncertainty of vehicle localization in such environments, sensor fusion of LiDAR, Radar, Camera, GPS/IMU, and Odometry sensors is utilized. This paper discusses a hybrid localization technique developed using: LiDAR-based Simultaneous Localization and Mapping (SLAM), GPS/IMU, Odometry data, and object lists from Radar, LiDAR, and Camera sensors. An Extended Kalman Filter (EKF) is utilized to fuse data from all sensors in two phases. In the preliminary stage, the SLAM-based vehicle coordinates are fused with the GPS-based positioning. The output of this stage is then fused with the object-based localization. This approach was successfully tested on FEV’s Smart Vehicle Demonstrator at FEV’s HQ. It represented a complicated test environment with dynamic and static objects. The test results show that multi-sensor
Alrousan, Qusay, Alzu'bi, Hamzeh, Pfeil, Andrew, Tasky, Tom
Joint Calibration of Dual LiDARs and Camera Using a Circular Chessboard2020-01-009804/14/2020
Environmental perception is a crucial subsystem in autonomous vehicles. In order to build safe and efficient traffic transportation, several researches have been proposed to build accurate, robust and real-time perception systems. Camera and LiDAR are widely equipped on autonomous self-driving cars and developed with many algorithms in recent years. The fusion system of camera and LiDAR provides state-of the-art methods for environmental perception due to the defects of single vehicular sensor. Extrinsic parameter calibration is able to align the coordinate systems of sensors and has been drawing enormous attention. However, differ from spatial alignment of two sensors’ data, joint calibration of multi-sensors (more than two sensors) should balance the degree of alignment between each two sensors. In this paper, we assemble a test platform which is made up of dual LiDARs and one monocular camera and use the same sensing hardware architecture as intelligent sweeper designed by our
Deng, Zhenwen, Xiong, Lu, Yin, Dong, Shan, Fengwu
Lidar Inertial Odometry and Mapping for Autonomous Vehicle in GPS-Denied Parking Lot2020-01-010304/14/2020
High-precision and real-time ego-motion estimation is vital for autonomous vehicle. There is a lot GPS-denied maneuver such as underground parking lot in urban areas. Therefore, the localization system relying solely on GPS cannot meets the requirements. Recently, lidar odometry and visual odometry have been introduced into localization systems to overcome the problem of missing GPS signals. Compared with visual odometry, lidar odometry is not susceptible to light, which is widely applied in weak-light environments. Besides, the autonomous parking is highly dependent on the geometric information around the vehicle, which makes building map of surroundings essential for autonomous vehicle. We propose a lidar inertial odometry and mapping. By sensor fusion, we compensate for the drawback of applying a single sensor, allowing the system to provide a more accurate estimate. Compared to other odometry using IMU and lidar, we apply a tight coupled of lidar and IMU method to achieve lower
Chen, Xuesong, Zhang, Sumin, Wu, Jian, He, Rui, Song, Shiping, Zhu, Bing, Zhao, Jian
LiDAR-Based Predictive Cruise Control2020-01-008004/14/2020
Advanced Driver Assistance Systems (ADAS) enable safer driving by relying on the inputs from various sensors including Radar, Camera, and LiDAR. One of the newly emerging ADAS features is Predictive Cruise Control (PCC). PCC aims to optimize the vehicle’s speed profile and fuel efficiency. This paper presents a novel approach of using the point cloud of a LiDAR sensor to develop a PCC feature. The raw point cloud is utilized to detect objects in the surrounding environment of the vehicle, estimate the grade of the road, and plan the route in drivable areas. This information is critical for the PCC to define the optimal speed profile of the vehicle while following the planned path. This paper also discusses the developed algorithms of the LiDAR data processing and PCC controller. These algorithms were tested on FEV’s Smart Vehicle Demonstrator platform. Test results show that the proposed PCC was implemented successfully, allowing the vehicle to adapt its speed based on the processed
Alzu'bi, Hamzeh, Jarbo, Anthony T., Alrousan, Qusay, Tasky, Tom
LiDAR and Camera-Based Convolutional Neural Network Detection for Autonomous Driving2020-01-013604/14/2020
Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines. Performance of the system is scrutinized
Hamieh, Ismail, Myers, Ryan, Nimri, Hisham, Rahman, Taufiq, Younan, Aarron, Sato, Brad, El-Kadri, Abdul, Nissan, Selwan, Tepe, Kemal
Analysis of Dashcam Video for Determination of Vehicle Speed2020-01-087704/14/2020
Using dashcam video footage to extract reliable vehicle speed data can be challenging when the only available image stream comes from a camera whose optical parameters are unknown. One means of overcoming such difficulties uses visible landmarks and features within the video frame whose dimensions can be independently measured. While good results have been obtained by others using a Total Station or LiDAR to physically measure locations for such purposes, this approach could prove difficult if a site of interest is inaccessible (e.g. on a busy highway that cannot be shut down) or if relevent features of the target location have changed (e.g. due to construction or even restriping of lanes lines). As an alternative to direct scene measurement, it is proposed that measurement of features visible in overhead satellite images be used to dimension relevant features visible in the video. In this work, videos from individual dashcams and phone-based cameras were used to calculate average
Leifer, Jack, Marquez, Alvaro
LiDAR-Based Urban Autonomous Platooning Simulation2020-01-071704/14/2020
The technological advancements of Advanced Driver Assistance Systems (ADAS) sensors enable the ability to; achieve autonomous vehicle platooning, increase the capacity of road lanes, and reduce traffic. This article focuses on developing urban autonomous platooning using LiDAR and GPS/IMU sensors in a simulation environment. Gazebo simulation is utilized to simulate the sensors, vehicles, and testing environment. Two vehicles are used in this study; a Lead vehicle that follows a preplanned trajectory, while the remaining vehicle (Follower) uses the LiDAR object detection and tracking information to mimic the Lead vehicle. The LiDAR object detection is handled in multiple stages: point cloud frame transformation, filtering and down-sampling, ground segmentation, and clustering. The tracking algorithm uses the clustering information to provide position and velocity of the Lead vehicle which allows for vehicle platooning. This paper covers the LiDAR object detection and tracking
Alzu'bi, Hamzeh, Tasky, Tom
Modeling and Design of an Autonomous Dragster2020-01-071104/14/2020
This work outlines the design, modeling and development of a competition eliminator dragster which is a specialized vehicle built to compete in the National Hot Rod Association (NHRA). A simple control strategy was also developed once the vehicle model was validated. Towards that end, redundant braking, steering, throttle and shifting systems were all redesigned, modeled, and then implemented in vehicle. Three key sensors (camera, radar, lidar) were also integrated on to the vehicle to enable the vehicle to know its position relative to the track. All these systems were developed and designed such that the vehicle could be autonomously but seamlessly overridden by an in-vehicle driver.
Bell, Joseph, Donikian, Vatche, Washington, Gregory
LiDAR Based Classification Optimization of Localization Policies of Autonomous Vehicles2020-01-102804/14/2020
People through many years of experience, have developed a great intuitive sense for navigation and spatial awareness. With this intuition people are able to apply a near rules based approach to their driving. With a transition to autonomous driving, these intuitive skills need to be taught to the system which makes perception is the most fundamental and critical task. One of the major challenges for autonomous vehicles is accurately knowing the position of the vehicle relative to the world frame. Currently, this is achieved by utilizing expensive sensors such as a differential GPS which provides centimeter accuracy, or by using computationally taxing algorithms to attempt to match live input data from LiDARs or cameras to previously recorded data or maps. Within this paper an algorithm and accompanying hardware stack is proposed to reduce the computational load on the localization of the robot relative to a prior map. The principal of the software stack is to leverage deep learning and
Hamieh, Ismail, Myers, Ryan, Rahman, Taufiq
Seeing Around Corners to Detect Object ShapesTBMG-3637304/01/2020
A technique was developed that enables reconstruction of images in great detail. Researchers computed millimeter- and micrometer-scale shapes of curved objects, providing an important component to a larger suite of non-line-of-sight (NLOS) imaging techniques.
Lidar in a Flash20AVEP03_0603/01/2020
Continental delivers a short-range 3D flash lidar sensor that's expected to find increasing application in commercial vehicles and off-highway machines in 2020. A precise three-dimensional profile of a vehicle's surroundings is a fundamental prerequisite for automated driving. A new high-resolution 3D flash lidar (HFL) sensor developed for use at close range - 50 m (164 ft) or less - delivers on this capability, according to Thomas Laux, head of business development and sales for HFL segment in Continental's Advanced Driver Assistance Systems (ADAS) business unit. “This is automotive grade and solid state, meaning no moving parts. It's a bunch of semiconductors, which is ideal for commercial vehicle and even more so for the off-highway environment - they don't have a lot of hours [of operation] but their environments can be pretty rigorous,” said Laux. The IP6K9K packaging is very important for these applications, he said, as is a 3D Global Shutter feature that eliminates motion
Gehm, Ryan
Long-Distance LADAR System and MethodTBMG-3598002/01/2020
A laser detection and ranging (LADAR) system was developed to provide unambiguous range and velocity measurements of long-distance targets such as sea-skimming anti-ship missiles. By using the LADAR's range and velocity data, false alarms and clutter objects will be distinguished from incoming missiles at longer ranges (up to 10 km). Because the developed LADAR uses an array receiver, it can also provide three-dimensional (3D) imagery of potential threats at closer ranges (2-3 km) in support of the force protection/situational awareness mission.
Helping Autonomous Vehicles See Around CornersTBMG-3576001/01/2020
To improve the safety of autonomous systems, MIT engineers have developed a system that can sense tiny changes in shadows on the ground to determine if there’s a moving object coming around the corner.
Bringing Precision Anamorphic Micro-Optics to Consumer-Level Laser ApplicationsTBMG-3547511/01/2019
The use of laser light for precise illumination has been limited to high-end applications like optical lithography or small niche markets like measurement technologies. Now that such industries as automotive and consumer electronics are developing and ramping up the production of LIDAR and 3D sensors, laser illumination is scaling in a new direction. For imaging applications, optics made of polymers are already the first choice for such devices as smart cameras. But in order to deliver glass micro-optics with better performance and long-term stability, the cost structure of injection molded polymer optics needed to be addressed.
Wind Event Warning SystemTBMG-3545411/01/2019
NASA Langley Research Center developed a wind event warning technology that provides a practical early warning system (5-10 minutes) for a severe change in the wind vector. Events such as gusts, shear, microbursts, or thunderstorm outflows can be detected in time to prevent damage to wind turbines or help airports prevent damage to aircraft. Further, an alternative power source could be ramped up or down as needed to accommodate the power draw in the electrical grid.
Autonomous Vehicle Engineering: September 201919AVEP0909/05/2019
Editorial The new 'face' of privacy The Navigator No trust in AI systems without data protection Innovation Nation In the mobility space, Israel is rivaling Silicon Valley for smarts and start-ups - and beats it in chutzpah. Autonomy in your Face Biometric technology is deemed essential to ensuring AV driving safety and advancing the user experience-if privacy issues don't derail its deployment. About Face! To win acceptance, deployment of facial-recognition technology needs to fit within a picture-perfect consumer and legal framework that balances benefits with privacy protection. The Vehicle as Gaming Device Audi spin-off Holoride uses VR to turn the back seat into an entertainment platform. BlackBerry Tech Duo Sees Emergence of Vehicle-based Platforms Though likely to provide the OS of autonomy, BlackBerry also anticipates a larger shift to automobiles as software platforms. Improving Lidar - or Defeating It The buzz at Sensors Expo pitted lidar-tech optimism against the reality of
Optical Distance Measurement at Record-High SpeedTBMG-3516209/01/2019
Scientists of Karlsruhe Institute of Technology (KIT) and École Poly-technique Fédérale de Lausanne (EPFL) have reported that they achieved the fastest distance measurement attained so far. The researchers demonstrated on-the-fly sampling of a gun bullet profile with micrometer accuracy. The experiment relied on a soliton frequency comb generated in a chip-based optical microresonator made from silicon nitride. Potential applications include real-time 3D cameras based on highly precise and compact LIDAR systems.
Bringing Human-Like Reasoning to Driverless Car NavigationTBMG-3477207/01/2019
With the aim of bringing more human-like reasoning to autonomous vehicles, MIT researchers have created a system that uses only simple maps and visual data to enable driverless cars to navigate routes in new, complex environments.
SLD and Ice Crystal Discrimination with the Optical Ice Detector2019-01-193406/10/2019
In response to new safety regulations regarding aircraft icing, Collins Aerospace has developed and tested an Optical Ice Detector (OID) capable of discriminating among icing conditions appropriate to Appendix C and Appendix O of 14 CFR Part 25 and Appendix D of Part 33. The OID is a short-range, polarimetric lidar that samples the airstream up to ten meters beyond the skin of the aircraft. The intensity and extinction of the backscatter light correlate with bulk properties of the cloud, such as water content and phase. Backscatter scintillation (combined with the outside air temperature from another probe) signals the presence of supercooled large droplets (SLD) within the cloud-a capability incorporated into the OID to meet the requirements of Appendix O. Recent laboratory and flight tests of the Optical Ice Detector have confirmed the efficacy of the OID to discriminate among the various icing conditions. Drizzle-sized droplets, mixed with a small droplet cloud in the Collins Cloud
Anderson, Kaare J., Ray, Mark D.
Infrared Light-Focusing PlatformTBMG-3463006/01/2019
Researchers have integrated two technologies widely used in applications such as optical communications, bio-imaging, and Light Detection and Ranging (LiDAR) systems to create a new infrared light-focusing system that combines the best features of both technologies while reducing the size of the optical system.
Retinas to Roadways: The Evolution of Optical Coherence TechnologyTBMG-3462306/01/2019
Insight Photonic Solutions Lafayette, CO
Reconstruction of 3D Accident Sites Using USGS LiDAR, Aerial Images, and Photogrammetry2019-01-042304/02/2019
The accident reconstruction community has previously relied upon photographs and site visits to recreate a scene. This method is difficult in instances where the site has changed or is not accessible. In 2017 the United States Geological Survey (USGS) released historical 3D point clouds (LiDAR) allowing for access to digital 3D data without visiting the site. This offers many unique benefits to the reconstruction community including: safety, budget, time, and historical preservation. This paper presents a methodology for collecting this data and using it in conjunction with aerial imagery, and camera matching photogrammetry to create 3D computer models of the scene without a site visit. To determine accuracies achievable using this method, evidence locations solved for using only USGS LiDAR, aerial images and scene photographs (representative of emergency personnel photographs) were compared with known locations documented using total station survey equipment and ground-based 3D laser
Terpstra, Toby, Dickinson, Jordan, Hashemian, Alireza, Fenton, Stephen
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