Related papers: A Survey and Insights on Deployments of the Connected and Autonomous Vehicles in US

A Survey and Insights on Deployments of the Connected and Autonomous Vehicles in US

URL: http://arxiv.org/abs/2008.04379v1
Date: Mon, 10 Aug 2020 19:35:51 GMT
Title: A Survey and Insights on Deployments of the Connected and Autonomous Vehicles in US
Authors: Sanchu Han
Abstract summary: CV/ITS (Connected Vehicle, Intelligent Transportation System) and AV/ADS (Autonomous Vehicle, Automated Driving System) have been emerging for the sake of saving people lives, improving traffic efficiency and helping the environment for decades. There are separate efforts led respectively by USDOT with state DOTs for CV, and private sectors through market driven approach from start-ups and technology companies for AV. By CV/ITS effort there are 97 deployments of V2X communications utilizing the 5.9 GHz band, 18,877 vehicles with aftermarket V2X communications devices, and 8,098 infrastructure V2X devices installed at the roadsides
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: CV/ITS (Connected Vehicle, Intelligent Transportation System) and AV/ADS (Autonomous Vehicle, Automated Driving System) have been emerging for the sake of saving people lives, improving traffic efficiency and helping the environment for decades. There are separate efforts led respectively by USDOT with state DOTs for CV, and private sectors through market driven approach from start-ups and technology companies for AV. By CV/ITS effort there are 97 deployments of V2X communications utilizing the 5.9 GHz band, 18,877 vehicles with aftermarket V2X communications devices, and 8,098 infrastructure V2X devices installed at the roadsides. However, CV/ITS still cannot be massively deployed in US markets due to lack of regulations, dedicated wireless spectrum bands, sustainable financial & business models with mature supply chain, etc. In the other side, technology-driven AV market has been much slower than expected mainly because of immaturity of AI technology to handle different complex driving scenarios in a cost effective way. In this paper, we first present these two parallel journeys focusing on the deployments including operating models, scenarios and applications, evaluations and lessons learning. Then, come up with recommendations to a cooperative CAV approach driving a more feasible, safer, affordable and cost effective transportation, but require a great industry collaboration from Automotive, Transportation. ICT and Cloud.

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