An Energy-Efficient High Definition Map Data Distribution Mechanism for Autonomous Driving

10/11/2020
by   Jinliang Xie, et al.
0

Autonomous Driving is now the promising future of transportation. As one basis for autonomous driving, High Definition Map (HD map) provides high-precision descriptions of the environment, therefore it enables more accurate perception and localization while improving the efficiency of path planning. However, an extremely large amount of map data needs to be transmitted during driving, thus posing great challenge for real-time and safety requirements for autonomous driving. To this end, we first demonstrate how the existing data distribution mechanism can support HD map services. Furthermore, considering the constraints of vehicle power, vehicle speed, base station bandwidth, etc., we propose a HD map data distribution mechanism on top of Vehicle-to-Infrastructure (V2I) data transmission. By this mechanism, the map provision task is allocated to the selected RSU nodes and transmits proportionate HD map data cooperatively. Their works on map data loading aims to provide in-time HD map data service with optimized in-vehicle energy consumption. Finally, we model the selection of RSU nodes into a partial knapsack problem and propose a greedy strategy-based data transmission algorithm. Experimental results confirm that within limited energy consumption, the proposed mechanism can ensure HD map data service by coordinating multiple RSUs with the shortest data transmission time.

READ FULL TEXT
research
04/24/2021

MultiCruise: Eco-Lane Selection Strategy with Eco-Cruise Control for Connected and Automated Vehicles

Connected and Automated Vehicles (CAVs) have real-time information from ...
research
11/27/2021

Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning

Autonomous driving technologies are expected to not only improve mobilit...
research
06/03/2021

Energy-Efficient Adaptive System Reconfiguration for Dynamic Deadlines in Autonomous Driving

The increasing computing demands of autonomous driving applications make...
research
01/22/2023

Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories

Prevalent solutions for Connected and Autonomous vehicle (CAV) mapping i...
research
12/29/2018

PI-Edge: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services

To simultaneously enable multiple autonomous driving services on afforda...
research
08/31/2023

Edge-Assisted Lightweight Region-of-Interest Extraction and Transmission for Vehicle Perception

To enhance on-road environmental perception for autonomous driving, accu...
research
04/19/2023

VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene

High-definition (HD) map serves as the essential infrastructure of auton...

Please sign up or login with your details

Forgot password? Click here to reset