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Vision based solution for auto- maneuvering of vehicle for emerging market

General Motors Technical Center-Souvik Bose, Ashwani Kumar Singh, D V Ram Kumar Singampalli
General Motors Technical Center India-Chandraprakash lalwani
  • Technical Paper
  • 2019-28-2517
To be published on 2019-11-21 by SAE International in United States
Vision based solution for auto- maneuvering of vehicle for emerging market: Author/Co-Author: Singh Ashwani, SDV Ram Kumar, Bose Souvik, Lalwani Chandraprakash General Motors Technical Centre India Key words: Image Processing, Gap finding, virtual/Imaginary lines, Advance Driver Assist System (ADAS), Vehicle to vehicle(V2V)/Vehicle to Infrastructure(V2I/V2X) Research & Engineering Objective: For the various levels of autonomous, the current perception algorithms involve considerable number of sensor inputs like cameras, radars and Lidars and their fusion logics. The planning route for the vehicle navigation is done through map information which is highly volatile and keep changing many at times. Existing steering assist feature during a curve is available by combining additional driver monitoring camera & 360 degree camera. The complexity is very high in the implementation and computation of these algorithm. These solutions are not cost-effective for emerging markets. Non-availability of required infrastructure in developing countries is one of the additional constrain. Feature unavailability due to road infrastructure (ex: poor or no lane markings), bad weather will lead to higher customer dissatisfaction. The objective is to develop a logic/study…
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DEVELOPMENT OF A FLEET MANAGEMENT SYSTEM FOR AN OFF-HIGHWAY VEHICLE

Research & Devlopment Institute-Jagannathan Vasu
  • Technical Paper
  • 2019-28-2439
To be published on 2019-11-21 by SAE International in United States
DEVELOPMENT OF A FLEET MANAGEMENT SYSTEM FOR AN OFF-HIGHWAY VEHICLE V.Jagannathan 1.a* , B.Jaiganesh 2.b & S.Sudarsanam 3.c Mahindra & Mahindra Limited, Mahindra Research Valley, Mahindra World City, Anjur PO, TN, India Corresponding author Email- V.JAGANNATHAN@mahindra.com Managing an off-highway vehicle fleet during validation is a challenging task. Complexity is acquainted when more than 100 vehicles with different horse power (hp) & with different product configuration working across India and other parts of countries. Traditionally, a tractor validation involves data collection such as usage hours (Hour meter reading on cluster), locations etc. which are recorded in spread sheet and updated to the respective project owners on daily basis through mail communications. A manual recording and consolidation of tractors validation status is prone to error, reiterative work, consumes more resource and effort. Moving towards digitalization, IT enabled system for updating the tractor validation status on daily basis was added with advantage of huge data storage capacity, history data retrieval and data access anytime & anywhere, a step ahead to traditional method but with few limitations of not…
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Trajectory Tracking Control for Autonomous Driving Vehicle with Obstacle Avoidance: Modeling, Simulation, and Performance Analysis

SAE International Journal of Connected and Automated Vehicles

China-Songxin Shi
Huazhong University of Science and Technology, China-Hefeng Zhan, Chaoran Lin, Qiangqiang Huang
  • Journal Article
  • 12-02-04-0014
Published 2019-11-19 by SAE International in United States
The external driving environment of an autonomous driving vehicle is complex and changeable. In this article, the trajectory tracking control with obstacle avoidance based on model predictive control was presented. Specifically, double-level control scheme by controlling the front steering angle was used in our research, and the double level is composed of the high level of model predictive controller for local trajectory planning and low level of model predictive controller for trajectory tracking. At high level, the local trajectory planner based on the point-mass model was designed. Then, at low level, the linear time-varying vehicle dynamics model was presented, and the trajectory tracking controller was proposed considering control variable, control increment, and output constraint. Finally, the trajectory tracking performance was tested in co-simulation environment with CarSim and Simulink, and the tracking errors were analyzed. Compared with the controller without a high level for local trajectory planning, this article indicates that the trajectory tracking controller has rather effective and efficient trajectory tracking performance during all conventional cases, which shows strong robustness to vehicle speed.
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Weighted Distance Metrics for Data Association Problem in Multi-Sensor Fusion

Dongfeng Motor Corporation Technical Center-Darui Zhang, Ning Bian, Daihan Wang, Hang Yang, Xinjuan Tuo
Published 2019-11-04 by SAE International in United States
Traffic accidents are the world's leading threat to human safety. The majority of traffic accidents are due to human error. Advanced Driver Assist Systems (ADAS) can reduce human error, therefore has the potential to effectively improve the safety of road traffic. The perception module in an ADAS understands the surrounding environment of the subject vehicle and therefore is the prerequisite for planning and control. Due to the limitation of computational constrain of Electronic Control Units, ADAS system commonly uses object-leveled multi-sensor fusion, in which raw data is processed to detect objects at the sensory level. In multi-sensor fusion, the task of assigning new observations to the existing tracks, known as Data Association problem, requires distance metrics to present the similarity between tracks. In the literature, metrics, such as standardized Euclidean distance and Mahalanobis distance has been used. Though accounting for the scale and correlation of the data, the existing metrics cannot account for the importance of each feature in predicting their dissimilarity. As a result, weighting factors are added to the distance metrics and they…
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Study on Robust Motion Planning Method for Automatic Parking Assist System Based on Neural Network and Tree Search

Tongji University-Fengwei Hu, Hui Chen, Jiren Zhang
Published 2019-11-04 by SAE International in United States
Automatic Parking Assist System (APAS) is an important part of Advanced Driver Assistance System (ADAS). It frees drivers from the burden of maneuvering a vehicle into a narrow parking space. This paper deals with the motion planning, a key issue of APAS, for vehicles in automatic parking. Planning module should guarantee the robustness to various initial postures and ensure that the vehicle is parked symmetrically in the center of the parking slot. However, current planning methods can’t meet both requirements well. To meet the aforementioned requirements, a method combining neural network and Monte-Carlo Tree Search (MCTS) is adopted in this work. From a driver’s perspective, different initial postures imply different parking strategies. In order to achieve the robustness to diverse initial postures, a natural idea is to train a model that can learn various strategies. As artificial neural network has outstanding potential in representing and learning knowledge, a neural network is utilized to provide prior knowledge, which is trained through supervised learning by a novel method that imitates human learning style. However, the training accuracy…
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An IMPC Based Parking Assistance System

FinitronX-Qianyu Ouyang, Xianzhe Jia
Published 2019-10-22 by SAE International in United States
This paper summarizes progress and outcome from our research projects on IMPC-based parking management system, including parking motion planning and control strategy, as well as a searching strategy for parking spot. IMPC here refers to interactive model predictive control regime, which is characterized in that multiple agents implementing separate MPC strategy are incorporating information about their state, objective, and constraints. To predict future parking parameters, we proposed a practical framework which integrates anticipatory techniques with a model predictive approach that robustly models the stochastic parking environment. The framework is able to take into account the interactions between vehicle subsystems, and can optimize trajectory under complex traffic patterns in real-world scenarios. Adaptive model predictive control is utilized to optimally minimize a cost function regarding performance, energy efficiency and drivability with regard to surrounding vehicle states. Dynamic programming was used to solve the control objective under multiple constraints, which yielded superior performance in comparison with convex programming. An original navigation system was developed for leading user to the parking spot in case of forgetting exact location, which…
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Sensor Perception and Motion Planning for an Autonomous Material Handling Vehicle

Automotive Research Association of India (ARAI)-Sanjay A Patil
Vellore Institute of Technology-Sahil Prabhakar, Dani Priyanka, Ankit Ghosh
Published 2019-10-22 by SAE International in United States
The ground mobile robotics study is structured on the two pivotal members namely Sensor Perception and Motion Planning. Sensor perception or Exteroception comprises the ability of measurement of the layout of the environment relative to vehicle's frame of reference which is a necessity for the implementation of safe navigation towards the goal destination in an unstructured environment. Environment scanning has played a significant role in mobile robots application to investigate the unexplored environment in the sector of defence while transporting and handling material in warehouse and hospitals. Motion Planning is a conjunction of analyzing the sensor's information while being able to plan the route from starting point to the target destination. In this paper, a 3600 2-D LiDAR is used to capture the spatial information of the surrounding, the scanning results are presented in a local map and global map. The LiDAR’s output is further transformed into an Occupancy grid for the comprehension of the Motion planning module to process the path. Probabilistic Roadmap and Vector Field Histogram are two methods used for Motion Planning.…
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Handling of Data from Heterogeneity of Vehicular Devices through Inter-Networking

VIT Universtity-Gnanaprakasam Anuradha, Kalivaradhan Ramesh Babu
Vellore Institute of Technology-Chooriyaparambil Damodaran Naiju
Published 2019-10-11 by SAE International in United States
Collection of various data from sensed data or raw availability of data from transcript or interdependency of data from various sources is a tedious task in a real time scenario like an Indian context is considered. Planning to find a solution to collect the data from various vehicular devices about the information related to the pollution becomes a cumbersome job. The need of the data, under what time duration data has to be transmitted, how they are interconnected and whether data needs to be stored or how they are processed is a major question that arise when dealing with collecting data and internetworking with various vehicular devices. A study of two different types of approaches for internetworking between the devices is discussed. One related to real time setup of mobile application and other with the dynamic cluster approach when the nodes are moving in a region was considered. Eliminating the speed of the vehicle with the movement of human formation of cluster with the mobile application to identify the various devices in the vicinity was…
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Demand Side Load Management by Using Priority Based Load Shedding Algorithm with and without Renewable Energy Generation

SRM Institute of Science And Technology-Rajarajeswari Rathinam, Suchitra Dayalan
Published 2019-10-11 by SAE International in United States
Demand side load management (DSLM) emphasizes control of the power demanded, by reducing the peak load and control of energy utilization of the system. DSLM is introduced to improve the flexibility of the grid power usage and also to aid the utilization of Renewable Energy Generation (REG) which is intermittent. In this work, implementation of load shedding (LS) algorithm for the residential load is performed with the limit of power as constraint, considering REG and grid in three different modes of operation. Solar and Wind power are the REG considered in this work. Priority Based Load Shedding (PBLS) is performed to limit the power consumption of equipment during peak hours with the implementation of varying pricing signal. In order to implement PBLS, three residential user load data for 24 hours is considered. The users are categorized as low, medium and high priority user. The priority of the user is based on the load consumption for 24 hours. The proposed LS scheme is performed, depending on the power requirements of Home Electric Devices (HEDs) and the…
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Spatiotemporal Imaging Exploiting Structured Sparsity

  • Magazine Article
  • TBMG-35104
Published 2019-09-01 by Tech Briefs Media Group in United States

Spatiotemporal imaging contains a large class of imaging problems, which involve collecting a sequence of data sets to resolve both the spatial and temporal (or spectral) distributions of some physics quantity. This capability is exploited in numerous different fields such as remote sensing, security surveillance systems, astronomical imaging, and biomedical imaging. One typical example is hyperspectral imaging, which is a powerful technology for remotely inferring the material properties of the objects in a scene of interest. Ultrasonic and thermal imaging are other important examples of spatiotemporal imaging where high spatial resolution is needed for urban planning, military planning, intelligence and disaster monitoring and evaluation.