Automation Enabling Technologies: Future Forecast, FY2014
Office of Operations Research and Development
Automation Enabling Technologies: Future Forecast, FY2014
BACKGROUND
Mohammed Yousuf 1; Daniel J Dailey 1; Kevin Dopart 1
POSITIONING, NAVIGATION & TIMING
MAPPING
COMMUNICATIONS
Vehicle automation relies heavily on technologies such as wireless communications, positioning, mapping, localization, timing, tracking, and sensing. Applications planned within the USDOT’s automation research roadmap depend on the understanding and applicability of these technologies. It is thus important to be aware of the state of these technologies, and more importantly “stay ahead of the curve”. The value of this project is not in accurately predicting the future of these technologies for USDOT’s automation program, but to minimize surprises. NEEDS: Accurate and reliable positioning that is
NEEDS: Macro/micro level maps to assist vehicle
affordable and precise for sensor fusion and cooperative aspects
navigation, real-time mapping algorithms to map vehicle’s surrounding environment accurately
TRENDS: Increased PNT capability at lower costs =
TRENDS: Increased use of Graphical Processing Units
increased sophistication in vehicles. New frameworks for sensor fusion > greater confidence in positioning
& 3D maps, Advanced SLAM techniques to handle challenging and dynamic conditions (weather/lighting)
GAPS: Many challenges still present (e.g. urban
GAPS: Limited data sharing between infrastructure
canyon, tunnels, etc.); majority of applications dependent on one source for GNSS timing
and vehicles; expensive LIDAR-based SLAM and Visual SLAM can’t handle challenging conditions
NEXT STEPS: Research methods to provide
NEXT STEPS: Research methods for exchanging
corrections from infrastructure elements; investigate timing techniques that provide redundancy
SENSORS
situational awareness between fixed infrastructure points and vehicles & real-time dynamic mapping
NEEDS: Technologies complimentary to DSRC for reliable and secure communications at high data rates, low latency, and efficient use of spectrum
TRENDS: Growth of 4G/5G networks enabling gigabits data transmission; use of RF alternatives (VLC & Li-Fi); Expansion of M2M for in-vehicle communications
GAPS: Communications security for both CV and AV; integrated wireless communication solutions for invehicle, inter-vehicle, and long range communications
NEXT STEPS: Further research solutions for communication security /privacy issues; Monitor progress of 5G cellular, M2M and D2D technologies
HUMAN FACTORS EXPECTED RESULTS
GOALS AND OBJECTIVES This project will employ professional experts in the technical areas necessary (e.g. positioning, navigation & timing, communications, sensing), for automated-connected vehicles, to track technical and popular press (all media forms) in the areas identified as enabling technologies, as well as related areas, on a monthly basis. The major goals of this project are listed below: • Provide guidance to USDOT with respect to technologies necessary to advance vehicle automation efforts • Provide a clear understanding of current and future directions of technologies necessary for automated vehicles • Provide a framework and content to understand the unique needs of vehicle automation applications and project the likely direction for technologies
NEEDS: Accurate and reliable 360 degree sensing of
NEEDS: Cooperative/non-distracting in-vehicle devices
vehicle surrounding; sensing in all-weather conditions without degradation TRENDS: Increased vision-based systems for detecting obstructions/recognizing objects; improved micro-processors and cloud based systems GAPS: Cannot perform in all-weather conditions; reliability still an issue and lack of robust standards to enhance data interface and accessibility NEXT STEPS: Research infrastructure sensors that compliment AV; explore updates to traffic signs/signals for improved recognition by AV Sensors
for different levels of automation; safe and smooth transition of control from AV to human TRENDS: Studies to understand driver behavior in different conditions; simulations to understand driver interaction at different levels of automation GAPS: Most simulators not flexible/dynamic; AV interaction with legacy vehicles and other vulnerable road users is still unknown (user Vs non-user) NEXT STEPS: Research needs and implications of different levels of automation on driving population (including older / disabled drivers)
1U.S.DOT
- Federal Highway Administration, Turner-Fairbank Highway Research Center
The research team documents important findings from weekly research activities and compiles the observations in an easy to understand format. The following are the list of deliverables as part of this project: 1 Literature Review Report Covers a wide range of technologies enabling vehicle automation 8 Monthly Technical Reports (7 reports completed thus far) New developments in research areas of interest Forecasts and recommendations as applicable 2 Webinars May 6th, 2015 Fall 2015 (date not fixed yet) 2 Summary Reports Interim report – Spring 2015 Final report – Fall 2015
Image Source: USDOT/Thinkstock
Automation Enabling Technologies: Future Forecast, FY2014
BACKGROUND
Mohammed Yousuf 1; Daniel J Dailey 1; Kevin Dopart 1
POSITIONING, NAVIGATION & TIMING
MAPPING
COMMUNICATIONS
Vehicle automation relies heavily on technologies such as wireless communications, positioning, mapping, localization, timing, tracking, and sensing. Applications planned within the USDOT’s automation research roadmap depend on the understanding and applicability of these technologies. It is thus important to be aware of the state of these technologies, and more importantly “stay ahead of the curve”. The value of this project is not in accurately predicting the future of these technologies for USDOT’s automation program, but to minimize surprises. NEEDS: Accurate and reliable positioning that is
NEEDS: Macro/micro level maps to assist vehicle
affordable and precise for sensor fusion and cooperative aspects
navigation, real-time mapping algorithms to map vehicle’s surrounding environment accurately
TRENDS: Increased PNT capability at lower costs =
TRENDS: Increased use of Graphical Processing Units
increased sophistication in vehicles. New frameworks for sensor fusion > greater confidence in positioning
& 3D maps, Advanced SLAM techniques to handle challenging and dynamic conditions (weather/lighting)
GAPS: Many challenges still present (e.g. urban
GAPS: Limited data sharing between infrastructure
canyon, tunnels, etc.); majority of applications dependent on one source for GNSS timing
and vehicles; expensive LIDAR-based SLAM and Visual SLAM can’t handle challenging conditions
NEXT STEPS: Research methods to provide
NEXT STEPS: Research methods for exchanging
corrections from infrastructure elements; investigate timing techniques that provide redundancy
SENSORS
situational awareness between fixed infrastructure points and vehicles & real-time dynamic mapping
NEEDS: Technologies complimentary to DSRC for reliable and secure communications at high data rates, low latency, and efficient use of spectrum
TRENDS: Growth of 4G/5G networks enabling gigabits data transmission; use of RF alternatives (VLC & Li-Fi); Expansion of M2M for in-vehicle communications
GAPS: Communications security for both CV and AV; integrated wireless communication solutions for invehicle, inter-vehicle, and long range communications
NEXT STEPS: Further research solutions for communication security /privacy issues; Monitor progress of 5G cellular, M2M and D2D technologies
HUMAN FACTORS EXPECTED RESULTS
GOALS AND OBJECTIVES This project will employ professional experts in the technical areas necessary (e.g. positioning, navigation & timing, communications, sensing), for automated-connected vehicles, to track technical and popular press (all media forms) in the areas identified as enabling technologies, as well as related areas, on a monthly basis. The major goals of this project are listed below: • Provide guidance to USDOT with respect to technologies necessary to advance vehicle automation efforts • Provide a clear understanding of current and future directions of technologies necessary for automated vehicles • Provide a framework and content to understand the unique needs of vehicle automation applications and project the likely direction for technologies
NEEDS: Accurate and reliable 360 degree sensing of
NEEDS: Cooperative/non-distracting in-vehicle devices
vehicle surrounding; sensing in all-weather conditions without degradation TRENDS: Increased vision-based systems for detecting obstructions/recognizing objects; improved micro-processors and cloud based systems GAPS: Cannot perform in all-weather conditions; reliability still an issue and lack of robust standards to enhance data interface and accessibility NEXT STEPS: Research infrastructure sensors that compliment AV; explore updates to traffic signs/signals for improved recognition by AV Sensors
for different levels of automation; safe and smooth transition of control from AV to human TRENDS: Studies to understand driver behavior in different conditions; simulations to understand driver interaction at different levels of automation GAPS: Most simulators not flexible/dynamic; AV interaction with legacy vehicles and other vulnerable road users is still unknown (user Vs non-user) NEXT STEPS: Research needs and implications of different levels of automation on driving population (including older / disabled drivers)
1U.S.DOT
- Federal Highway Administration, Turner-Fairbank Highway Research Center
The research team documents important findings from weekly research activities and compiles the observations in an easy to understand format. The following are the list of deliverables as part of this project: 1 Literature Review Report Covers a wide range of technologies enabling vehicle automation 8 Monthly Technical Reports (7 reports completed thus far) New developments in research areas of interest Forecasts and recommendations as applicable 2 Webinars May 6th, 2015 Fall 2015 (date not fixed yet) 2 Summary Reports Interim report – Spring 2015 Final report – Fall 2015
Image Source: USDOT/Thinkstock
