Personalized Routing for Car Navigation Systems (original) (raw)
Proceedings of the 19th …, 2006
Navigation services (e.g., in-car navigation systems and online mapping sites) compute routes between two locations to help users navigate. However, these routes may direct users along an unfamiliar path when a familiar path exists, or, conversely, may include redundant information that the user already knows. These overly complicated directions increase the cognitive load of the user, which may lead to a dangerous driving environment. We have developed a system, called MyRoute, that reduces route complexity by creating user specific routes based on a priori knowledge of familiar routes and landmarks. MyRoute works by compressing well known steps into a single contextualized step and rerouting users along familiar routes.
Personalized Routing Dynamically Adjusted to Avoid Adverse Situations
2021
Routes that are optimal in general for a particular travel need may at times be unsuitable in a specific instance because of various factors such as construction, weather, accidents, rush hour traffic, road surface conditions, presence of crowds, etc. The impact of such factors on a person's travel plans can depend on the specifics of the person's travel circumstances, such as travel mode, vehicle characteristics, etc. This disclosure describes techniques to proactively deliver travel routing guidance personalized to a user, based on user-permitted contextual factors.
Performance and Quality Evaluation of a Personalized Route Planning System
2003
Advanced personalization of database applications is a big challenge, in particular for distributed mobile environments. We present several new results from a prototype of a route planning system. We demonstrate how to combine qualitative and quantitative preferences gained from situational aspects and from personal user preferences. For performance studies we analyze the runtime efficiency of the SR-Combine algorithm used to evaluate top-k queries. By determining the cost-ratio of random to sorted accesses SR-Combine can automatically tune its performance within the given system architecture. Top-k queries are generated by mapping linguistic variables to numerical weightings. Moreover, we analyze the quality of the query results by several test series, systematically varying the mappings of the linguistic variables. We report interesting insights into this rather under-researched important topic. More investigations, incorporating also cognitive issues, need to be conducted in the ...
Personalized services for mobile route planning: a demonstration
2003
Enabling mobility in urban and populous areas needs innovative tools and novel techniques for individual traffic planning. We present a prototype of a traffic information system enabling personalized route planning plus advanced services like traffic jam alerting. The best routes are efficiently computed using the SR-Combine algorithm, subject to various user preferences and current traffic situation gathered dynamically from several Internet sources. We implemented a J2EE application server which smoothly adapts to distributed online processing, once high bandwidth networks like UTMS are available.
Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015
All current navigation systems return efficient source-todestination routes assuming a "one-size-fits-all" set of objectives, without addressing most personal preferences. Although they allow some customization (like "avoid highways" or "avoid tolls"), the choices are very limited and require some sophistication on the part of the user. In this paper we present, implement, and test a framework that generates personalized driving directions by automatically analyzing users' GPS traces. Our approach learns cost functions using coordinate descent, leveraging a state-of-the-art route planning engine for efficiency. In an extensive experimental study, we show that this framework infers user-specific driving preferences, significantly improving the route quality. Our approach can handle continental-sized inputs (with tens of millions of vertices and arcs) and is efficient enough to be run on an autonomous device (such as a car navigation system) preserving user privacy.
A Map Matching Algorithm for Car Navigation Systems that Predict User Destination
22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
In this paper, we propose a map matching algorithm for car navigation systems that predict user destination. This car navigation system is a novel system that automatically predicts user purpose and destination to present various information based on predicted purpose without user interaction. It requires the correct road where the car drives in real time, and it also need to know the route from the start point to the current point correctly. The proposal map matching method divides the trajectory into equal intervals and calculates the shortest path score for each one. Testing using GPS data for actual car trips showed that its use results in better destination prediction than with conventional methods in most cases. The results were the best for intervals of 5 minutes.
In the past few years, with the proliferation of mobile devices people are experiencing frequent communication and information exchange. For instance, in the context of people's visits, it is often the case that each person carries out a smart phone, to get information about nearby places. When one visits some location, an application will recommend useful information according to its current location, preferences and past visits. This paper introduces the concept of smart routing as a recommender system for tourists that takes into account the dynamics of their personal user profiles.
Online Route Prediction for Automotive Applications
2006
An information and communication technology infrastructure is rapidly emerging that enables the delivery of location-based services to vast numbers of mobile users. Services will benefit from being aware of not only the user’s location, but also the user’s current destination and route towards the destination. This paper describes a component that enables the use of geocontext. Using GPS data, the component gathers a driver’s routes and associates them with usage meta-data. Other services may then provide the component with a driver ID, the time of the day, and a location, in return obtaining the likely routes for the driver.
Proceedings of the 2004 ACM symposium on Applied computing - SAC '04, 2004
Intelligent Transportation Systems are characterised by a requirement for detailed information on extensive transport networks. This information is typically gathered from sensors deployed throughout the network and is used for management and maintenance operations.
Smart Navigation: Using Artificial Intelligent Heuristics in Navigating Multiple Destinations
Navigation applications are becoming an essential need in any mobile device. Finding the best path (time and distance) from an address to another is one of the most asked queries among driving users. Moreover, finding the best path with multiple destinations is a query that could be asked by many, including commercial companies' drivers (similar to the famous "Traveling Salesman Problem"). Google maps, Yahoo maps, and tens of other solutions are examples of such mobile applications. Calculating the best driving path between two addresses is subject to many factors including distance, road situation, road traffic, speed limitations and others. This paper presents the use of smart heuristic functions, as well as an efficient data structure to be used in finding efficient path between multiple points (addresses) rather than one destination. It presents spatial databases, current solutions, heuristics in Graph problems, and finally a smart solution (our new Algorithm A*Mul...