24,283 research outputs found

    Open source environment to define constraints in route planning for GIS-T

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    Route planning for transportation systems is strongly related to shortest path algorithms, an optimization problem extensively studied in the literature. To find the shortest path in a network one usually assigns weights to each branch to represent the difficulty of taking such branch. The weights construct a linear preference function ordering the variety of alternatives from the most to the least attractive.Postprint (published version

    Route selection for vehicle navigation and control

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    This paper presents an application of neural-fuzzy methodology for the problem of route selection in a typical vehicle navigation and control system. The idea of the primary attributes of a route is discussed, and a neural-fuzzy system is developed to help a user to select a route out of the many possible routes from an origin to the destination. The user may not adopt the recommendation provided by the system and choose an alternate route. One novel feature of the system is that the neural-fuzzy system can adapt itself by changing the weights of the defined fuzzy rules through a training procedure. Two examples are given in this paper to illustrate how the route selection/ranking system can be made adaptive to the past choice or preference of the user. ©2007 IEEE.published_or_final_versio

    A dynamic and scalable user-centric route planning algorithm based on Polychromatic Sets theory

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    Existing navigation services provide route options based on a single metric without considering user's preference. This results in the planned route not meeting the actual needs of users. In this paper, a personalized route planning algorithm is proposed, which can provide users with a route that meets their requirements. Based on the multiple properties of the road, the Polychromatic Sets (PS) theory is introduced into route planning. Firstly, a road properties description scheme based on the PS theory was proposed. By using this scheme, users' travel preferences can be quantified, and then personalized property combination schemes can be constructed according to these properties. Secondly, the idea of setting priority for road segments was utilized. Based on a user's travel preference, all the property combination schemes can be prioritized at relevant levels. Finally, based on the priority level, an efficient path planning scheme was proposed, in which priority is given to the highest road segments in the target direction. In addition, the system can constantly obtain real-time road information through mobile terminals, update road properties, and provide other users with more accurate road information and navigation services, so as to avoid crowded road segments without excessively increasing time consumption. Experiment results show that our algorithm can realize personalized route planning services without significantly increasing the travel time and distance. In addition, source code of the algorithm has been uploaded on GitHub for this algorithm to be used by other researchers

    Toward personalised and dynamic cultural routing: a three-level approach

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    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. The concept relies on three levels of support: 1) programming the tour, i.e. selecting a set of relevant points of interests (POIs) to be included into the tour, 2) scheduling the tour, i.e. arranging the selected POIs into a sequence based on the cultural, recreational and situational value of each, and 3) determining the tour’s travel route, i.e. generating a set of trips between the POIs that the tourist needs to perform in order to complete the tour. The “smart routing” approach intends to enhance the experience of tourists in a number of ways. The first advantage is the system’s ability to reflect on the tourists’ dynamic preferences, for which an understanding of the influence of a tourist’s affective state and dynamic needs on the preferred activities is required. Next, it arranges the POIs together in a way that creates a storyline that the tourist will be interested to follow, which adds to the tour’s cultural value. Finally, the POIs are connected by a chain of multimodal trips that the tourist will have to make, also in accordance with the tourist’s preferences and dynamic needs. As a result, each tour can be personalised in a “smart” way, from the perspective of both the cultural and the overall experience of taking it. We present the building blocks of the “smart routing” concept in detail and describe the data categories involved. We also report on the current status of our activities with respect to the inclusion of a tourist’s affective state and dynamic needs into the preference measurement phase, as well as discuss relevant practical concerns in this regard

    Adaptive route selection for dynamic route guidance system based on fuzzy-neural approaches

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    The objective of this work is to model the driver behaviour in the area of route selection. The research focus on an optimum route search function in a typical in-car navigation system or dynamic route guidance (DRG) system. In this work, we want to emphasize the need to orientate the route selection method on the driver's preference. Each route candidate has a set of attributes. A fuzzy-neural approach is used to represent the correlation of the attributes with the driver's route selection. A recommendation or route ranking can be provided to the driver. Based on a training of the fuzzy-neural net on the driver's choice, the route selection function can be made adaptive to the decision-making of the driver.published_or_final_versio

    A Review of Trip Planning Systems.

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    This report reviews current information provision in all modes of transport and assesses the needs for and benefits of trip planning systems. The feasibility of trip planning systems is discussed given the current state of technology and information availability and supply. The review was stimulated by technological developments in telecommunications and information technology which are providing the possibility of a greatly enhanced quality of information to aid trip planning decisions. Amongst the conclusions reached were the following: Current information provision is considered deficient in many respects. Travellers are often unaware of alternative routes or services and many are unable to acquire adequate information from one source especially for multi-modal journeys. In addition, there is a lack of providing real time information where it is required (bus stops and train stations) and of effective interaction of static and real time information. Most of the projects, which integrate static and dynamic data, are single mode systems. Therefore there is a need for an integrated trip planning system which can inform and guide on all aspects of transport. Trip planning systems can provide assistance in trip planning (before and during the journey) using one or a number of modes of travel, taking into account travellers preferences and constraints, and effectively integrating static and dynamic data. Trip planning systems could adversely affect traffic demand as people who become aware of new opportunities might be encouraged to make more journeys. It could also affect travellers choice as a result of over-saturation of information, over-reaction to predictive information, and concentration on the same 'best' routes. However, it can be argued, based on existing evidence, that such a system can benefit travellers, and transport operators as well as the public sector responsible for executing transport policies. Travellers can benefit by obtaining adequate information to help them in making optimal decisions and reducing uncertainty and stress associated with travel. Public transport operators can benefit by making their services known to customers, leading to increased patronage. Public transport authorities can use the supply of information to execute their transport policies and exercise more control over traffic management

    SMAP: A Novel Heterogeneous Information Framework for Scenario-based Optimal Model Assignment

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    The increasing maturity of big data applications has led to a proliferation of models targeting the same objectives within the same scenarios and datasets. However, selecting the most suitable model that considers model's features while taking specific requirements and constraints into account still poses a significant challenge. Existing methods have focused on worker-task assignments based on crowdsourcing, they neglect the scenario-dataset-model assignment problem. To address this challenge, a new problem named the Scenario-based Optimal Model Assignment (SOMA) problem is introduced and a novel framework entitled Scenario and Model Associative percepts (SMAP) is developed. SMAP is a heterogeneous information framework that can integrate various types of information to intelligently select a suitable dataset and allocate the optimal model for a specific scenario. To comprehensively evaluate models, a new score function that utilizes multi-head attention mechanisms is proposed. Moreover, a novel memory mechanism named the mnemonic center is developed to store the matched heterogeneous information and prevent duplicate matching. Six popular traffic scenarios are selected as study cases and extensive experiments are conducted on a dataset to verify the effectiveness and efficiency of SMAP and the score function
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