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.
Car navigation – computing routes that avoid complicated crossings
Personalized navigation and way-finding are prominent research areas of location-based service (LBSs). This includes innovative concepts for car navigation. Within this paper, we investigate the idea of providing drivers a routing suggestion which avoids ‘complicated crossings’ in urban areas. Inexperienced drivers include persons who have a driver’s license but, for whatever reason, feel uncomfortable to drive in a city environment. Situations where the inexperienced driver has to depend on a navigation device and reach a destination in an unfamiliar territory may be difficult. Preferences of inexperienced drivers are investigated. ‘Fears’ include driving into ‘complicated crossings’. Therefore, the definition and spatial characteristics of ‘complicated crossings’ are investigated. We use OpenStreetMap as a road dataset for the routing network. Based on the topological characteristics of the dataset, measured by the number of nodes, we identify crossings that are ‘complicated’. The user can choose to compute an alternative route that avoids these complicated crossings. This methodology is one step in building a full ‘inexperienced drivers’ routing system, which includes additional preferences from the user group, for example, as avoiding left turns where no traffic light is present.
Route guidance systems for improving urban travel and location choices
Transportation Research Part A: General
Recent technological advances in navigation systems for private vehicles have the capability to provide drivers with highway route information on a dashboard-mounted video display screen. These technological advances, together with two-way radio communication of digital information, automatic measurement of traffic flows, and supercomputer technology, could be combined to provide useful information to drivers concerning expected travel times, best routes, and best departure times. This paper reviews the status of this technology and explores the information and prediction requirements for the computer models required to implement such a system. Research needed to evaluate the potential impact of s&h a system is also described.
International Journal of Linguistics and Computational Applications, 2015
Traveling is a part of every person's day-today life. With the massive and complicated road network of a modern city or country, finding a good route to travel from one place to another is not a simple task. The knowledge of the actual current state of the road traffic and its short-term and dynamic path evolution for the entire road network is a basic component of ATIS (Advanced Traveler Information Systems) and ATMS Advanced Traffic Management System) applications. In this view the use of real-time Taxi Data (TD), based on traces of GPS positions to gather accurate travel times/speeds in a road network and to improve short-term predictions of travel conditions. GPS-equipped taxis can be regarded as traffic flows on road surfaces, and taxi drivers are usually experienced in finding the fastest (quickest) route to a destination based on their knowledge. We mine smart driving directions from the historical GPS trajectories of a large number of taxis, and provide a user with the practically fastest route to a given destination at a given departure time. In our approach, we propose a time-dependent landmark graph, where a node (landmark) is a road segment frequently traversed by taxis, to model the intelligence of taxi drivers and the properties of dynamic road networks. The essential components that will be discussed are a Web-services-based data collection approach then, a Variance-Entropy-Based Clustering approach is devised to estimate the distribution of travel time between two landmarks in different time slots. Based on this graph, we design a two-stage routing algorithm to compute the practically fastest route. In our existing system static (Dynamic)-path and not update the rout.
Route Plan Evaluation Method for Personalised Passenger Information Service
TRANSPORT, 2015
Due to changing expectations of characteristics of mobility demands, public transportation users increasingly require a reduction of both the preparation and travel time, an easier and more pleasant travelling experience as well as route plans based on reliable data. Both international and domestic research is widely concerned with route planning optimization. Exemplary assistance applications are already in operation, but they are only semi-occasionally and slightly personalized. Consequently, there is potential for significant research and development in this area. Our developed method and algorithm evaluates the routes based on the personalised user settings and in this way, the ideal routes can be determined. User preferences are represented in evaluation criteria. The algorithm also manages network modifications and often-changing user preferences. The novelty of our algorithm lies in the more realistic evaluation of the routes appreciably considering both the exact physical pr...
2016 IEEE Global Communications Conference (GLOBECOM), 2016
Route guidance and navigation services have been widely attracting researchers and application developers due to the serious problems of traffic congestion and the ceaseless need to improve the driving experience. Motivated by such driving concerns, this paper proposes a real-time, dynamic route guidance system with the main focus on the driver safety and satisfaction. As a unique feature compared to other existing systems, the proposed driver-centric route guidance (DCRG) system considers the driver behavior in the route guidance process for the sake of boosting the safety levels on roads. The system also considers the driver preferences targeting a personalized satisfying driving experience. As most drivers prefer traversing the fastest and healthiest route to their destination, the DCRG system takes into account as well the real-time traffic and road conditions while guiding drivers towards their targeted destinations. Performance evaluation of DCRG shows significant improvements in the travel time, on-road safety, and preference satisfaction levels compared to the shortest and fastest route guidance schemes.