This SAE Recommended Practice provides common data output formats and definitions for a variety of data elements that may be useful for analyzing the performance of automated driving system (ADS) during an event that meets the trigger threshold criteria specified in this document. The document is intended to govern data element definitions, to provide a minimum data element set, and to specify a common ADS data logger record format as applicable for motor vehicle applications. Automated driving systems (ADSs) perform the complete dynamic driving task (DDT) while engaged. In the absence of a human “driver,” the ADS itself could be the only witness of a collision event. As such, a definition of the ADS data recording is necessary in order to standardize information available to the accident reconstructionist. For this purpose, the data elements defined herein supplement the SAE J1698-1 defined EDR in order to facilitate the determination of the background and events leading up to a

Event Data Recorder Committee

Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles

J3216_202107 (Current)

07/16/2021

This document describes machine-to-machine (M2M) communication to enable cooperation between two or more participating entities or communication devices possessed or controlled by those entities. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle with driving automation feature(s) engaged. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of manually operated vehicles or pedestrians or cyclists carrying personal devices), or road operators (e.g., those who maintain or operate traffic signals or workzones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be used to influence (directly or indirectly) DDT performance by one or more nearby road users

Cooperative Driving Automation(CDA) Committee

Taxonomy and Definition of Safety Principles for Automated Driving System (ADS)

J3206_202107 (Current)

07/07/2021

This SAE Information Report classifies and defines a harmonized set of safety principles intended to be considered by ADS and ADS-equipped vehicle development stakeholders. The set of safety principles herein is based on the collection and analysis of existing information from multiple entities, reflecting the content and spirit of their efforts, including: SAE ITC AVSC Best Practices CAMP Automated Vehicle Research for Enhanced Safety - Final Report RAND Report - Measuring Automated Vehicle Safety: Forging a Framework U.S. DOT: Automated Driving Systems 2.0 - A Vision for Safety Safety First for Automated Driving (SaFAD) UNECE WP29 amendment proposal UNECE/TRANS/WP.29/GRVA/2019/13 On a Formal Model of Safe and Scalable Self-Driving Cars (Intel RSS model) SAE J3018 This SAE Information Report provides guidance for the consideration and application of the safety principles for the development and deployment of ADS and ADS-equipped vehicles. This SAE Information Report is not intended to

On-Road Automated Driving (ORAD) committee

Deep Learning Based Real Time Vulnerability Fixes Verification Mechanism for Automotive Firmware/Software

2021-01-018304/06/2021

Software vulnerability management is one of the most critical and crucial security techniques, which analyzes the automotive software/firmware across the digital cockpit, ADAS, V2X, etc. domains for vulnerabilities, and provides security patches for the concerned Common Vulnerabilities and Exposures (CVE). The process of automotive SW/FW vulnerability management system between the OEMs and vendors happen through a channel of fixing a certain number of vulnerabilities by 1st tier supplier which needs to be verified in front of OEMs for the fixed number and type of patches in there deliverable SW/FW. The gap of verification between for the fixed patches between the OEMs and 1st tier supplier requires a reliable human independent intelligent technique to have a trustworthiness of verification. Hence, in this regard, a novel machine learning based intelligent verification technique is proposed which is free from human intervention to verify the certain number and type of vulnerabilities

Ansari, Asadullah, Ameen Alimohideen, Mohamed, P.C., Karthik

New SAE Standard for Automated-Driving Developers

20AVEP07_0407/01/2020

Developed in less than a year, SAE's new J3216 standard will impact traffic management, operations and safety for automated mobility. In May, amid quarantine and lockdowns for the Coronavirus pandemic, SAE International published SAE J3216 Standard: Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles. The new standard provides clarity to support advancement of full automation. SAE J3216 builds on 2016's SAE J3016 that defines six levels of driving automation, from SAE Level Zero (no automation) to SAE Level 5 (full vehicle autonomy). While J3016 aims to provide clarity and offer a foundation for advancing vehicle automation technologies, the newly-published J3216 does so with terms, definitions and taxonomy focused on Cooperative Driving Automation (CDA), a key building block that supports all levels of automation.

Shuttleworth, Jennifer

SAE STANDARDS NEWS

20AUTP06_0606/01/2020

New Cooperative Driving Automation standard provides clarity to support advancement of full automation In May, amid quarantine and lockdowns for the Coronavirus pandemic, SAE International published SAE J3216 Standard: Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles (https://www.sae.org/standards/content/j3216_202005/). The new standard provides clarity to support advancement of full automation. SAE J3216 builds on 2016's SAE J3016 that defines six levels of driving automation, from SAE Level Zero (no automation) to SAE Level 5 (full vehicle autonomy). While J3016 aims to provide clarity and offer a foundation for advancing vehicle automation technologies, the newly-published J3216 does so with terms, definitions and taxonomy focused on Cooperative Driving Automation (CDA), a key building block that supports all levels of automation.

Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles

J3216_202005 (Historical)

05/07/2020

Cooperative Driving Automation(CDA) Committee

V2X to the Rescue for VRUs!

20AVEP05_0305/01/2020

For motorcyclists and other vulnerable road users, V2X communication is a vital safety asset for the AV future. As development of autonomous vehicles (AV) moves inexorably forward, connectivity-also known as vehicle-to-everything (V2X) communication-will play a crucial role in their adoption. Much of the necessary V2X technology is already available, leaving regulatory and infrastructure challenges as the remaining major obstacles to an effective network rollout. Deployment of V2X capabilities could be a boon to vulnerable road users (VRUs) such as motorcyclists, cyclists and pedestrians, according to safety experts. It is connectivity, not autonomy, that will alert a vehicle that traffic ahead has stopped, or that a motorcycle hidden behind buildings is approaching an intersection. ADAS and AV sensor suites help vehicles that are so equipped navigate their immediate environments in real-time, but it is the V2X network that promises to bring a safer, omniscient view of the road ahead

Seredynski, Paul

Performance Evaluation of the Pass at Green Connected Vehicle V2I Application Using Simulation, Dynamometer and Track Testing

2020-01-138004/14/2020

In recent years, the trend in the automotive industry has been favoring the reduction of fuel consumption in vehicles with the help of new and emerging technologies, such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Vehicle to Everything (V2X) communication. As the world of transportation gets more and more connected through these technologies, the need to implement algorithms with V2I capability is amplified. In this paper, an algorithm called Pass at Green (PaG), utilizing V2I to modify the speed profile of a vehicle to decrease fuel consumption has been studied. PaG uses Signal Phase and Timing (SPaT) information acquired from upcoming traffic lights, which are the current phase of the upcoming traffic light and the remaining time that the phase stays active. Then, PaG modifies the speed of the vehicle by accelerating, keeping its speed constant or decelerating to decrease fuel consumption, minimize idling time and reduce the likelihood of catching a red light in

Kavas-Torris, Ozgenur, Cantas, Mustafa Ridvan, Gelbal, Sukru Yaren, Guvenc, Levent

Optimization of Intersection Safety based on V2X Communication

2020-01-137604/14/2020

Intersections serve as nodes of multiple roads where multiple vehicles meet. Compared with straight roads the traffic environment of intersection is more complex. As a result, accidents in those areas, with the frequent occurrence and severe consequences, are the focus of the study. Vehicle-to-everything (V2X) improves road safety and traffic efficiency of Intelligent Transport System (ITS) in the future. Based on V2X cooperative communications, wireless interconnected vehicles, pedestrians, and infrastructures can collect and change the traffic environmental information with other road users in real-time. Therefore, the potentially dangerous situations in an extended time and space horizon can be perceived. The users of V2X communication devices can utilize computing systems with computers and extended sensors onboard. Based on the intersection road-side infrastructure, Vehicle-to-Infrastructure (V2I) communication has been actively considered to be used in the intersection areas

Wu, Biao, Liao, Maozhu, Ma, Zhixiong, Liu, Rui

Hardware-in-the-Loop and Road Testing of RLVW and GLOSA Connected Vehicle Applications

2020-01-137904/14/2020

This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections. This same approach of HIL testing followed by testing in real intersections using our experimental vehicle is later extended to the GLOSA

Gelbal, Sukru Yaren, Cantas, Mustafa Ridvan, Aksun Guvenc, Bilin, Guvenc, Levent, Surnilla, Gopichandra, Zhang, Hao, Shulman, Michael, Katriniok, Alexander, Parikh, Jayendra

Leverage wireless technologies in timber harvesting to enhance operational productivity and business profitability

2020-01-137804/14/2020

Growing needs of forestry products; primarily wood followed by pulp and paper industry have mechanized the process of harvesting timber in most part of world. Such job sites have several machines and vehicles working together to harvest and transport the logs. Timber logging is very similar to crop harvesting with longer harvesting cycle and hence it is critical that every part of it is effectively utilized; timely harvest and transport to factories play an important role. Traditionally, these areas have had little cellular connectivity, restricting communication between operators, machines, land owners and factories. With better connectivity, it will be easier to monitor and operate job sites for example if skidder would know how many trees are felled, how many logs and bunches are created and where they are kept; it would reduce time and fuel spent in searching for logs. Also, with better communication between machines, skidder would know when to pick up logs and avoid longer wait

Pandit, Ishani, Iyer, Suchitra

Cooperative Mandatory Lane Change for Connected Vehicles on Signalized Intersection Roads

2020-01-088904/14/2020

This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where vehicles are allowed to change lane to follow a prescribed path. The proposed hierarchical control strategy consists of two control levels: a high level controller at the intersection and a decentralized low level controller in each car. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes model predictive control (MPC) to track the target velocity in a fuel efficient manner. The main objective in this paper is to consider mandatory lane changes. As in the realistic scenarios, vehicles are not required to drive in single lane. More specifically, they more likely change their lanes prior to signals. Hence, the

Du, Zhiyuan, Xu, Bin, Pisu, Pierluigi

An Iterative Histogram-Based Optimization of Calibration Tables in a Powertrain Controller

2020-01-026604/14/2020

To comply with the stringent fuel consumption requirements, many automobile manufacturers have launched vehicle electrification programs which are representing a paradigm shift in vehicle design. Looking specifically at powertrain calibration, optimization approaches were developed to help the decision-making process in the powertrain control. Due to computational power limitations the most common approach is still the use of powertrain calibration tables in a rule-based controller. This is true despite the fact that the most common manual tuning can be quite long and exhausting, and with the optimal consumption behavior rarely being achieved. The present work proposes a simulation tool that has the objective to automate the process of tuning a calibration table in a powertrain model. To achieve that, it is first necessary to define the optimal reference performance. The calibration table then has its values optimized by the Genetic Algorithm to a single value that better matches the

Bruck, Lucas, Amirfarhangi Bonab, Saeed, Lempert, Adam, Biswas, Atriya, Anselma, Pier Giuseppe, Roeleveld, Joel, Rane, Omkar, Madireddy, Krishna, Wasacz, Bryon, Belingardi, Giovanni, Emadi, Ali

Android Defense in Depth Strategy in an Automobile Ecosystem

2020-01-136504/14/2020

Android is becoming an environment of choice in the automotive sector because of near production grade open source stack availability and large developer community. With growing interest from Automotive OEMs for Android IVI (In-Vehicle Infotainment) solutions, we predict a similar growth trend in an automobile like in Mobile space. At another end, the need for more interconnected devices within the Automobile ecosystem is increasing, which leads to an increased threat to security. In sophisticated device interconnections, identifying the gateways and implementing the right security strategy is key to improve overall system security & stability. While Android is maturing for automotive and with growing interest from automotive OEMs, we spent time in analyzing current Android defense-in-depth concepts with the automotive perspective. The main aim of this paper is to examine the current defense-in-depth strategies available in Android and propose additional measures to meet automotive

Achuthan, Balasubramanian, Chandupatla, Srinivas, Yerram, Nalinikanth

Synchronous and Open, Real World, Vehicle, ADAS, and Infrastructure Data Streams for Automotive Machine Learning Algorithms Research

2020-01-073604/14/2020

Prediction based optimal energy management systems are a topic of high interest in the automotive industry as an effective, low-cost option for improving vehicle fuel efficiency. With the continuing development of connected and autonomous vehicle (CAV) technology there are many data streams which may be leveraged by transportation stakeholders. The Suite of CAVs-derived data streams includes advanced driver-assistance (ADAS) derived information about surrounding vehicles, vehicle-to-vehicle (V2V) communications for real time and historical data, and vehicle-to-infrastructure (V2I) communications. The suite of CAVs-derived data streams have been demonstrated to enable improvements in system-level safety, emissions and fuel economy. Practical concerns, lack of standardization, and current low levels of technology penetration dictate that the acquisition of real-world data for use in the development of optimal energy management systems is challenging and expensive, presenting a bottleneck

Rabinowitz, Aaron I., Gaikwad, Tushar, White, Samantha, Bradley, Thomas, Asher, Zachary

Simulation of Curved Road Collision Prevention Warning System of Automobile Based on V2X

2020-01-070704/14/2020

Li, Xuanhe, Wu, Jian, He, Rui, Zhu, Bing, Zhao, Jian, Zhou, Hang

A Study of Using a Reinforcement Learning Method to Improve Fuel Consumption of a Connected Vehicle with Signal Phase and Timing Data

2020-01-088804/14/2020

Connected and automated vehicles (CAVs) promise to reshape two areas of the mobility industry: the transportation and driving experience. The connected feature of the vehicle uses communication protocols to provide awareness of the surrounding world while the automated feature uses technology to minimize driver dependency. Constituting a subset of connected technologies, vehicle-to-infrastructure (V2I) technologies provide vehicles with real-time traffic light information, or Signal Phase and Timing (SPaT) data. In this paper, the vehicle and SPaT data are combined with a reinforcement learning (RL) method as an effort to minimize the vehicle’s energy consumption. Specifically, this paper explores the implementation of the deep deterministic policy gradient (DDPG) algorithm. As an off-policy approach, DDPG utilizes the maximum Q-value for the state regardless of the previous action performed. In this research, the SPaT data collected from dedicated short-range communication (DSRC

Phan, Ashley, Yoon, Hwan-Sik

Effects of a Probability-Based Green Light Optimized Speed Advisory on Dilemma Zone Exposure

2020-01-011604/14/2020

Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data. By utilizing this advisory method, real-time communications from the vehicle to infrastructure (V2I) become unnecessary, eliminating data-loss related

Saldivar-Carranza, Enrique, Li, Howell, Kim, Woosung, Mathew, Jijo, Bullock, Darcy, Sturdevant, James

THE MAN FROM ARPA-E

20AUTP04_0104/01/2020

Advanced R&D programs directed by Dr. Chris Atkinson are building the energy-efficient mobility future. Engineers and scientists working in mobility R&D have described Dr. Chris Atkinson as a guiding light in their efforts to make future vehicle propulsion technologies more efficient- and commercially viable. One long-time industry associate dubbed him “the ultimate project manager”-and who could disagree? As a Program Director of ARPA-E-the U.S. Dept. of Energy's Advanced Research Projects Agency-Energy-Dr. Atkinson oversees the funding and progress of 20 or more R&D projects. He leads a team of engineers and commercialization experts at ARPA-E, focusing on improving the energy efficiency of connected and automated vehicles, advanced combustion devices, and energy conversion and storage systems in the transportation space. The building blocks of future batteries, power electronics, EV and PHEV charging, IC engines, and related systems in their nascent stages of development, can be

Brooke, Lindsay

Vehicle Safe-Mode, Concept to Practice Limp-Mode in the Service of Cybersecurity

11-02-02-000602/27/2020

This article describes both a concept and an implementation of vehicle safe-mode (VSM) - a mechanism that may help reduce the damage of an identified cyberattack to the vehicle, its driver, the passengers, and its surroundings. Unlike other defense mechanisms that try to block the attack or simply notify of its existence, the VSM mechanism responds to a detected intrusion by limiting the vehicle’s functionality to safe operations and optionally activating additional security countermeasures. This is done by adopting ideas from the existing mechanism of Limp-mode that was originally designed to limit the damage of a mechanical, or an electrical, malfunction and let the vehicle “limp back home” in safety. Like Limp-mode, the purpose of safe-mode is to limit the vehicle from performing certain functions when conditions arise that could render full operation dangerous: Detecting a malfunction in the Limp-mode case is analogous to detecting an active cybersecurity breach in the safe-mode

Dagan, Tsvika, Montvelisky, Yuval, Marchetti, Mirco, Stabili, Dario, Colajanni, Michele, Wool, Avishai

Research on the Enhanced ADAS Functions with Modular Design Based on 5G-V2X Technology

2020-01-502602/24/2020

This paper will mainly discuss the effect of the combination of the 5th generation wireless systems - Vehicle to Everything (5G-V2X) technology an Advanced Driver Assistance Systems (ADAS) functions. With the promotion and popularization of 5G technology with high bandwidth and bottom delay, V2X has been able to quickly and safely transmit more information to target vehicles in need in the field of automatic driving. Traditional ADAS functions development has been carried out for decades, but there are still many unsolvable problems in perception and decision-making. In this paper, V2X technology is introduced into the auxiliary driving functions of L0-L3 stage by using the idea of platform module design. On the basis of not redeveloping the original functions, the existing problems of perception and decision-making are improved. Through the experimental demonstration in this paper, this method can indeed save the development cost and shorten the development cycle.

Pingfan, Jin, Jiayi, Guan, Guoqi, Zhong

Connected Vehicles - An Ecosystem for Services

2019-28-244711/21/2019

This paper outlines the different aspects of the Connected Vehicle concept. The blocks required to implement a Connected Vehicle infrastructure is also discussed in detail. Two main types of short-range wireless communication are discussed in Connected Vehicles context namely Vehicle-to-Vehicle (V2V), and Vehicle-to-Infrastructure (V2I) communication. An overview of the evolution of the Connected Vehicle and its operational aspects are presented together with its application. The impacts and potential operational benefits of the Connected Vehicle are discussed. The various challenges to architect non-functional requirements in the case of Connected Vehicle technology are identified and discussed.

Venkataram, Prabha Baragur

V2X Standardization in Over-the-Air Solution

2019-28-243511/21/2019

Today in-vehicle software is growing significantly resulting into increase in importance of over-the-air software/firmware updates dramatically. Various suppliers are providing the update-over-the-air solution in the automotive sector. Due to limited standardization in solution, each supplier needs more customization for specific customer. This paper is to bring in the required standardization in V2X resulting into ‘vehicle on-board components’ as one solution to multiple customer. “Update over-the-air improved solution through various standardization resulting into ‘vehicle on-board components’ as the product”

Kumaraswamy, Pavithra

Data connectivity in HARSH ENVIRONMENTS

19TOFHP08_0308/01/2019

Ensuring high-speed data transmission requires OEM designers to think more about components, placement and the impact of environmental conditions early in design. Technology advances are increasingly bringing a new level of connectivity to industrial and commercial vehicles. Customers are demanding functionality that automates or enhances operational tasks to increase driver productivity and safety and, in many cases, also brings down total cost of ownership. Features such as automatic adaptive braking and steering, onboard diagnostics, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication and cameras that give the driver a 360-degree view of their environment are becoming basic customer requirements. These features require large amounts of data to be transmitted at high speeds. As engineers design new models to meet these customer demands, the challenge is to ensure signal integrity and data transmission in the harsh environment of the trucking and off-highway

Manko, Christian

Cooperative Collision Avoidance in a Connected Vehicle Environment

2019-01-048804/02/2019

Connected vehicle (CV) technology is among the most heavily researched areas in both the academia and industry. The vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to pedestrian (V2P) communication capabilities enable critical situational awareness. In some cases, these vehicle communication safety capabilities can overcome the shortcomings of other sensor safety capabilities because of external conditions such as 'No Line of Sight' (NLOS) or very harsh weather conditions. Connected vehicles will help cities and states reduce traffic congestion, improve fuel efficiency and improve the safety of the vehicles and pedestrians. On the road, cars will be able to communicate with one another, automatically transmitting data such as speed, position, and direction, and send alerts to each other if a crash seems imminent. The main focus of this paper is the implementation of Cooperative Collision Avoidance (CCA) for connected vehicles. It leverages the Vehicle to

Gelbal, Sukru Yaren, Zhu, Sheng, Anantharaman, Gokul Arvind, Aksun Guvenc, Bilin, Guvenc, Levent

A Framework for Vision-Based Lane Line Detection in Adverse Weather Conditions Using Vehicle-to-Infrastructure (V2I) Communication

2019-01-068404/02/2019

Lane line detection is a very critical element for Advanced Driver Assistance Systems (ADAS). Although, there has been significant amount of research dedicated to the detection and localization of lane lines in the past decade, there is still a gap in the robustness of the implemented systems. A major challenge to the existing lane line detection algorithms stems from coping with bad weather conditions (e.g. rain, snow, fog, haze, etc.). Snow offers an especially challenging environment, where lane marks and road boundaries are completely covered by snow. In these scenarios, on-board sensors such as cameras, LiDAR, and radars are of very limited benefit. In this research, the focus is on solving the problem of improving robustness of lane line detection in adverse weather conditions, especially snow. A framework is proposed that relies on using Vehicle-to-Infrastructure (V2I) communication to access reference images stored in the cloud. These reference images were captured at

Horani, Modar, Rawashdeh, Osamah

An Immersive Vehicle-in-the-Loop VR Platform for Evaluating Human-to-Autonomous Vehicle Interactions

2019-01-014304/02/2019

The deployment of autonomous vehicles in real-world scenarios requires thorough testing to ensure sufficient safety levels. Driving simulators have proven to be useful testbeds for assisted and autonomous driving functionalities but may fail to capture all the nuances of real-world conditions. In this paper, we present a snapshot of the design and evaluation using a Cooperative Adaptive Cruise Control application of virtual reality platform currently in development at our institution. The platform is designed so to: allow for incorporating live real-world driving data into the simulation, enabling Vehicle-in-the-Loop testing of autonomous driving behaviors and providing us with a useful mean to evaluate the human factor in the autonomous vehicle context.

Rastogi, Vibhor, Merco, Roberto, Kaur, Manveen, Rayamajhi, Anjan, Gavelli, Marco, Papa, Gianluca, Pisu, Pierluigi, Babu, Sabarish, Robb, Andrew, Martin, Jim

Intention Aware Motion Planning with Model Predictive Control in Highway Merge Scenario

2019-01-140203/25/2019

Human drivers navigate by continuously predicting the intent of road users and interacting with them. For safe autonomous driving, research about predicting future trajectory of vehicles and motion planning based on these predictions has drawn attention in recent years. Most of these studies, however, did not take into account driver’s intentions or any interdependence with other vehicles. In order to drive safely in real complex driving situations, it is essential to plan a path based on other driver’s intentions and simultaneously to estimate the intentions of other road user with different characteristics as human drivers do. We aim to tackle the above challenges on highway merge scenario where the intention of other road users should be understood. In this study, we propose an intention aware motion planning method using finite state machine and model predictive control without any vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communications. The key idea is to design

Kim, Hayoung, Kim, Dongchan, Huh, Kunsoo

Still Unsettled on Vehicle Connectivity Standard

19AVEP03_1003/01/2019

As data and data-sharing become more crucial to the transportation evolution, the auto sector has yet to gain consensus on the best connectivity format. As autonomous vehicles inch closer to reality, a diverse range of companies and public entities are exploring ways to maximize their positive impact on traffic flows and congestion. Communication at all levels, both between vehicles and between public and private interest groups, will be an important element for improving efficiency.

Costlow, Terry

Road Tested

19AVEP03_1103/01/2019

Transportation-infrastructure expert Kirk Steudle reflects on the rapid progress toward the connected-AV future and the challenges ahead. In the auto industry, mechanical and electrical engineers work from the tire up. Civil engineers work from the tire down,” quips Kirk Steudle. “And although it's taken a while for both to understand each other's jargon, the connected-and-autonomous vehicle is forcing them all together-to solve problems for society's mobility.” Steudle, a registered professional engineer, has been at the vehicle-to-road nexus his entire career. Last October he retired as director of the Michigan Dept. of Transportation where, among many achievements, his leadership helped put the state and its core industry in the vanguard of connected-car and AV-related developments, testing, and infrastructure standards. During his final year at MDoT, he also served as interim CEO of the American Center for Mobility, the new 500-acre AV proving ground and test center near Ann Arbor.

Brooke, Lindsay

Swarm Intelligence Based Algorithm for Management of Autonomous Vehicles on Arterials

2018-01-164608/07/2018

Connected and autonomous vehicles are different from traditional vehicles. The communication between vehicles (V2V) or between vehicles and infrastructures (V2I) renders it possible to convey traffic information (e.g. signal timing or speed advisory) from signal controllers to vehicles as well as vehicles to vehicles in real time. Taking this advantage, this paper aims to developing an algorithm which enables the interconnected autonomous vehicles running efficiently on arterials. A set of driving rules determining random behavior and swarm behavior of autonomous vehicles is developed based on swarm intelligence theory. Under control of these rules, each autonomous vehicle follows the same rules, which make it select target vehicle from all the optimal individuals in detection zone according to characteristics of itself, then approach to the target by changing lane, following former car, or accelerating. The result of simulation shows that this swarm algorithm enables an autonomous

Li, Lin, Hao, Ruochen, Ma, Wanjing, Qi, Xinzhou, Diao, Chenxue

Enhancing Driver Awareness Using See-Through Technology

2018-01-061104/03/2018

This paper presents a real-time application of see-through technology using computer vision (e.g., object detection) and Vehicle-to-X (V2X) communication (e.g., Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I)). Each access point (AP) was connected to Chattanooga’s fiber optics internet, supporting a data transfer rate up to 10-Gbps. Using a 5Ghz frequency, vehicular communications were set up with a seamless handover for transferring real-time data. Two web cameras acting as clients were mounted on the windshield of two of three vehicles to send image data to the offsite server. Using multi-threaded programming, both image feeds were processed simultaneously. Once the server received the images, it performed an object recognition algorithm on each image using a convolutional neural network (CNN). Post- identification, the images from the second vehicle were sent and overlaid dynamically to the third vehicle’s image. This repetitive overlapping of images allowed the third

Thompson, Rebekah L., HU, Zhen, Cho, Jin, Stovall, Jose, Sartipi, Mina

2021-12-29.TEST Visual Sensor Fusion and Data Sharing across Connected Vehicles for Active Safety

2018-01-0026

04/03/2018

The development of connected-vehicle technology, which includes vehicle-vehicle and vehicle-infrastructure communications, opens the door for unprecedented active safety and driver-enhanced systems. In addition to exchanging basic traffic messages among vehicles for safety applications, a significantly higher level of safety can be achieved when vehicles and designated infrastructure-locations share their sensor data. In this paper, we propose a new system where cameras installed on multiple vehicles and infrastructure-locations share and fuse their visual data and detected objects in real-time. The transmission of camera data and/or detected objects (e.g., pedestrians, vehicles, cyclists, etc.) can be accomplished by many communication methods. In particular, such communications can be accomplished using the emerging Dedicated Short-Range Communications (DSRC) technology. In our proposed system the vehicle receiving the visual data from an adjacent vehicle fuses the received visual

Al-Qassab, Hothaifa, Pang, Su, Al-Qizwini, Mohammed, Radha, Hayder

2021-12-29.TEST Validating Prototype Connected Vehicle-to-Infrastructure Safety Applications in Real- World Settings

2018-01-0025

04/03/2018

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan

Parikh, Jayendra, Kailas, Aravind, Adla, Rawa, Rajab, Samer, Ali, Mahdi, Vijaya Kumar, Vivek, Meier, Jan-Niklas, Sakakida, Masafumi, Goudy, Roy, Yoshida, Hiroyuki, Deering, Richard, Williams, Richard