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Method and System for Cognitive Vehicle Route Recommendation System

IP.com Disclosure Number: IPCOM000247892D
Publication Date: 2016-Oct-10
Document File: 3 page(s) / 159K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for providing a cognitive optimized route map based on user preferences, wherein the system is a learning model dynamically detecting and updating the user preferences. The method and system further provides optimized route maps to locations, relevant to performance alerts from the respective automobile, thereby reducing the risk level associated with driving.

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Method and System for Cognitive Vehicle Route Recommendation System

Dependence on automobiles for transportation has been an age old practice. However, users are not necessarily aware of the condition of the road that they would be taking, due to many parameters including, but not limited to user being an inexperienced driver, lack of awareness about weather and road conditions by the user. Elderly drivers, specifically face hardships while driving due to their decreased attention and reaction time to the vehicles surrounding them.

Disclosed is a method and system for providing a cognitive optimized route map based on user preferences, wherein the system is a learning model dynamically detecting and

updating the user preferences. The method and system further provides optimized route maps to locations, relevant to performance alerts from the respective automobile, thereby reducing the risk level associated with driving.

In accordance with the system, the cognitive map builder module has numerous functions associated with it, namely accepting an output from the rule engine, applying an optimized route building algorithm in lieu of the rule priorities and further providing the user (driver) with verbal comments and explanations regarding the optimized built

routes.

Figure 1

As illustrated in Figure 1, the system includes a data collection module, a rule processing module and a cognitive map builder module. The system is integrated into a cloud environment, the cloud environment facilitating access to data sources and repositories related to route conditions. The data collection module collects various

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route map building facts, wherein the facts include, but are not limited to performance and conditions of the automobile, driver's driving ability level, state and conditions of roads, traffic, weather and route metadata (purpose, time, priorities). Based on the source of the facts, the data collection module categorizes the facts into static and dynamic, wherein static facts can be, but not limited to, driver's age and car type and dynamic facts are facts constantly updated in real-time.

The rule processing as illustrated in Figure 1, includes a rule engine, a rule agent and a set of rules. A fuzzy rules reasoning computational model is applied to the facts

collected from various data sources, to enable level of reasoning's. Further, a basic set of generic rules are provided during the initiation of the system, while the properties

associated with the rules are updated in real-time. The rule engine processes the route map building rules and applies them to the route map building facts, collected at the data collecting module, further recommending adjustments to routes, addition of specific locations to the map or adjusting priorities of the existing rules. The rule agent processes is also involved in updating the rules, more specifically the fuzzy sets by adding new rules or adjusting the priorities of t...