Data Sources Analysis for Sustainable Trip Planner Development for Riga City

In today’s daily traveller world, not only the time and money became important, but climate change and pandemic raised the importance of safety and sustainability of future trip plans. In order to provide such a wide coverage for a variety of important information, a sustainable trip planner needs to receive a lot of data from a variety of differentiated data sources. Provided review of related works shows that a lot of started activities in this aspects gives all of us promises and hope that available Big Data sources will be wisely used in order to bring added value not only to individual travellers, but also society, the transportation services will become better structured and information will be easily available for smart and safe decision making, that gradually will increase life quality. The study’s main goal is analysis of open data sources for the trip planner development. Authors analysed availability of data for Riga transport system and data usage for sustainable trip planner.

A genetic-based pairwise trip planner recommender system

The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study.

A Genetic-Based Pairwise trip Planner Recommender System

The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study.

USER PERCEPTION USABILITY OF THE MALAYSIAN MOBILE TRIP PLANNER PLATFORM: A REVIEW STUDY

Tourism is important due to its benefits and role as a commercial activity that creates demand and growth in many industries. Tourism is vital not only in increasing economic activities but also in generating additional employment and revenue. Malaysia has increased its efforts in diversifying the economy and decreasing its dependence on exports by promoting increased tourism in the country. For this reason, the use of information technology in tourism has increased. Hence, mobile applications and applet tools play an important role among Internet users. This research reviews 24 standardised usability questionnaires in the literature for choosing the appropriate usability instrument. Then, this study investigated the usability measurement scales of the well-known mobile application, Malaysia Trip Planner, on the basis of Nielsen’s usability principles. Therefore, this study could provide future research directions and recommendations on improving the attributes of such applications.

DYNAMIC TRIP PLANNER FOR PUBLIC TRANSPORT USING GENETIC ALGORITHM

This paper reports the development of a public transport trip planner to help the urban traveller in planning and preparing for his commute using public transportation in the city. A Genetic Algorithm (GA) approach that handles real-time Global Positioning Systems (GPS) data from buses of the Metropolitan Transport Corporation (MTC) in Chennai City (India) has been used to develop the planner. The GA has been shown to provide good solutions within the problem’s computation time constraints. The developed trip planner has been implemented for static network data first and subsequently extended to use real-time data. The “walk mode” and Chennai Mass Rapid Transit System (MRTS) have also been included in the geospatial database to extend the route-planner’s capabilities. The algorithm has subsequently been segmented to speed up the prediction process. In addition, a temporal cache has also been introduced during implementation, to handle multiple queries generated simultaneously. The results showed that there is promise for scalability and citywide implementation for the proposed real-time route-planner. The uncertainty and poor service quality perceived with public transport bus services in India could potentially be mitigated by further developments in the route-planner introduced in this paper.

Internet GIS-Based Multimodal Public Transport Trip Planning Information System for Travelers in Lithuania

The main purpose of this research is to present the developed VINTRA system, a comprehensive solution to a fully developed public transit system in Lithuania, and it is very important in encouraging travelers to use public transport. VINTRA is not simply a trip planner; it is capable of planning multimodal public transport trips, using different parameters in public transport trip planning. This system has the functionality to create and edit public transport route trajectories and to edit and calculate timetables according to the distance between stops. This research presents the public transport trip planning parameters procedure of the calculated walking route directions, integrated with the calculation results of public transit routes, as well as combining visualization in digital maps. This paper also discusses how route-planning systems could perform data exchange based on General Transit Feed Specification and how assessment of the public transport trip planning results, compared to the VINTRA system created with Google, was performed.