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The operational safety of Automated Driving System (ADS)-Operated Vehicles (AVs) are a rising concern with the deployment of AVs as prototypes being tested and also in commercial deployment. The robustness of safety evaluation systems is essential in determining the operational safety of AVs as they interact with human-driven vehicles. Extending upon earlier works of the Institute of Automated Mobility (IAM) that have explored the Operational Safety Assessment (OSA) metrics and infrastructure-based safety monitoring systems, in this work, we compare the performance of an infrastructure-based Light Detection And Ranging (LIDAR) system to an onboard vehicle-based LIDAR system in testing at the Maricopa County Department of Transportation SMARTDrive testbed in Anthem, Arizona. The sensor modalities are located in infrastructure and onboard the test vehicles, including LIDAR, cameras, a real-time differential GPS, and a drone with a camera. Bespoke localization and tracking algorithms are created for the LIDAR and cameras. In total, there are 26 different scenarios of the test vehicles navigating the testbed intersection; for this work, we are only considering car following scenarios. The LIDAR data collected from the infrastructure-based and onboard vehicle-based sensors system are used to perform object detection and multi-target tracking to estimate the velocity and position information of the test vehicles and use these values to compute OSA metrics. The comparison of the performance of the two systems involves the localization and tracking errors in calculating the position and the velocity of the subject vehicle, with the real-time differential GPS data serving as ground truth for velocity comparison and tracking results from the drone for OSA metrics comparison.

The operational safety of Automated Driving System-equipped vehicles (AVs) is a critical issue with AVs being deployed on public roads. Methodologies for evaluating the operational safety are therefore necessary to maintain public safety. One possible approach is a safety case established by the AV developer that uses evidence to support a structured argument that the AV exhibits a given level of operational safety. One of the key components of a safety case for AVs is a set of testing results showing behavioral competency in a variety of scenarios within the AV’s operational design domain (ODD). The Institute of Automated Mobility (IAM) has previously published operational safety assessment (OSA) metrics along with a means to evaluate the severity of violations of the safety envelope-type OSA metrics for navigation of individual scenarios in the proposed OSA Methodology. The objective of the OSA Methodology is to objectively quantify the safety performance of each scenario navigated by the AV, with the aggregate quantifications to be included in the AV’s safety case. This work expands on the introduction of the OSA Methodology to (1) include more OSA metrics (beyond the safety envelope type) with clearly defined formulations for the severity of metric violation formulations, and (2) propose a methodology for interpreting the various OSA metric violation measurements to result in the desired quantification of the AV’s safety performance of a scenario navigation that is composed of evaluations of collision events, near-miss events, and non-collision events. The OSA Methodology is implemented in various simulation software and in real-world testing results at an IAM testbed to validate the concept. The results show a promising test result interpretation methodology that can be incorporated into a safety case framework to help ensure AV operational safety.

As energy storage system (ESS) technology advances, vehicle testing in both laboratory and on-road settings is needed to characterize the performance of state-of-the-art technology and also identify areas for future improvement. The Idaho National Laboratory (INL), through its support of the U.S. Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA), is collaborating with ECOtality North America and Oak Ridge National Laboratory (ORNL) to conduct on-road testing of advanced ESSs for the Electric Drive Advanced Battery (EDAB) project. The project objective is to test a variety of advanced ESSs that are close to commercialization in a controlled environment that simulates usage within the intended application with the variability of on-road driving to quantify the ESS capabilities, limitations, and performance fade over cycling of the ESS. To accommodate on-road testing of a wide range of ESS size, mass, and intended applications, the EDAB testbed was constructed on a mid-sized pickup truck chassis. This truck was converted into a Series Plug-In Hybrid Electric Vehicle (PHEV) which enables vehicle operation consistent with any electrified vehicle. Sophisticated software algorithms were prepared and integrated into the testbed to emulate the physical characteristics and ESS demands of the intended application during on-road operation. This emulation is vital for proper ESS operation since the testbed is larger and heavier than the vehicle for which the ESS is typically designed. On-road testing is conducted over a range of ambient temperatures and driving route types ranging from ‘stop-and-go’ city driving to constant-speed highway driving. Battery laboratory cycling with standard test procedures has been conducted throughout all phases of testing to corroborate the on-road data and accurately measure the ESS degradation. The first ESS to be tested is the Type I EV Pack manufactured by EnerDel, Inc. The ESS has a Li-ion chemistry, with a mixed-oxide cathode and amorphous hard carbon anode and a rated capacity of 70 Ah (at a C/3 rate). Due to the sealed enclosure, there is no internal thermal management system (TMS). The intended application for this ESS is for a small EV. This paper will report on current results of energy consumption, city vs. highway proportions, battery throughput, and laboratory testing results. The results illustrate the performance of the unit under test and the degradation throughout. The end-of-test criteria are 100,000 miles, three years of operation, or a 23% decrease in battery capacity, whichever occurs first.

Vehicles equipped with idle-stop (IS) systems are capable of engine shut down when the vehicle is stopped and rapid engine re-start for the vehicle launch. This capability reduces fuel consumption and emissions during periods when the engine is not being utilized to provide propulsion or to power accessories. IS systems are a low-cost and fast-growing technology in the industry-wide pursuit of increased vehicle efficiency, possibly becoming standard features in European vehicles in the near future. In contrast, currently there are only three non-hybrid vehicle models for sale in North America with IS systems and these models are distinctly low-volume models. As part of the United States Department of Energy’s Advanced Vehicle Testing Activity, ECOtality North America has tested the real-world effect of IS systems on fuel consumption in three vehicle models imported from Europe. These vehicles were chosen to represent three types of systems: (1) spark ignition with 12-V belt alternator starter; (2) compression ignition with 12-V belt alternator starter; and (3) direct-injection spark ignition, with 12-V belt alternator starter/combustion restart. The vehicles have undergone both dynamometer and on-road testing; the test results show somewhat conflicting data. The laboratory data and the portion of the on-road data in which driving is conducted on a prescribed route with trained drivers produced significant fuel economy improvement. However, the fleet data do not corroborate improvement, even though the data show significant engine-off time. It is possible that the effects of the varying driving styles and routes in the fleet testing overshadowed the fuel economy improvements. More testing with the same driver over routes that are similar with the IS system-enabled and disabled is recommended. There is anecdotal evidence that current Environmental Protection Agency fuel economy test procedures do not capture the fuel economy gains that IS systems produce in real-world driving. The program test results provide information on the veracity of these claims.