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Method and System for Cognitive Conversational Vehicle Navigation System

IP.com Disclosure Number: IPCOM000249426D
Publication Date: 2017-Feb-27
Document File: 3 page(s) / 88K

Publishing Venue

The IP.com Prior Art Database

Abstract

This disclosure introduces a method and system for cognitive conversational vehicle navigation system. The current vehicle navigation system is usually working in a fixed way, rather than considering the driving skills and demands of individual drivers. Therefore, this disclosure provides a cognitive way to understand the driver's intention on the routine, retrieves the surrounding environmental factors that may affect the navigation, and then dynamically adjust the interactions with the driver for better navigation effect.

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Method and System for Cognitive Conversational Vehicle Navigation System

This disclosure introduces a method and system to enhance the user experience of vehicle navigation system by more cognitive conversational support.

It is observed that the current vehicle navigation system is usually working in a fixed way, rather than considering the driving skills and demands of individual drivers. For example, an experienced driver may only need 20 minutes for a 20-mile distance, however, an inexperienced driver may need 30 minutes or more. An experienced driver may only need very few guidance from the navigation system, however, an inexperienced driver may frequently check with the navigation system to confirm the right routine.

This disclosure models the personalized navigation needs as <s, v, n, r, inst>, where: s : the driver’s response time to the instruction; v : vehicle speed; n : noise; r : the road condition, which is a <start_point, end_point, road_type , complexity >; inst : instruction that should be given to user.

Figure 1 shows the system flow. Through interacting with the user, the system can first establish the expected routine, and then identify personalized user navigation needs. After that, the system predicts road condition, vehicle speed, surrounding noise based on previous history data, and updates the current location using absolute and relative distance measure. The personalized user navigation needs, road condition, vehicle speed, surrounding noise, and latest location will be used as constraints to generate constraint-based r...