Browse Prior Art Database

Dynamically Identifying An Optimal Following Distance For Driverless Cars In A Slipstream Chain

IP.com Disclosure Number: IPCOM000240953D
Publication Date: 2015-Mar-13
Document File: 4 page(s) / 85K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for dynamically identifying an optimal following distance for driverless cars in a slipstream chain. The method and system relies on a cloud-based database of vehicle-makes and vehicle-models for refining a first approximation with data from onboard fuel efficiency monitoring system of vehicle.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 39% of the total text.

Page 01 of 4

Dynamically Identifying An Optimal Following Distance For Driverless Cars In A Slipstream Chain

Human driven vehicles optimize fuel efficiency based on a human intelligence and human instincts. Driverless vehicles (also called self-driving vehicle) may not optimize fuel efficiency automatically, or at least may not do so in certain situations.

Disclosed is a method and system for dynamically identifying an optimal following distance for driverless cars in a slipstream chain, where the following distance maximizes fuel efficiency. The method and system utilizes a centralized database for gathering optimal following distance data from each possible duet of vehicles in the slipstream chain.

Consider a scenario where a driverless "Vehicle A" is leading another driverless "Vehicle B". The pair, i.e. A-leading-B, have an optimal following distance at a certain speed. The following distance information is stored in a centralized database and is used for estimating a drafting distance responsive to a similar situation in the future. The method and system downloads the data from the centralized database for another possible duet of vehicles travelling at a particular speed. The downloaded data is used to maintain the speed for finding the optimal following distance between the vehicles. The capabilities of the driverless car create slipstream chains in which "Vehicle B" increases fuel efficiency by drafting behind "Vehicle A". Therefore, an ideal following distance varies with every pair of vehicles (one leading and one following).

Unlike platoons (groups of cars), the method and system automatically detects fuel efficiency by linking up a single vehicle and modulating the distance accordingly. The method and system detects fuel efficiency for a single vehicle. Thereafter, the method and system modulates the distance between the vehicles accordingly. Suppose two vehicles are traveling at highway speeds. The two vehicles traveling at highway speeds communicate with a handshake and determine that one vehicle follows the other vehicle at the drafting distance. The method and system determines that one vehicle is following the other at a certain drafting distance. The following vehicle then aligns behind the leading vehicle. At first, the distance between the vehicles may be greater than the optimal following distance for drafting. Thereafter, the following vehicle slowly closes the gap in the distance with the leading vehicle. The method and system also monitors the current fuel efficiency of the vehicles which may slowly increase. At a certain following distance, fuel efficiency may peak. There are chances that driving closer or falling back may reduce fuel efficiency of the vehicles. Therefore, the following vehicle maintains the optimal following distance at a particular speed. Hence, the vehicles drafting behind one another offer several Smarter Planet benefits including lower congestion, greater road capacity, and fuel savings. By draft...