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National Names Phrase List

V2X Core Technical Committee
  • Ground Vehicle Standard
  • J2540/3_201906
  • Current
Published 2019-06-11 by SAE International in United States

This SAE Standard provides a table of textual messages meeting the requirements for expressing the names of street and roads and some basic building blocks for phrases commonly used in the ITS industry. The tables provided herein are taken from SAE J2369, and follow the rules of SAE J2540 and therefore allow a local representation in various different languages, media expressions, etc. to allow true international use of these phrases. The phrases are predominantly intended to provide a means to express street names including pre and post fixes (North Oak Street is an example name with a prefix "North" and main portion "Oak" and a suffix "Street"). Other phrases exist for other specific specialty areas of ITS, and all such phrases follow a set of encoding and decoding rules outlined in SAE J2540 to ensure that the use of these phrases in messages remain interoperable between disparate types of user equipment.

 
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RDS Phrase Lists

V2X Core Technical Committee
  • Ground Vehicle Standard
  • J2540/1_201906
  • Current
Published 2019-06-11 by SAE International in United States

This SAE Standard provides a table of textual messages meeting the requirements for expressing "Radio Data Systems" (RDS) phrases commonly used in the ITS industry. They can be used both over the RDS subcarrier transmission media as part of a 37-bit long "Group 8a message" as well as being used to provide a common content list of phrases used in a wide number of other media and applications.

 

A Non-Contact Overload Identification Method Based on Vehicle Dynamics

Suizhou-WUT Industry Research Institute-Gangfeng Tan
Wuhan University of Technology-Daolin Zhou, Yiran Ding, Shimin Yu, Xiaofei Ma, Shuai Wang, Zhenyu Wang
Published 2019-04-02 by SAE International in United States
The vehicle overload seriously jeopardizes traffic safety and affects traffic efficiency. At present, the static weighing station and weigh-in-motion station are both relatively fixed, so the detection efficiency is not high and the traffic efficiency is affected; the on-board dynamic weighing equipment is difficult to be popularized because of the problem of being deliberately damaged or not accepted by the purchaser. This paper proposes an efficient, accurate, non-contact vehicle overload identification method which can keep the road unimpeded. The method can detect the vehicle overload by the relative distance (as the characteristic distance) between the dynamic vehicle's marking line and the road surface. First, the dynamics model of the vehicle suspension is set up. Then, the dynamic characteristic distance of the traffic vehicle is detected from the image acquired by the calibrated camera based on computer vision and image recognition technology. The data error caused by the vehicle vibration can be reduced by the filter set up in this paper. Finally, the actual axle load of the vehicle can be obtained combined with the established…
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Route-Optimized Energy Management of Connected and Automated Multi-Mode Plug-In Hybrid Electric Vehicle Using Dynamic Programming

Michigan Technological University-Neeraj Rama, Huanqing Wang, Joshua Orlando, Darrell Robinette, Bo Chen
Published 2019-04-02 by SAE International in United States
This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route. The objective of the optimizer is to enable future Connected and Automated Vehicles (CAVs) to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile information from Intelligent Transportation Systems (ITS), Internet of Things (IoT), High-definition Mapping, and onboard sensing technologies. Emphasis is placed on runtime minimization to quickly react and plan an optimal mode scheme in highly dynamic road conditions with minimal computational resources. On-road performance of the…
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Ensuring Fuel Economy Performance of Commercial Vehicle Fleets Using Blockchain Technology

Ohio State University-Hamza Anwar, Mukilan Arasu, Qadeer Ahmed
Published 2019-04-02 by SAE International in United States
In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas. We implement a consortium blockchain infrastructure, as opposed to a fully public blockchain (similar to the blockchain underlying Bitcoin) which is arguably not real-time or well suited for this safety-critical application. By leveraging in real-time a fleet vehicle’s powertrain status, geospatial traffic data,…
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New Paradigm in Robust Infrastructure Scalability for Autonomous Applications

Wayne State University-Kyle W. Brown
Published 2019-04-02 by SAE International in United States
Artificial Intelligence (A.I.) and Big Data are increasing become more applicable in the development of technology from machine design and mobility to bio-printing and drug discovery. The ability to quantify large amounts of data these systems generate will be paramount to establishing a robust infrastructure for interdisciplinary autonomous applications. This paper purposes an integrated approach to the environment, pre/post data processing, integration, and system security for robust systems in intelligent transportation systems. The systems integration is based on a FPGA embedded system design and computing (EDGE) platform utilizing image processing CNN algorithms from High Energy Physics (HEP) experiments in data centers with associative memory to ROS- FPGA technology in vehicles for hyper-scale infrastructure scalability. The ability to process data in the future is equivalent to collision particle detection that the Large Hadron Collider (LHC) produces at CERN. The future of robust scalability will depend upon how seamlessly several applications can be integrated into a high-performance package with minimal consumption. The proposed architecture will entirely be dependent on a digital network with special attention paid to…
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State-of-the-Art and Development Trends of Energy Management Strategies for Intelligent and Connected New Energy Vehicles: A Review

Tongji University-Zhen Song, Ke Song, Tong Zhang
Published 2019-04-02 by SAE International in United States
Intelligent and connected vehicle (ICV) and new energy vehicle (NEV) will be two important directions of the automotive technology in the future, and the coordinated development of these two directions reflects relevantly the higher requirements put forward by nowadays society and people. Through the use of intelligent and connected technology (ICT), NEVs can exchange various traffic information data with the outside world (e.g. other running vehicles, road infrastructure, internet, etc.) in real time, which is so-called Vehicle to Everything (V2X). Based on the further analysis of the mutual traffic information, the vehicles can identify the current driving conditions and predict the future driving conditions effectively, which can realize the real time optimization of the energy management strategies (EMSs) of vehicles’ powertrain system, so as to meet the driving requirements of vehicles under different driving conditions. This will not only greatly improve the fuel economy of NEVs, but also ease the traffic congestion situation effectively. A review on the application results of intelligent and connected technology in NEVs (mainly hybrid vehicles) in recent years are given,…
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Deep Learning in Machine Vision

  • Magazine Article
  • TBMG-33894
Published 2019-03-01 by Tech Briefs Media Group in United States

FLIR Systems has introduced their Firefly machine vision camera with open platform deep learning inference onboard. Deep learning makes it possible to easily develop high performance solutions for difficult vision problems.

 

Active Safety Bicyclist Test Targets Recommendation

Active Safety Systems Standards Committee
  • Ground Vehicle Standard
  • J3157_201902
  • Current
Published 2019-02-06 by SAE International in United States
The goal of the Bicyclist Test Mannequin Task Force is to develop standard specifications/requirements for bicyclist test mannequins (one adult and one child) that are representative of real bicyclists to the sensors used in Bicyclist Detection systems and can be used for performance assessment of such in-vehicle systems (including warning and/or braking) in real world test scenarios/conditions. This version of the document only includes the recommended bicyclist mannequin characteristics for vision, Lidar, and/or 76 to 78 GHz radar-based Bicyclist Pre-Collision systems.
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Optimization of Vehicle Operating Conditions by Using Simulation Modeling Software

Kherson State Agrarian University-Olena Volska
Kherson State Maritime Academy-Igor Gritsuk, Evgen Belousov, Dmytro Pohorletskyi
Published 2019-01-16 by SAE International in United States
The paper describes the process of modeling and optimizing the operating conditions of vehicles for a section of the transport network using simulation tools. The cyphergrams of the transport flow intensities in the transportation hub were built, a graphic model of vehicle traffic in the transportation hub was built, and a transition probability matrix was compiled, which was used to simulate modeling and optimize vehicle operating conditions for the considered transport hub. It is necessary to use simulation modeling software that supports all simulation methods and a powerful built-in library for traffic modeling. The corresponding simulation model was created. With the help of it, modeling in the transport hub selected for research has been carried out and the optimum values of the duration of the phases of traffic light objects have been obtained. It has reduced the average travel time through the site, which is considered in the work, and the number of cars in traffic jams. In the process of modeling, the objective function is formed with the corresponding restrictions. Also, the task of…
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