ABSTRACT Northrop Grumman has developed a software and hardware solution to provide enhanced 360 degree local situational awareness (LSA) to enable the warfighter with an overmatch capability on today’s modern battlefield. The architecture exploits technological gains in cameras, video processing, and video compression. The approach allows rapid comprehension of local and remote situational views presented with operational relevance for a ground combat platform or tactical wheeled platform crew. The 360 Degree LSA approach provides direct visualization of relative positioning of targets, threats, and lines of fire; and additionally offers common situational understanding / operational picture from the dismounted soldier to higher echelon commands. The approach provides prioritized information through LSA software to provide an enhanced view to the warfighter whereas the squad leader becomes an integral part of the crew with a view of the common operating picture (mounted) and

Viscovich, Christopher, Geoghegan, Susan, Worthy, David

Design and Development of a Virtual Autonomous System

2022-01-507210/03/2022

An autonomous vehicle or a driverless vehicle is a ground vehicle that is capable of sensing its environment and moving safely with little to no human input. The present study aims to validate existing literature on vehicle following, emergency braking, lane changing, overtaking, and jerk trajectory with regard to autonomous vehicles. By using the jerk trajectory equation, we are able to optimize it by implementing a complete overtaking procedure. We are also able to compare the variation in both the dynamic and kinematic bicycle model for the same vehicle and traveling the same distance. A new kinematic bicycle model is built, which is more simple to construct. This project is performed using MATLAB and Simulink for creating and modifying the system blocks. There has also been an integration of 3D visualization software such as VR sink and Unreal Engine. We construct the vehicles by simple transfer functions, ACC and PID as the main system blocks for vehicles 1, 2, and 3, respectively

Narain, C.M., Patil, Sharanbassapa S.

Tire Track Identification: A Method for Drivable Region Detection in Conditions of Snow-Occluded Lane Lines

2022-01-007803/29/2022

Today’s advanced driver-assistance systems (ADAS) commonly utilize the camera sensor to provide the benefit of increased safety to the driver. This is done by using computer vision to detect two key environmental features: lane lines and objects (e.g., vehicles, pedestrians, bicycles). Lane detections are vital for safety features such as lane departure warnings, lane-keeping assist systems, and lane-centering systems. However, when subjected to adverse weather conditions, either heavy perception of rain or snow or occlusion of lane lines due to rain or snow, the lane detection algorithms are no longer capable of detecting the lane lines. Hence, the ADAS feature is no longer providing the benefit of increased safety to the driver. The performance of one of the leading computer vision system providers was tested in conditions of variable snow coverage on the road, causing occluded lane lines, using data collected in the 2020-2021 winter in Kalamazoo, Michigan. The results show that this

Goberville, Nicholas A., Kadav, Parth, Asher, Zachary D.

A humanized vehicle speed control to improve the acceptance of automated longitudinal control

2022-01-009703/29/2022

Vehicle speed controls, as adaptive cruise control and related automated evolutions, are control systems able to follow a desired vehicle reference speed that is set by the driver and fused with information as road signs, SD maps etc.. Current normal production systems don’t distinguish among the vehicle users, only some carmakers are doing first steps towards the introduction of learning from driver to adapt the traditional control. In our work, we follow up this content with a humanized speed control, based on learning of driver longitudinal behavior. This method is able to combine machine learning algorithms, vehicle positioning and recurrent trips into existing automated longitudinal control systems. Proposed algorithm can reduce the interactions between drivers and automated systems by improving the acceptance of automated longitudinal control. Furthermore, proposed integration works mainly on speed reference that dramatically simplifies the customization of the system. We present

Raffone, Enrico, Rei cEng, Claudio, Fossanetti, Massimo

Design and Validation of Energy-optimal Adaptive Cruise Control (EACC)

2022-01-050303/29/2022

The energy consumption of electric vehicles (EVs) is not only influenced by the efficiency of the powertrain components (battery, electric machines, inverters, etc.), but also to a large extend by the driving profile. Therefore, the new function of energy-optimal adaptive cruise control (EACC) is proposed as a new feature in this paper. This function exploits a large potential for energy consumption reduction by optimizing the EVs’ speed trajectory using model predictive control (MPC). EACC optimizes the speed profile of EVs by considering various connected driving information (speed limits, road gradients, predicted future behavior of the vehicle ahead, etc.). To validate the performance of EACC, a prototype system was implemented in an EV. The EV controlled by EACC was driven as the ego-vehicle on a test track. In the test cycles, which represent realistic urban driving scenarios, EACC reduces the energy consumption of the ego-vehicle by up to 13% in comparison to an ego-vehicle

Jia, Yanzhao, Abdelkarim, Anas, Klingbeil, Xiaonan, Görges, Daniel

Isolating the Influence of Road Grade and Curvature on Class-8 Truck Platoon Energy Efficiency

2022-01-006603/29/2022

Platooning heavy-duty trucks reduces aerodynamic drag for following trucks, reducing energy consumption and increasing both range and mileage. Previous platooning experimentation has demonstrated fuel economy benefits in two-, three-, and four-truck configurations. However, exogenous variables disturb the ability of these platoons to maintain the desired formation, causing an accordion effect within the platoon and subsequently reducing energy benefits via unnecessary acceleration/deceleration events. This phenomenon is increasingly exacerbated as platoon size and road grade variations increase. The current work assesses how platoon size, road curvature and road grade influence platoon energy efficiency. Fuel consumption rate is experimentally quantified for four heterogeneous Class 8 vehicles operating in standalone (baseline), two-, and four-truck platooning configurations to assess fuel consumption changes while driving through diverse road conditions under the command of a

Snitzer, Philip, Stegner, Evan, Siefert, Jan, Bevly, David M., Hoffman, Mark

Multi trucks platooning fuel economy test results with cooperative adaptive cruise control under real-world driving conditions

2022-01-050103/29/2022

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions for 3 trucks automation. As part of a U.S. Department of Energy Funding Opportunity Announcement award project, 3 trucks platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. On-highway testing is done on a route in Indiana representing the operation of long-haul Class 8 trucks in the United States. The road includes low, medium and high grade segments. The impact of road grade variation and traffic on truck platooning is analyzed and some of the issues with this technology are identified for further research and improvements.

Borhan, Hoseinali, Brady, Nathan, YU, Chia-Siung, Fuhs, Karla, Adi, Gayatri, Pattel, Bibin, Lammert, Michael

System Identification Techniques to Improve ADAS Feature Performance

2022-01-009303/29/2022

The advances in automotive technology continue to deliver safety and driving comfort benefits to the society. The Automated Driving Assistance System (ADAS) technology is at forefront of this evolution. Today, various vehicle models on the road have features like lane centering, automated emergency braking, adaptive cruise control, traffic jam assist etc. During early development, such feature algorithms often assume ideal environmental and vehicle conditions while doing performance evaluation. The lane centering ADAS feature performance in a test vehicle was studied. The feature considered here is an end-to-end feature, i.e., from camera sensor output to steering actuation. Lane centering control system often has multiple control loops within the vehicle system. The delay in steering system response has a significant effect on overall lane centering performance and driver feel. This study focuses on understanding effect of EPS behavior and vehicle lateral dynamics on overall ADAS

Awathe, Arpit, Varunjikar, Tejas, Ganguli, Subhabrata

Prediction of Lane Change on the Expressway Based on Logistic Regression

2021-01-703212/15/2021

In autonomous driving system, lane change decision-making plays an important role as the front-end of lateral control. However, the current prediction methods of lane change are typically performed by using basic variables as the features of model without deep processing, which reduces the accuracy of the prediction. Therefore, we propose a binary logistic regression method to solve the lane change decision problem under expressway conditions, which treat quantified willingness and risk as the inputs. Firstly, we design Lane Changing Willingness function and Lane Changing Risk function with the minimum safety spacing theory and traffic environment factors. Secondly, a binary logistic regression method for predicting lane change behavior is proposed. Thirdly, we develop the driving simulation platform with low latency data collecting tools and design the experiments. After training the model with the experiment data, the proposed method predicts the lane change decision with 94.02

Sun, Weiqi, Bai, Jie, Huang, Libo, Chang, Liang, Dong, Lianfei, Luo, Zhengang

A Comparative Study on Various Methodologies and Solutions for Evaluation of Short-Range Radar to Validate the Features of Autonomous Vehicle.

2021-26-046809/22/2021

Autonomous vehicle is a vehicle capable of sensing its environment and taking decisions automatically with no human interventions. To achieve this goal, ADAS (Advance Driving Assistance System) technologies play an important role and even today technologies are improving and emerging. The sensing of environment can be achieved with the help of sensors like Radar and Camera. Radar sensors are used in detecting the range, speed and directions of multiple targets using complex signal processing algorithms. Radar with long range and short range are widely used in the autonomous vehicles. Radar sensors with long range can be used to realize features like Adaptive Cruise Control, Advance Emergency Brake Assist. The short-range radar sensors are used for Blind Spot Monitoring, Lane Change Assist, Rear Pre-Crash System, Rear Cross Traffic Alert, Occupant safe exist, Trailer Merge Assist and Front Cross Traffic Alert. To realize the Autonomous Vehicle functionalities four short range radar

Sujeendra, M R, Kesana, Sindhu Prabha, Saddaladinne, Jagadeesh Babu

Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

2021-01-006404/06/2021

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad

Adam, Cristian, Lakshmanan, Sridhar, Richardson, Paul, Stegner, Evan, Ward, Jacob, Hoffman, Mark, Bevly, David M.

Simulation Study to Evaluate Robustness of the Lane Centering Feature

2021-01-010904/06/2021

The advances in automotive technology continue to deliver safety and driving comfort benefits to the society. The Automated Driving Assistance System (ADAS) technology is at the forefront of this evolution. Today, various vehicle models on the road have features like lane keeping assist, lane centering, automated emergency braking, adaptive cruise control, traffic jam assist etc. During early development, such feature algorithms often assume ideal environmental and vehicle conditions while doing a performance evaluation. This study focuses on the use of simulation platform to evaluate robustness of the lane centering ADAS feature in presence of various factor variations. The feature considered here is an end-to-end feature, i.e., from camera sensor output to steering actuation. The use of closed-loop simulation tools is well recognized in automotive industry for early requirements validation as well as robustness study. However, it has been traditionally used mainly for vehicle

Varunjikar, Tejas, Awathe, Arpit, Kushwaha, Pushpendra, Chen, Chao

Coalesce of Artificial Intelligence into ADAS Hardware-In-the-Loop Testing

2021-01-019304/06/2021

Automotive industry is inclined towards connected, comfortable, environment friendly, efficient and smarter systems. Advanced Driver Assist System (ADAS) technology assist drivers to achieve a safer as well as better ride by automation and improvisation of the vehicular systems. With the advent of ADAS system, there is a significant focus not only in the development of Electronic Control Units (ECUs) and its features to cater to the emerging market but also on the information that could be displayed to meet the functional as well as safety requirements. This ADAS information display ensures timely notification to the driver with unique alerts that can be acoustic or visual. These systems should be tested thoroughly to ensure reliability as failures may impose severe risk on the OEM. Hardware in the loop testing has been largely adopted by industry against manual testing in lieu of the testing constraints imposed by the latter. This paper discusses on the existing test methods for ADAS

Krishnamoorthy, Bharathi, Nammalwar, Giri, Wulf, Torsten, Pazhur, Nandini

Research on Parallel Regenerative Braking Control of the Electric Commercial Vehicle Based on Fuzzy Logic

2021-01-011904/06/2021

Regenerative braking is an effective technology to extend the driving range of electrified vehicles by recovering kinetic energy from braking. This paper focuses on the design of the regenerative braking control strategy for a commercial vehicle which requires significantly larger braking power than passenger cars. To maximize the energy recovery while ensuring the braking efficiency of the vehicle and its braking safety, this paper proposed a fuzzy logic strategy for regenerative braking control, and a feasibility study was conducted for an electric van. The work includes in three steps. Firstly, state variables that significantly affect regenerative braking performance, i.e., vehicle speed, battery State-of-Charge (SOC), and braking intensity, are identified based on mathematical modelling of the vehicle system dynamics in braking maneuver. With the three state variables as control inputs, the fuzzy logic controller is then developed to allocate the required braking force to the

Ye, Meng, Tan, Gangfeng, Lei, Fushou, Chen, Kailang, Feng, Jiaming, Zhao, Feng‘an

Traxen ‘trains’ AI-based adaptive cruise control for heavy trucks

21TOFHP02_0602/01/2021

Artificial intelligence (AI), high-definition maps, and advanced algorithms and sensors combine to enable Traxen's intelligent adaptive cruise control (ACC) system for commercial vehicles, iQ-Cruise, to reduce fuel consumption by an average of 10% on customer routes. Piloted by several fleet customers, the system becomes available to the commercial-vehicle aftermarket in the first quarter of 2021, followed by OE truck manufacturers in the next 24 months. “We are increasing the trucking industry's profit margins by 50%,” said Ali Maleki, founder and CEO of Traxen, a Plymouth, Michigan-based technology startup that's been developing and testing the system for the past two years, logging more than 1.5 million miles of data from customers' trucks. “With fuel cost being one of the top operating costs for fleets worldwide, delivering a solution like iQ-Cruise that offers a 10% fuel efficiency improvement on average is a remarkable feat for the industry.”

Gehm, Ryan

Ford expands EV lineup with E-Transit cargo van

20TOFHP12_1012/01/2020

Ford revealed on November 12 its next fully electric vehicle (EV), the 2022 E-Transit cargo van, with the automaker's new president and CEO Jim Farley stating, “The transition of fleet vehicles to zero emissions, especially for the fast-growing last-mile delivery segment, is critical to achieve our carbon neutrality goal by 2050. We're standing with California for higher standards, lower emissions and cleaner air. And we're proud to support and live up to the Paris Agreement.” Farley and Ford expect the global demand for full-size vans to grow another one-third by the end of this decade. That includes a potential market for more than 1.1 million full-size, fully electric and connected commercial vehicles worldwide, Farley said during the virtual product launch.

Gehm, Ryan

AV and ADAS Testing from Out of the Box

20AVEP11_1011/01/2020

A new tool from Foretellix guides engineers through virtual systems testing to minimize the risk of getting dangerous predeployment bugs. For self-driving vehicle systems to gain the full confidence of the public, the mobility industry and government regulators, OEMs have to prove that AVs (and those equipped with enhanced SAE Level 2 automated-driving systems) are safer being driven by software than by humans. But a recent string of unfortunate events in 2020 involving automatic emergency braking (AEB) systems is causing concerns. Early in the year, Volvo recalled 750,000 cars from 2019 and 2020 production over a fault in its AEB. Engineers discovered a software glitch that prohibited the system from activating under certain temperatures. Then in June, in Taiwan, a Tesla Model 3 operating in Autopilot mode slammed into an overturned tractor-trailer rig at 70 mph, reportedly due to software issues related to the car's forward-facing sensor array and an AEB that failed to react. This

Brooke, Lindsay

Candidate Improvements to Dedicated Short Range Communications (DSRC) Message Set Dictionary [SAE J2735] Using Systems Engineering Methods

J3067_202010 (Current)

10/06/2020

This document is not a standard, it is a candidate for a standard being submitted to SAE for their consideration as a comment to SAE J2735. The term SAE J2735 SE candidate is used within this document to refer to this submission. This document specifies dialogs, messages, and the data frames and data elements that make up the messages specifically for use by applications intended to utilize the 5.9 GHz Dedicated Short Range Communications for Wireless Access in Vehicular Environments (DSRC/WAVE, referenced in this document simply as “DSRC"), communications systems. Although the scope of this Standard is focused on DSRC, these dialogs, messages, data frames and data elements have been designed, to the extent possible, to be of use for applications that may be deployed in conjunction with other wireless communications technologies. This standard therefore specifies the definitive message structure and provides sufficient background information to allow readers to properly interpret the

V2X Communications Steering Committee

Reconstructing Accidents in the ADAS Age

20AVEP09_0909/01/2020

Data access and privacy concerns will be key challenges to determine ADAS-influencing factors, according to an SAE WCX Digital Summit expert panel. With advanced driver-assist systems (ADAS) evolving rapidly, the technology will continue to improve safety as it augments the skill and attention of human drivers. Accidents will still occur, however, and when they do, determining fault and failures will become more complex when a range of electronic sentinels are involved. A panel discussion during SAE's 2020 WCX Digital Summit [www.sae.org/attend/virtual-events/wcx-digital-summit] brought together experts in the accident reconstruction field to discuss how ADAS might influence the determining factors contributing to a crash. Moderated by Origin Forensics' principal Jarrod Carter, the “Accident Reconstruction in an ADAS Future” panel speakers included: Edward Fatzinger, forensic engineer, Momentum Engineering Corp.; Eldon Leaphart, principal engineer, Carr Engineering Inc.; Alan Moore

Seredynski, Paul

Unsettled Issues Facing Automated Vehicles and Insurance

EPR202001508/05/2020

This SAE EDGE™ Research Report explores how the deployment of automated vehicles (AVs) will affect the insurance industry and the principles of liability that underly the structure of insurance in the US. As we trade human drivers for suites of sensors and computers, who (or what) is responsible when there is a crash? The owner of the vehicle? The automaker that built it? The programmer that wrote the code?Insurers have over 100 years of experience and data covering human drivers, but with only a few years’ worth of information on AVs – how can they properly predict the true risks associated with their deployment? Without an understanding of the nature and risks of AVs, how can the government agencies that regulate the insurance industry provide proper oversight? Do the challenges AVs present require a total reworking of our insurance and liability systems, or can our current structures be adapted to fit them with minor modifications?{"bold":"Unsettled Legal Issues Facing Automated

Williams, Ian

Development of Design and Engineering Recommendations for In-Vehicle Alphanumeric Messages

J2831_202007 (Current)

07/29/2020

This Information Report provides recommendations for alphanumeric messages that are supplied to the vehicle by external (e.g., RDS, satellite radio) or internal (e.g., infotainment system) sources while the vehicle is in-motion. Information/design recommendations contained in this report apply to OEM (embedded) and aftermarket systems. Ergonomic issues with regard to display characteristics (e.g., viewing angle, brightness, contrast, font design, etc.) should review ISO 15008.

Driver Vehicle Interface (DVI) Committee

Development of Design and Engineering Recommendations for In-Vehicle Alphanumeric Messages

J2831_202007-TEST-REC (Historical)07/29/2020

Driver Vehicle Interface (DVI) Committee

WHAT WE'RE DRIVING

20AUTP08_0707/01/2020

Before I started a drive in the 2020 Mazda3, I had to toggle the drive-select to “sport.” And release the parking brake. Each and every time. At least the two switches are in proximity on the center console. But this annoyance mars the generally good experience of the Mazda3 (all-new in 2019) and once again suggests it's a refreshing but occasionally cockeyed prism through which Mazda engineers and planners view the world.

Radar Death Star

20AVEP07_0607/01/2020

Lunewave radar's 3D-printed spherical antenna makes for fast, 360-degree single-snapshot readings that are claimed to beat the slower sweeps of conventional radar. Radar sensing has been used for various functions in passenger vehicles for more than two decades. Like all sensors intended an automated vehicle (AV), radar has strengths and weaknesses. It's good at detecting objects from long distances of a couple hundred meters or more, even in bad weather. And it has a low cost, which depending on quality and scale of production is between about $50 to a few hundred dollars per unit. But the relatively inexpensive, planar, phased-array radar antennas commonly used for functions like adaptive cruise control don't have the resolution needed for higher levels of automated functions, some experts believe. That shortcoming motivated Hao and John Xin, the brother co-founders of Lunewave, to commercialize a spherical radar antenna based on the Luneburg lens design created three-quarters of a

Berman, Bradley

Radar's Evolving Role in ADAS and the AV Future

20AVEP05_0405/01/2020

The automotive radar sensor market is growing at a 21% compound annual growth rate, putting greater demands on chip design, testing, and module deployment. Until recently, various vehicle OEMs were vying to be first to put self-driving cars on the road by the magical turn of the decade. But as 2020 arrived, the bullish tone has switched to a more cautionary outlook. While the truly self-driving SAE Level 5 autonomous vehicle (AV) without a steering wheel is still years away, innovations needed to support the intelligent self-driving car of the future continue to emerge and improve. Developers grapple with the need to comply with safety and security standards as the average car sees more sensor technology connecting it with onboard devices as well as with its environment. Within the increasingly capable sensor suite (see table), automotive radar is now an indispensable technology that enables sub-systems for advanced driver assistance systems (ADAS).

Kundi, Rick

Utilization of Vehicle Connectivity for Improved Energy Consumption of a Speed Harmonized Cohort of Vehicles

2020-01-058704/14/2020

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements. The basis of this study is a precursor to developing a connected vehicle

Morgan, Christopher, Robinette, Darrell, Santhosh, Pruthwiraj, Bloom-Edmonds, John

Experimental Evaluation of Longitudinal Control for Automated Vehicles through Vehicle-in-the-Loop Testing

2020-01-071404/14/2020

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment. Details associated with applying the proposed VIL for testing adaptive cruise control (ACC), in conjunction with approaches for creating a virtual lead vehicle, as well as results of energy consumption analysis for a 2017 Toyota Prime with stock and improved longitudinal control algorithm, are

Di Russo, Miriam, Iliev, Simeon, Stutenberg, Kevin M., Ku, Jerry, Rask, Eric

Creating Driving Scenarios from Recorded Vehicle Data for Validating Lane Centering System in Highway Traffic

2020-01-071804/14/2020

The adoption of simulation is critical to reducing development time and enhancing system robustness for Advanced Driver Assistance Systems (ADAS). Automotive companies typically have an abundance of real data recorded from a vehicle which is suitable for open-loop simulations. However, recorded data is often not suitable to test closed-loop control systems since the recorded data cannot react to changes in vehicle movement. This paper introduces a methodology to create virtual driving scenarios from recorded vehicle data to enable closed-loop simulation. This methodology is applied to test a lane centering application. A lane centering application helps a driver control steering to stay in the current lane and control acceleration and braking to maintain a set speed or to follow a preceding vehicle. The driver’s vehicle is referred to as the ego vehicle. Other vehicles on the road are referred to as target vehicles. To test the lane centering system in simulation, engineers must model

Park, Seo-Wook, Patil, Kunal, Wilson, Will, Corless, Mark, Choi, Gabriel, Adam, Paul

Reference Test System for Machine Vision Used for ADAS Functions

2020-01-009604/14/2020

Advanced Driver Assistance Systems (ADAS) like Lane Departure Warning (LDW) and Lane Keep Assist (LKA) have been available for several years now but has experienced low customer acceptance and market penetration. These deficiencies can be traced to the inability of many of the perception systems to consistently recognize lane markings and localize the vehicle with respect to the lane markings in the real-world with poor markings, changing weather conditions and occlusions. Currently, there is no available standard or benchmark to evaluate the quality of either the lane markings or the perception algorithms. This work seeks to establish a reference test system that could be used by transportation agencies to evaluate the quality of their markings to support ADAS functions that rely on pavement markings. The test system can also be used by designers as a benchmark for their proprietary systems. To support this development, an extensive video dataset was collected at different times of

Nayak, Abhishek, Rathinam, Sivakumar, Pike, Adam, Gopalswamy, Swaminathan

Perceptions of Two Unique Lane Centering Systems: An FOT Interview Analysis

2020-01-010804/14/2020

The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance. Perceptions of adaptive cruise control (ACC) were similar across vehicles

Landry, Steven, Seppelt, Bobbie, Russo, Luca, Mehler, Bruce, Angell, Linda, Gershon, Pnina, Reimer, Bryan

Vehicle Trajectory Prediction Based on Motion Model and Maneuver Model Fusion with Interactive Multiple Models

2020-01-011204/14/2020

Safety is the cornerstone for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Systems (ADS). To assess the safety of a traffic situation, it is essential to predict motion states of traffic participants in the future with mathematic models. Accurate vehicle trajectory prediction is an important prerequisite for reasonable traffic situation risk assessment and appropriate decision making. Vehicle trajectory prediction methods can be generally divided into motion model based methods and maneuver model based methods. Vehicle trajectory prediction based on motion models can be accurate and reliable only in the short term. While vehicle trajectory prediction based on maneuver models present more satisfactory performance in the long term, these maneuver models rely on machine learning methods. Abundant data should be collected to train the maneuver recognition model, which increases complexity and lowers real-time performance. In this paper, a vehicle trajectory prediction

Xiao, Wei, Zhang, Lijun, Meng, Dejian

Prevention of Snow Accretion on Camera Lenses of Autonomous Vehicles

2020-01-010504/14/2020

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses. In the experiments, snow is formed using a novel snow gun inside a walk-in cold room connected to a

Mohammadian, Behrouz, Sarayloo, Mehdi, Heil, Jamie, Sojoudi, Hossein, Robertson, Michael, Hong, Haiping, Tran, Tommy, Patil, Sunil, Krishnan, Venkatesh

Scenario Analysis and Control Comparison for a High Speed Autonomous Vehicle

2020-01-071004/14/2020

This paper studies the simulation and control of an autonomous dragster. Four scenarios are provided that are critical to vehicle and driver safety in drag racing. Equations are then created to model the behavior during these safety scenarios. The use of a kinematic bicycle model and a Newtonian wheel stand model are discussed for plane-of-motion and out-of-plane vehicle movement, respectively. A separate controller is designed for each model by comparing different control methods. Proportional-Integral-Derivative (PID) control, optimal control, and model predictive control (MPC) are presented and applied to the models. The models are simulated from a speed of 75 m/s, being the estimated top speed of the research vehicle, up to a top speed of 150.5 m/s which is in alignment with the highest recorded speed of a dragster. The comparison of the control techniques yields MPC as superior for the bicycle model and PID as sufficient for the wheel stand model. Latency of the system is also

Donikian, Vatche, Bell, Joseph, Washington, Gregory

Robust Sensor Fused Object Detection Using Convolutional Neural Networks for Autonomous Vehicles

2020-01-010004/14/2020

Environmental perception is considered an essential module for autonomous driving and Advanced Driver Assistance System (ADAS). Recently, deep Convolutional Neural Networks (CNNs) have become the State-of-the-Art with many different architectures in various object detection problems. However, performances of existing CNNs have been dropping when detecting small objects at a large distance. To deploy any environmental perception system in real world applications, it is important that the system achieves high accuracy regardless of the size of the object, distance, and weather conditions. In this paper, a robust sensor fused object detection system is proposed by utilizing the advantages of both vision and automotive radar sensors. The proposed system consists of three major components: 1) the Coordinate Conversion module, 2) Multi level-Sensor Fusion Detection (MSFD) system, and 3) Temporal Correlation filtering module. The proposed MSFD system employs the principles of artificial

Park, Jungme, Jayachandran Raguraman, Sriram, Aslam, Aakif, Gotadki, Shruti

Optimal Yaw Rate Control for Over-Actuated Vehicles

2020-01-100204/14/2020

As we are heading towards autonomous vehicles, additional driver assistance systems are being added. The vehicle motion is automated step by step to ensure passengers’ safety and comfort, while still preserving vehicle performance. However, simultaneous activations of concurrent systems may conflict, and non-suitable behavior may emerge. Our research work consists in proving that with the right coordination approach, simultaneous operation of different systems improve the vehicle’s performance and avoid the emergence of unwanted conflicts. To prove this, we gathered different control architectures implemented in commercial passenger cars, and we compared them with our control architecture using a unified reference vehicle model. The high-fidelity vehicle model is developed in Simcenter Amesim in a modular and extensible manner. This enables adding systems in a plug-and-play way. Not only different control architectures can be tested on the same vehicle, but also different systems

Kissai, Moad, Monsuez, Bruno, Mouton, Xavier, Martinez, Didier, Tapus, Adriana

A Stability-Guaranteed Time-Delay Range for Feedback Control of Autonomous Vehicles

2020-01-009004/14/2020

The vehicles with level-5 autonomy (L5AVs) that have no human driver in the loop are also known as self-driving cars. L5AVs are assumed the next generation of ground transportation, which have growing attention from both industry and academia in most recent years. Most of the work related to feedback strategies of L5AVs are on developing mapping systems through a variety of sensors. These systems can be considered as an analogue to the perception and central nervous system of human drivers. For instance, innovative visualization systems are more powerful when compared to the visual perception system of a person, yet, mapping demands high computation loads. This burden causes delay in the feedback loop and thus, it might have an unfavorable influence on proper and safe control action. This study investigates the effect of time delay occurring in mapping systems on the stability of the controlled vehicle. An algorithm entitled as “Cluster Treatment of Characteristic Roots - CTCR” is used

Kirli, Ahmet, Arslan, Mehmet Selçuk

Impact of Automated Lane Change Assist on Energy Consumption

2020-01-008204/14/2020

This paper models adaptive cruise control combined with automated lane change assist to investigate the energy consumption improvements that such a system may provide compared to conventional adaptive cruise control. Automatically executing a lane change may improve efficiency, for example, when following a vehicle that is slowing to make a turn. Changing lanes while maintaining speed is hypothesized to be more efficient than staying in the same lane as the turning vehicle and reducing speed. The differences in such scenarios are simulated in a virtual environment using a cuboid model with idealized sensors. The ego-vehicle detects scenarios and performs a lane change to reduce or eliminate required speed changes. The results of the simulations compare the energy content of the resulting drive cycle as an idealized method to measure energy consumption for each cruise control strategy. The simulations consider traffic laws, such as turn signal requirements that may dictate the distance

Troxler, Casey, Currier, Patrick, Reinholtz, Charles

Effects of Training on Learning and Use of an Adaptive Cruise Control System

2020-01-103304/14/2020

This study examined the effects of formalized training on driver behavior and understanding of an adaptive cruise control (ACC) system with drivers experienced with ACC. Sixteen participants drove an ACC-equipped vehicle while following a lead vehicle around a test track. Participants completed three laps, each involving different lead vehicle behaviors, such as making a lane change or stopping at a red light, that test the limitations and capabilities of ACC (i.e., boundary conditions) of the subject ACC system. Immediately before driving, half of the participants watched a training video describing how the ACC system would respond to these lead vehicle behaviors. Participants’ knowledge of the ACC system limitations was assessed by a pre- and post-test questionnaire, and participants’ interactions with the ACC system - including braking behavior, other pedal movements, and actuation of ACC via steering wheel controls - were recorded by video cameras. We did not observe differences in

Krake, Audra, Jonas, Rachel, Hoyos, Christian, Crump, Caroline, Lester, Benjamin, Cades, David, Harrington, Ryan

Impact of Mixed Traffic on the Energy Savings of a Truck Platoon

2020-01-067904/14/2020

A two-truck platooning system was tested on a closed test track in a variety of realistic traffic and transient operating scenarios - conditions that truck platoons are likely to face on real highways. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate, serving as proxies to evaluate the impact of aerodynamic drag-reduction under constant-speed conditions. These measurements demonstrate the effects of: cut-in and cut-out maneuvers by other vehicles, transient traffic, the use of mismatched platooned vehicles (van trailer mixed with flatbed trailer), platoon following another truck with adaptive cruise control (ACC) and the presence of a multiple-passenger-vehicle pattern ahead of and adjacent to the platoon. These scenarios are intended to address the possibility of “background aerodynamic platooning” impacting realized savings on public roads. Using calibrated J1939 fuel rate

McAuliffe, Brian, Raeesi, Arash, Lammert, Michael, Smith, Patrick, Hoffman, Mark, Bevly, David

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

GM deploying electricals of the future

20AUTP03_0803/01/2020

In tandem with its corporate strategy to “skip” vehicle hybridization and focus solely on electric vehicles (EVs) for future propulsion (see cover story), General Motors recently offered media a deeper look at the company's all-new vehicle electrical architecture that was first confirmed in mid-2019, saying the vehicle-wide electrical system is associated with more than 100 new patents. The advanced “digital vehicle platform,” known internally as Global B, debuted with the 2020 Cadillac CT5 sedan. It serves as the electrical foundation for the 2020 Chevrolet Corvette Stingray and the 2021 Chevrolet Tahoe and Suburban, GM Yukon and Cadillac Escalade and will carry into all of the company's future conventionally-powered and EV models.

Visnic, Bill

Model Predictive Automatic Lane Change Control for Intelligent Vehicles

2020-01-502502/24/2020

As a basic link of driving behavior in urban roads, vehicle lane changing has a significant impact on traffic flow characteristics and traffic safety, and the automation of lane change is also a key issue to be solved in the field of intelligent driving. In this paper, the research on the automatic lane change control for intelligent vehicles is carried out. The main work is to build the overall structure of the vehicle's automatic lane change behavior, of which the planning and tracking are focused. The strategy of Constant Time Headway (CTH) is used in the lane change decision. The lane change trajectory adopts the model of constant velocity offset plus sine function, and the longitudinal displacement is determined by the vehicle speed when changing lanes. Model Predictive Control (MPC) theory is used to track the trajectory, which optimizes tracking accuracy and vehicle stability and constrains the range and rate of change of vehicle speed and steering angle. By using weighted

Meng, Ren, Guangqiang, Wu, Xunjie, Chen, Xuyang, Liu

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

Tier 1s tout newest mobility tech at CES 2020

20AUTP02_0901/01/2020

The mammoth annual techfest formerly known as the Consumer Electronics Show has become a must-attend for the mobility industry, with dozens of displays by OEMs and suppliers of all dimensions. At this year's CES, Automotive Engineering was impressed by new developments in ADAS and AV sensing and processing, V2X connectivity, vehicle cabin sensing and related technologies, electrification advances and a number of vehicle introductions. Highlights of our reporting include:

Brooke, Lindsay

Unsettled Topics Concerning Automated Driving Systems and the Transportation Ecosystem

EPR2019005

11/05/2019

Over the last 100 years, the automobile has become integrated in a fundamental way into the broader economy. A broad and deep ecosystem has emerged, and critical components of this ecosystem include insurance, after-market services, automobile retail sales, automobile lending, energy suppliers (e.g., gas stations), medical services, advertising, lawyers, banking, public planners, and law enforcement. These components - which together represent almost $2 trillion of the U.S. economy - are in equilibrium based on the current capabilities of automotive technology. However, the advent of autonomous vehicles (AVs) and technologies like electrification have the potential to significantly disrupt the automotive ecosystem. The critical cog governing the rate and pace of this shift is the management of the test and verification of AVs. In this SAE EDGE™ report, six senior industry leaders in the impacted ecosystems essay articles which describe sectors of the current automotive ecosystem and

Razdan, Rahul

Study on Comprehensive Evaluation Index of Front Collision Hazard of Intelligent Vehicle

2019-01-504411/04/2019

Collision avoidance technology is one of the key areas in the longitudinal safety research of intelligent vehicles. For the research of collision avoidance system, the existing methods usually use the evaluation index based on time interval or braking process to carry out risk assessment. In order to overcome the shortcomings of the formulas for describing the longitudinal hazard degree established in most studies, such as great differences, inconsistent standards and weak normalization, a comprehensive evaluation method for the longitudinal hazard in front-impact scenarios is established. This method takes into account both the analysis of time interval and braking process, and considers the non-linear variation of the longitudinal hazard degree with the real-time distance and speed of two vehicles. It can describe the longitudinal hazard degree of vehicles in dangerous traffic scenarios. Compared with the existing longitudinal hazard assessment methods, the effectiveness and

Jiaxiang, Qin, Zhang, Sumin, Weiwen, Deng, Rui, He

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