Assessment of Technologies for Improving Light-Duty Vehicle Fuel Economy—2025-2035 (2021) / Chapter Skim
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8 Connected and Automated Vehicles
8 Connected and Automated Vehicles
Pages 238-268
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If designed with efficiency in mind, automated vehicles could substantially improve fuel efficiency, lowering drivers' fuel costs and increasing driving range for electric vehicles (EVs) while delivering societal benefits through reduced fuel use and emissions.
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The impacts on energy use from fully autonomous vehicles, such as increased travel owing to accessibility for the non-driving population and greater productivity for vehicle occupants, are discussed in Chapter 9. 8.2 CAV TECHNOLOGIES 8.2.1 Automation Technologies and Operating Modes The push for safer vehicles to reduce the number of road fatalities and injuries has been behind the introduction of electronically controlled systems to enhance human driving capabilities and supplement or replace mechanical- and hydraulic-based vehicular systems.
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For example, LRR is the key sensor for adaptive cruise control (ACC) and highway automatic emergency braking systems, while MRRs are mainly deployed for blind zone detection and rear cross traffic and SRRs for rear emergency breaking.
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digital mapping is an important addition to vehicle automation technology at all levels. While map accuracy for navigation purposes is 10 m and 1–2 m for ADAS purposes, HD maps have an accuracy of 10 cm.
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It can bring multiple other benefits as well, including better fuel efficiency. Connected vehicles can use a combination of different technologies to communicate with their surroundings including other road users, roadside infrastructure, and other devices, which may be near or far.
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A 2012 report of the Center for Automotive Research reported DSRC per vehicle cost projections from a connected vehicle technology industry Delphi study, as shown in Table 8.3 (CAR, 2012)
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automated vehicle system components. TABLE 8.4 Onboard Technologies That Enable Automation and Connectivity and Their Capabilities as Implemented in 2020 Vehicles Specs in 2020 Number per Weight per Power Draw per Cost per Technology Vehicle Unit (kg)
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8.2.4 Onboard Computing Vehicle automation systems require substantial onboard computing. The continued expansion of their functionality to systems with greater vehicle driving authority requires dramatic increases in electronic content and interconnected, embedded systems.
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Table 8.5 details several of the available and upcoming models. 8.3 IMPACTS OF CAV TECHNOLOGIES ON VEHICLE EFFICIENCY Vehicle automation can increase or decrease fuel consumption owing to a variety of factors.
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Benz models • Ultrasonic sensors • Active lane keeping assist • Digital HD map technology • Active lane change assist • Active brake assist with cross-traffic function • Active emergency stop assist • Active speed limit assist • Evasive steering assist • Congestion emergency braking • Route-based speed adaptation Nissan ProPilot Assist 2 (Pro Pilot Assist • Centrally mounted • Lane centering and blind spot MY 2016 (Serena, Japan) High for both luxury and Altima, Rogue, Leaf with Navi-link)
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• Sensors • Adaptive cruise control with ($42,000–$55,000 + luxury trims • Driver monitoring system stop-and-go capability and $4,150–$4,950) • Radar speed sign recognition • Traffic jam assistance • Precollision assist and pedestrian detection • Evasive steering assist Toyota Mobility 2 (Mobility Teammate)
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• 360-degree sensing -- front • Lane centering MY 2020 (Skyline, Japan, Standard with hybrid Ariya camera, front and side sonar, • Accelerating and braking in $40,000) Skyline in Japan front and side radar, AVM response to vehicle ahead cameras • Advanced steering assist Will be available in United • Driver monitoring camera • Hands-free single lane, States with MY 2021 • Intelligent dynamic highway driving suspension • Hands-on guided lane • Direct adaptive steering changing abilities • Assist in passing, lane diversions and lane exiting BMW 2021 iNext 3 • 5G • In "ease mode" the steering 2021 (highway pilot)
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. If an automated vehicle using eco-driving algorithms is tested for fuel economy by "following" a federal testing drive cycle, it will exceed the allowable deviation from the standard drive cycles for fuel consumption testing.
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Hence the automated vehicle cannot use eco-driving during testing, so the fuel savings go undetected, removing an incentive for automakers to adopt the technology. FINDING 8.2: Connectivity technologies can add substantially to the fuel savings benefits of automation technologies.
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FINDING 8.3: Connected and automated driving can allow some engine and powertrain efficiency technolo gies to achieve their full savings potential. However, high penetration of highly automated vehicles that create a deterministic traffic environment would limit the need for high torque capability and thus make small, natu rally aspirated engines with stop-start and limited torque-assist the most cost-effective and efficient option for engine-powered vehicle powertrains where towing and load-carrying capabilities are not required.
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These efficiency gains (2%–3%) from power management in a strong HEV by automated driving or load preview can be smaller than the efficiency gains obtained in mild or micro-HEVs (4%–6%)
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FINDING 8.4: The look-ahead information provided by connected and automated vehicle technologies can be used to improve power management in hybrids, increasing efficiency by 2%–3% in strong hybrids and 4%–6% in mild hybrids. PHEVs have the potential for the highest percentage gains, with as much as 14% higher fuel efficiency on trips that significantly exceed the battery range.
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Indeed, given that BEVs will ultimately be equipped with CAV technologies to improve safety, functionality, and convenience, one might view the primary energy efficiency objective for a BEV's CAV technologies as offsetting any range loss arising from the system's power requirements. On the other hand, BEVs' electrical and auxiliary systems may otherwise be a good match for CAV packaging requirements.
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(2019) simulated Levels 4 and 5 automated driving systems for real-world vehicle trips from the California Household Travel Survey assuming constant system power consumption of 2.5 kW above that of a non-automated vehicle, consistent with "the likely present-day value" (Hamza et al., 2019)
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Level 1 to 3 vehicles are likely to crash less frequently than conventional vehicles, and Level 4 and 5 vehicles presumably will crash very rarely. If these highly automated vehicles were to achieve full penetration, crashworthiness requirements could be substantially reduced.
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CAV technologies are added primarily for safety and other non-energy related purposes, so costs should not be entirely attributed to fuel economy. Package effectiveness estimates do not reflect operation over the standardized test cycles, but rather are mostly based on testing or simulation reflecting driving patterns closer to actual conditions and optimization for individual vehicles.
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Individual automation technologies may result in fuel savings of more than 10% in some driving conditions, although they can also increase fuel use if not implemented for efficiency. FINDING 8.8: With reliable vehicle-to-infrastructure information, connected and automated vehicle technolo gies in combination could increase fuel efficiency by as much as 20% in some driving conditions.
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• Data and mapping technology • Onboard computing and vehicle controls • Wiring Level 2 automation w/ PT Previous package plus: $2,410 $2,292 $2,180 $2,073 controls + connectivity • Communications technology (DSRC or Above plus: C-V2X transceiver) • V2X to extend prediction horizon • Additional computer • Optimization of engine and transmission controls 1 power management (HEV, PHEV)
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. FIGURE 8.8 Company announcements of deployment of highly automated vehicles.
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8.5.1 CAV Technologies in Fuel Economy Standards One domain in which energy impacts of CAVs have been discussed in some detail is fuel economy and emissions standards. While some CAV technologies can substantially improve energy efficiency, these savings would not generally raise a vehicle's test fuel economy, because the test protocols are designed to ensure consistency of driving across all vehicles.
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One way to avoid this problem would be for the agencies to consider CAV technologies that can save energy in setting the level of the standards. The velocity trajectories through which CAVs can achieve fuel efficiency improvements may differ significantly from the velocity profile of the standard fuel economy test cycles.
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December 17. https://www.forbes.com/sites/samabuelsamid/2019/12/17/nvidia-announces-next-generation-orin-chip-for-automated vehicles/#7acc35f4f373.
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2020. "SMART Mobility Connected and Automated Vehicles Capstone Report." Office of Energy Efficiency and Renewable Energy.
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2020. "Energy-Efficient Connected and Automated Vehicles -- EEMS016." Presentation at the Department of Energy Vehicle Technologies Office Annual Merit Review.
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2019. "Integrated Power and Thermal Management for Connected and Automated Vehicles (IPTM-CAV)
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2019. An automated vehicle fuel economy benefits evalu ation framework using real-world travel and traffic data.
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