Refine Your Search

Topic

Search Results

Technical Paper

Wireless Charging for EV/HEV with Prescriptive Analytics, Machine Learning, Cybersecurity and Blockchain Technology: Ongoing and Future Trends

2019-04-02
2019-01-0790
Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy.
Technical Paper

Intelligent Vehicle Monitoring for Safety and Security

2019-04-02
2019-01-0129
The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.
Technical Paper

Secure Vehicular Communication Using Blockchain Technology

2020-04-14
2020-01-0722
Also, all the existing methods for vehicular communication rely on a centralized server which itself invite massive cyber-security threats. These threats and challenges can be addressed by using the Blockchain (BC) technology, where each transaction is logged in a decentralized immutable BC ledger.
Technical Paper

Securing Connected Vehicles End to End

2014-04-01
2014-01-0300
As vehicles become increasingly connected with the external world, they face a growing range of security vulnerabilities. Researchers, hobbyists, and hackers have compromised security keys used by vehicles' electronic control units (ECUs), modified ECU software, and hacked wireless transmissions from vehicle key fobs and tire monitoring sensors. Malware can infect vehicles through Internet connectivity, onboard diagnostic interfaces, devices tethered wirelessly or physically to the vehicle, malware-infected aftermarket devices or spare parts, and onboard Wi-Fi hotspot. Once vehicles are interconnected, compromised vehicles can also be used to attack the connected transportation system and other vehicles. Securing connected vehicles impose a range of unique new challenges. This paper describes some of these unique challenges and presents an end-to-end cloud-assisted connected vehicle security framework that can address these challenges.
Technical Paper

Trust-Based Control and Scheduling for UGV Platoon under Cyber Attacks

2019-04-02
2019-01-1077
Unmanned ground vehicles (UGVs) may encounter difficulties accommodating environmental uncertainties and system degradations during harsh conditions. However, human experience and onboard intelligence can may help mitigate such cases. Unfortunately, human operators have cognition limits when directly supervising multiple UGVs. Ideally, an automated decision aid can be designed that empowers the human operator to supervise the UGVs. In this paper, we consider a connected UGV platoon under cyber attacks that may disrupt safety and degrade performance. An observer-based resilient control strategy is designed to mitigate the effects of vehicle-to-vehicle (V2V) cyber attacks. In addition, each UGV generates both internal and external evaluations based on the platoons performance metrics. A cloud-based trust-based information management system collects these evaluations to detect abnormal UGV platoon behaviors.
Journal Article

A Novel Assessment and Administration Method of Autonomous Vehicle

2020-04-14
2020-01-0708
As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.
Journal Article

Towards a Cyber Assurance Testbed for Heavy Vehicle Electronic Controls

2016-09-27
2016-01-8142
Cyber assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. Many cyber security experts and analysts are used to working with traditional information technology (IT) networks and are familiar with a set of technologies that may not be directly useful in the commercial vehicle sector. To help connect security researchers to heavy trucks, a remotely accessible testbed has been prototyped for experimentation with security methodologies and techniques to evaluate and improve on existing technologies, as well as developing domain-specific technologies. The testbed relies on embedded Linux-based node controllers that can simulate the sensor inputs to various heavy vehicle electronic control units (ECUs). The node controller also monitors and affects the flow of network information between the ECUs and the vehicle communications backbone.
Technical Paper

Evaluating Trajectory Privacy in Autonomous Vehicular Communications

2019-04-02
2019-01-0487
Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.
Technical Paper

Securing J1939 Communications Using Strong Encryption with FIPS 140-2

2017-03-28
2017-01-0020
Since 2001, all sensitive information of U.S. Federal Agencies has been protected by strong encryption mandated by the Federal Information Processing Standards (FIPS) 140-2 Security Requirements. The requirements specify a formal certification process. The process ensures that validated encryption modules have implemented the standard, and have passed a rigorous testing and review processes. Today, this same strong security protection has become possible for vehicle networks using modern, cost-effective encryption in hardware. This paper introduces the motivation and context for the encryption diagnostics security in terms of all vehicles in general, not just trucks which use SAE J1939 communications. Several practical scenarios for using such encryption hardware and the advantages of using hardware compared to software private-key encryption and public-key encryption are described.
Technical Paper

Transformational Technologies Reshaping Transportation - An Academia Perspective

2019-10-14
2019-01-2620
This paper and the associated lecture present an overview of technology trends and of market and business opportunities created by technology, as well as of the challenges posed by environmental and economic considerations. Commercial vehicles are one of the engines of our economy. Moving goods and people efficiently and economically is a key to continued industrial development and to strong employment. Trucks are responsible for nearly 70% of the movement of goods in the USA (by value) and represent approximately 300 billion of the 3.21 trillion annual vehicle miles travelled by all vehicles in the USA while public transit enables mobility and access to jobs for millions of people, with over 10 billion trips annually in the USA creating and sustaining employment opportunities.
Technical Paper

Foreseeable Misuse in Automated Driving Vehicles - The Human Factor in Fatal Accidents of Complex Automation

2017-03-28
2017-01-0059
Today, highly automated driving is paving the road for full autonomy. Highly automated vehicles can monitor the environment and make decisions more accurately and faster than humans to create safer driving conditions while ultimately achieving full automation to relieve the driver completely from participating in driving. As much as this transition from advanced driving assistance systems to fully automated driving will create frontiers for re-designing the in-vehicle experience for customers, it will continue to pose significant challenges for the industry as it did in the past and does so today. As we transfer more responsibility, functionality and control from human to machine, technologies become more complex, less transparent and making constant safe-guarding a challenge. With automation, potential misuse and insufficient system safety design are important factors that can cause fatal accidents, such as in TESLA autopilot incident.
Research Report

Unsettled Impacts of Integrating Automated Electric Vehicles into a Mobility-as-a-Service Ecosystem and Effects on Traditional Transportation and Ownership

2019-12-20
EPR2019004
The current business model of the automotive industry is based on individual car ownership, yet new ridesharing companies such as Uber and Lyft are well capitalized to invest in large, commercially operated, on-demand mobility service vehicle fleets. Car manufacturers like Tesla want to incorporate personal car owners into part-time fleet operation by utilizing the company’s fleet service. These robotaxi fleets can be operated profitably when the technology works in a reliable manner and regulators allow driverless operation. Although Mobility-as-a-Service (MaaS) models of private and commercial vehicle fleets can complement public transportation models, they may contribute to lower public transportation ridership and thus higher subsidies per ride. This can lead to inefficiencies in the utilization of existing public transportation infrastructure.
Technical Paper

Experimental Setup Enabling Self-Confrontation Interviews for Modelling Naturalistic Driving Behavior

2019-04-02
2019-01-1082
Behavioral models of traffic actors have a potential of unlocking sophisticated safety features and mitigating several challenges of urban automated driving. Intuitively, volunteers driving on routes of daily commuting in their private vehicles are the preferred source of information to be captured by data collection system. Such dataset can then serve as a basis for identifying efficient methods of context representation and parameterization of behavioral models. This paper describes the experimental setup supporting the development of driver behavioral models within the SIMUSAFE project. In particular, the paper presents an IoT data acquisition and analysis infrastructure supporting self-confrontation interviews with drivers. The proposed retrofit system was installed in private vehicles of volunteers in two European cities. Wherever possible, the setup used open source software and electronic components available on consumer market.
Research Report

Unsettled Topics Concerning Automated Driving Systems and the Development Ecosystem

2020-03-17
EPR2020004
With over 100 years of operation, the current automobile industry has settled into an equilibrium with the development of methodologies, regulations, and processes for improving safety. In addition, a nearly $2-trillion market operates in the automotive ecosystem with connections into fields ranging from insurance to advertising. Enabling this ecosystem is a well-honed, tiered supply chain and an established development environment. Autonomous vehicle (AV) technology is a leap forward for the existing automotive industry; now the automobile is expected to manage perception and decision-making tasks. The safety technologies associated with these tasks were presented in an earlier SAE EDGE™ Research Report, “Unsettled Technology Areas in Autonomous Vehicle Test and Validation.”
Technical Paper

Buckendale Lecture Series: Transformational Technologies Reshaping Transportation—A Government Perspective

2018-09-01
2018-01-2011
Transportation departments are under-going a dramatic transformation, shifting from organizations focused primarily on building roads to a focus on mobility for all users. The transformation is the result of rapidly advancing autonomous vehicle technology and personal telecommunication technology. These technologies provide the opportunity to dramatically improve safety, mobility, and economic opportunity for society and industry. Future generations of engineers and other transportation professionals have the opportunity to be part of that societal change. This paper will focus on the technologies state DOT’s and the private sector are researching, developing, and deploying to promote the future of mobility and improved efficiency for commercial trucking through advancements in truck platooning, self-driving long-haul trucking, and automated last mile distribution networks.
Technical Paper

The Autonomous Vehicle Challenges for Emergent Market

2017-11-07
2017-36-0436
Technological advances in both hardware (Nano-electronics) and software (artificial intelligence) are increasingly influencing our lives on equipment and devices that surrounds us and more recently our means of locomotion. The autonomous vehicles, which previously appeared only in movie scenes, can already be found in our environment, such as ships, cars, trucks, tractors and aero engines. Considering the autonomous vehicles, its launching is much closer than we could imagine, since many companies signalize having the conditions to launch them in a large scale within 2018 year. The insertion of this type of technology opens a range of advances related to vehicles and the environment in which it is inserted. The communication between the vehicles, roads and people can be highlighted. These advances reveal a series of benefits to the customer such as free time during the route, higher safety, etc.
Research Report

Unsettled Topics Concerning Autonomous Public Transportation Systems

2020-10-30
EPR2020020
With billions of dollars of investment and events like DARPA’s Grand Challenges automated driving technology has been making its way toward commercialization. While the enabling technology for SAE Level 4 and 5 automated vehicles (AV) has not yet matured, specific restricted-use models such as “robo-taxis” and automated truck convoying show great promise. Now, cities are across the world are looking to AVs to solve their public transportation issues. With low speeds and fixed route, public transportation is an ideal application for AVs. From a business angle, AVs could leverage existing public transport models and infrastructure while providing superior quality of service for disadvantaged communities. Yet, dense urban environments—which would benefit from automated transportation the most—present unique challenges and public sector requirements. This SAE EDGE™ Research Report by Dr.
X