Trip Planning Research Articles

Exploring association between perceived importance of travel/traffic information and travel behaviour in natural disasters: A case study of the 2011 Brisbane floods

A sound understanding of travellers’ behavioural changes and adaptation when facing a natural disaster is a key factor in efficiently and effectively managing transport networks at such times. This study specifically investigates the importance of travel/traffic information and its impact on travel behaviour during natural disasters. Using the 2011 Brisbane flood as a case study, survey respondents’ perceptions of the importance of travel/traffic information before, during, and after the flood were modelled using random-effects ordered logit.A hysteresis phenomenon was observed: respondents’ perceptions of the importance of travel/traffic information increased during the flood, and although its perceived importance decreased after the flood, it did not return to the pre-flood level. Results also reveal that socio-demographic features (such as gender and age) have a significant impact on respondents’ perceptions of the importance of travel/traffic information. The roles of travel time and safety in a respondent’s trip planning are also significantly correlated to their perception of the importance of this information.The analysis further shows that during the flood, respondents generally thought that travel/traffic information was important, and adjusted their travel plans according to information received. When controlling for other factors, the estimated odds of changing routes and cancelling trips for a respondent who thought that travel/traffic information was important, are respectively about three times and seven times the estimated odds for a respondent who thought that travel/traffic information was not important. In contrast, after the flood, the influence of travel/traffic information on respondents’ travel behaviour diminishes. Finally, the analysis shows no evidence of the influence of travel/traffic information’s on respondents’ travel mode; this indicates that inducing travel mode change is a challenging task.

The application and impact of gamification funware on trip planning and experiences: the case of TripAdvisor’s funware

Despite the wide diffusion of gamification in business, limited research exists investigating the application and impacts of gamification. As the gamification effects are heavily dependent on the context of its implementation, this study used the design of the TripAdvisor’s funware for investigating the use and the impacts of gamification in a specific tourism context. After reviewing the literature for understanding how to design funwares that can lead to desired experiential and behavioural user outcomes, the paper discusses the way in which the TripAdvisor designed its funware for motivating the travellers to engage with its website and for enhancing the travellers’ online experiential values and trip planning processes. Data from TripAdvisor users were also collected for investigating the impacts of the TripAdvisor’s funware design on the following users’ outcomes: experiential values gained by using TripAdvisor; impacts of TripAdvisor on travellers’ trip planning processes; impacts of Tripadvisor on trip experiences. Finally, the paper discusses the implications of the findings to researchers, designers and tourism organisations.

Individual Behavioural Models for Personal Transit Pre-trip Planners

This paper presents the results of an in-progress research project aiming to define an advanced trip planner for transit networks. Starting from the description of user needs and logical architecture of the trip planner, the paper describes the module to support the user with pre-trip information based on his/her personal preferences. In particular the theoretical aspects of the individual, instead of user group (aggregate), path choice modelling used to support path choice set individuation, path utility calculation and user preference learning process are defined. The theoretical framework has been applied and tested through some experiments carried out on the public transport network of the metropolitan area of Rome.

Quality Assessment of Open Realtime Data for Public Transportation in the Netherlands

Modern technologies in the public transportation sector offer a variety of opportunities to advance solutions for every-day use, such as trip planning. Oftentimes, buses and metro lines do not adhere to their schedules, e.g. due to traffic congestion or overcrowding. In such cases, realtime information on the transit system may be used to find faster alternative routes. This paper analyses the quality of a realtime data set that is the first of its kind in Europe, since it covers a whole country, i.e. the Netherlands. The data are published in the General Transit Feed Specification (GTFS)-realtime format as a live-feed. These interoperable feeds, if shared with the public by transit agencies, can be used by developers to write customized applications for public transit users, e.g. through integration with the OpenTripPlanner (OTP) routing platform.

Hurried or Risk-adverse Travelers: who will Pay More for Multimodal Information?

By enabling the use of multimodal information by travelers, public policy can improve the use of soft travel modes and reduce the negative externalities of car use. However, such an eco-innovative multimodal information platform might only be efficient if travelers are willing to use it and pay for its development and update. To evaluate the relevance of the creation of a multimodal platform in the Plateau de Saclay – an area located 20km south of Paris, very concerned by congestion – this paper measures workers’ willingness to pay (WTP) for such a platform from a survey conducted in this area. A multinomial logit with unobserved heterogeneity is estimated to determine marginal WTP for the services that could potentially be provided by the platform. The respective effects of risk aversion and value of travel time on this marginal WTP are also investigated. Some gender differences in the evaluation of the platform and its trip planning are also apparent: men's WTP increases with their value of travel time and decreases with their risk aversion while women's WTP is mainly influenced by the constraints they may face when commuting

Rural Intelligent Public Transportation System Design

In order to improve the level of intelligence, availability, convenience, information and humanization of rural public transportation systems, they are more willing to use modern information and communicative technologies. In addition to management services, intelligent transportation systems can provide passengers, drivers and other institutions with other services such as trip planning, tracking and so forth. In this paper the authors have attempted to present a comprehensive design of rural ITS based on cloud and grid computing, RFID, GPS, GIS, etc. through e-commerce and particularly m-commerce in order to improve the rural transportation management and presentation of user-centric services. Also according to the design, intercity transportation services to passengers are re-engineered. The results show proposed design with distribution infrastructure improves the performance of e-commerce and ISs in transportation domain. The system designed on this paper regardless of the possible challenges could efficiently cover the problems of rural transportation of newly developing countries.

Survey of Cross-Regional Intermodal Passenger Travel

This paper presents an investigation of the mode choice behavior of cross-regional commuters in the greater Toronto and Hamilton area of Ontario, Canada. A survey of cross-regional intermodal passenger travel (called SCRIPT) was developed and conducted during the spring and the fall of 2014. SCRIPT collects data on respondents' revealed preference in daily commuting trips to pivot each respondent's mode choice stated preference experiment separately. An innovative multimodal trip planner tool was developed to generate feasible travel options for each stated preference experiment with information on household auto ownership level, proximity to transit, work start time, and total travel time from home to work, as well as predeveloped discrete choice models to identify access station locations of intermodal travel modes. The stated preference experiments were based on the D-efficient design technique. The survey used 1,203 randomly selected cross-regional commuters. The paper reports on a mode choice model estimated by the revealed preference data portion of the survey to verify the validity of the survey design, sampling procedure, and data quality. An empirical model provides insight into cross-regional commuters' mode choice behavior.

An Energy Management Strategy for a DC Distribution System for Power System Integration of Plug-In Electric Vehicles

This paper proposes an energy management strategy (EMS) for a dc distribution system for power system integration of plug-in electric vehicles (PEVs). The dc distribution system is intended to integrate electric vehicles in a parking lot with an ac grid through bidirectional dc–dc converters (battery chargers) and a central voltage-sourced converter. Using an online constrained optimization algorithm, the proposed EMS manages the power flow within the dc system. Thus, the PEV owners can charge or discharge their batteries based on the state-of-charge of the batteries and their upcoming trip plans. The EMS offers two energy exchange options to the PEV owners: 1) the fast energy exchange option for the owners wishing to minimize the energy exchange time; and 2) the optimal energy exchange option for the owners intend to either minimize their costs of charging or maximize their revenues through selling their stored energy. The proposed EMS seamlessly handles all charging/discharging requests from the PEV owners with different options and, at the same time, it takes into account the power demand and power generation limits of the ac grid to preclude under-voltage, over-voltage, and reverse power flow issues. Various energy exchange scenarios are simulated to demonstrate the effectiveness of the proposed EMS.

사용자 평점 기반의 사전 체험형 여행계획 자동생성 알고리즘

본 논문에서는 사용자 및 전문가 평점에 기반하여 여행계획을 자동으로 생성하여 여행에 앞서 효율적인 스토리텔링 여행을 체험할 수 있도록 지원하는 연구를 진행하였다. 효율적인 여행계획의 자동생성을 위하여, 입력된 전문가 평점 및 사용자들의 평점들을 토대로 우선순위를 바꿔 나타낼 수 있도록 하였으며, 점진적 계층 방식을 이용하여 생성된 스토리텔링 기반의 추천코스를 통합하여 전체 여행계획 생성이 가능하도록 하였다. 이렇게 생성된 여행계획은 일반 동영상 및 파노라마 동영상을 통하여 실제 위치를 체험해 볼 수 있도록 하여 사용자들에게 여행지에 대한 기대감을 높일 수 있도록 하였다. 또한, 휴리스틱 기법을 이용하여 시스템의 사용이 많아질수록 보다 효율적인 여행계획 생성이 이루어질 수 있도록 하였다. 연구된 내용은 안드로이드 운영체제 환경에서 구현 및 테스트하여 새로운 방식의 여행계획 자동생성에 효율성을 입증하였다. 본 연구에서는 파노라마 동영상을 통한 체험 방식의 도입과 사용자 평점 기반의 효율적인 여행계획의 자동구성방법을 제시하여, 내 외국인의 여행계획 구성에 대한 활용뿐만 아니라 궁극적으로 관광활성화에도 기여할 수 있을 것이라 기대된다. The purpose of this study is to develope an algorithm which generates trip plans based on rating points of travel app users and travel experts to help potential travellers experience their desired destinations in advance. This algorithm uses the above rating points and the gradually created hierarchy to generate the most preferred and efficient trip courses. Users can go through video clips or panoramic VR videos of the actual destinations from their trip plans generated by the algorithm which may add excitement to their actual trips. With our heuristic methods, the more users input their ratings, the better trip plans can be generated. This algorithm has been tested on android OS and proven efficient in generating trip plans. This research introduces a way to experience travel destinations with panoramic VR video and proposes the algorithm which generates trip plans based on users' ratings. It is expected to be useful for travellers' trip planning and to contribute growth in the travel market.

Analyzing how travelers choose scenic routes using route choice models

Finding a scenic route between two locations is a common trip planning task, in particular for tourists and recreational travelers. For the automated computation of a scenic route in a trip planning system it is necessary to identify which attributes of a route and its surroundings are associated with attractive scenery. This study uses a route choice model, more specifically a Path Size Logit (PSL) model, to identify the relevant attributes and their relative importance. Three hypotheses are formulated and tested with three PSL models to understand the effects of different attributes on scenic route selection. The set of chosen scenic routes are based on various VGI (Volunteered Geographic Information) data that have been extracted for California as a study region. The results identify several variables of the surrounding environment as significant contributors to route scenery after controlling for road type.

Range search on tuples of points

Range search is a fundamental query-retrieval problem, where the goal is to preprocess a given set of points so that the points lying inside a query object (e.g., a rectangle, or a ball, or a halfspace) can be reported efficiently. This paper considers a new version of the range search problem: Several disjoint sets of points are given along with an ordering of the sets. The goal is to preprocess the sets so that for any query point q and a distance δ, all the ordered sequences (i.e., tuples) of points can be reported (one per set and consistent with the given ordering of the sets) such that, for each tuple, the total distance traveled starting from q and visiting the points of the tuple in the specified order is no more than δ. The problem has applications in trip planning, where the objective is to visit venues of multiple types starting from a given location such that the total distance traveled satisfies a distance constraint. Efficient solutions are given for the fixed distance and variable distance versions of this problem, where δ is known beforehand or is specified as part of the query, respectively.

Abstract A75: Racial and ethnic differences in travel time to mammography facilities in 5 US cities

Abstract Introduction: Screening by mammography is one component of an overall strategy to identify early breast cancer and reduce breast cancer mortality. While women in rural areas may be at a disadvantage in accessing mammography, urban residents who depend on public transportation can also face barriers to mammography services, despite generally shorter travel distances. We examined travel time using public transportation from census tracts to mammography facilities in Boston, Philadelphia, San Antonio, San Diego and Seattle. Methods: Data sources included: U.S. 2010 census data used to identify women 40 years of age and older, and race/ethnicity groups by census tract in each city; American Community Survey data to determine household availability of a private vehicle; NAVTEQ street network for each metropolitan area; and FDA's certification and inspection records of U.S. mammography facilities. Using the public transportation option on Google Trip Planner we obtained the travel time from the centroid of each census tract to the nearest mammography facility. A standard trip time of 11:00 am on weekdays was used for all searches. We calculated tract percentages of households with no vehicle availability and percentage blacks, whites, Asians and Hispanics for each metropolitan area. Median travel times were obtained by summing travel time by vehicle access and race/ethnicity across all census tracts in the metropolitan area. Finally, we calculated overall mammography capacity ratios (number of machines * estimated number of mammograms per machine / population of women 40 years of age and older) for each city. Results: Overall, median travel times to the closest mammography facilities by public transportation were 21 minutes in Philadelphia, 27 minutes in Boston, 33 minutes in Seattle, 34 minutes in San Antonio, and 35 minutes in San Diego. Across all cities, travel time increased as availability of a private vehicle increased indicating a suburban effect. Focusing on census tracts with low private vehicle availability we saw little differences in median travel time by race/ethnicity in Philadelphia (13 to 14 minutes) and Boston (14 to 15 minutes) while in Seattle, whites had the shortest travel time (23 minutes) compared to blacks, Asians, and Hispanics (30 minutes). In San Antonio and San Diego, blacks had the longest travel times (33 minutes and 28 minutes) compared to the other groups. Maximum travel times in tracts with low vehicle availability ranged from 86 minutes to over two hours. There was less variability in travel times for census tracts classified as having high vehicle availability. Conclusion: Our results reveal a geographic pattern of wide-ranging travel times within and across the five metropolitan areas with regard to low-vehicle-availability populations. The Eastern cities of Boston and Philadelphia, with well-developed train systems, had travel times to the nearest mammography facility that were almost 10 to 15 minutes (21% to 39%) shorter than the western cities of San Diego, San Antonio and Seattle. Across all metropolitan areas in the low vehicle availability category, white census tracts tended to have among the shortest travel times. In the Western cities only black census tracts consistently had longer travel times than whites while Hispanic and Asian travel times varied relative to that of whites. Although mammography capacity was adequate at the metropolitan level, we found maximum travel times of more than two hours for residents of some census tracts having low private vehicle availability. Citation Format: Shannon Graham, Brian Lewis, Barry Flanagan, Meg Watson, Lucy Peipins. Racial and ethnic differences in travel time to mammography facilities in 5 US cities. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr A75. doi:10.1158/1538-7755.DISP13-A75

The Design of a Map for Tourists to Engage in Circuitous Movements

Circuitous tourism helps to deepen the understanding of local cultures; however, the encouragement of circuitous movement by tourists through design is still under exploration. This study investigated the cultural area of Lukang in Taiwan through think-aloud protocols, behavioral observation, and circuitous movement planning to understand how tourists pre-plan and use the circuitous movement indicated on a site map. We then suggested a new map design that encourages circuitous movement and compared its effect on pre-planning and touring with that of the old map. This study found that in using maps for wayfinding people must rest. Site maps have always been a tool for tourists to plan their trips. When planning trips, tourists with maps relied on their past experiences; however, the existence of resting areas affected the planning of trips. Adding resting area icons effectively increased the touring periods and the number of attractions visited. Information on resting areas helped tourists independently arrange periods of repose, which aided planning and experiencing local specialties. Information on resting is thus an important factor for circuitous tours.

On-Road Study of Fatigue Management Strategies in Long-Haul Truck Drivers

The current study investigated what strategies long-haul truck drivers use to mitigate fatigue at the wheel. A group of 52 truck drivers participated in the study in which drivers’ fatigue at the wheel was measured by a well-validated self-rating scale (the Karolinska Sleepiness Scale) and the use of fatigue countermeasures by a diary for a period of two consecutive workweeks including day and night-time trips. Results showed that the drivers more frequently used fatigue countermeasures while fatigued at the wheel but most of these countermeasures, with the exception of caffeine, can be regarded as inefficient (e.g., opening a window). The results indicate that long-haul truck drivers respond to fatigue at the wheel but the countermeasures they use are not optimal. It is likely that in addition to driver fatigue management training changes in shift and trip planning practices and sleeping facilities at rest stops are needed to improve the situation.

Querying visible points in large obstructed space

Querying visible points is a fundamental problem in computational geometry and spatial databases. With the development of new applications such as trip planning and nearest neighbors, querying visible points plays a key role in obstacle space and the result can be further used such as defining the shortest path. Thereby, efficiently finding the result is essentially important. However, the performance of current methods decrease substantially for large datasets. To solve the problem, we proposes a new and fast algorithm to find visible points for an arbitrary query location inside a large polygon containing obstacles. The method is based on polygon triangulation. By decomposing the polygon into a set of triangles, we manage the polygon by organizing triangles in an efficient way instead of maintaining a large number of vertices. We propose a data structure to partition the searching space into several parts, each of which is independently processed. Afterwards, by recursively calling a method we search visible points by accessing triangles and return the result in a progressive way. Through a theoretical analysis, assuming the polygon contains N vertices in total, the time complexity of our algorithm is O(N), improving the existing method O(N l o g N). We prove the correctness of the algorithm and analyze the space complexity, which is O(N). The technique is extended to return visible points less than a threshold distance to the query location. Using both synthetic and real datasets, we perform extensive experiments to test our algorithm and demonstrate its efficiency and effectiveness. Visible points are efficiently processed in a large obstacle space with over one million vertices. Experimental results show that our technique gains more than one order of magnitude speedup compared to competitive methods using large datasets.

Trip Planner Over Probabilistic Time-Dependent Road Networks

Recently, the management of transportation systems has become increasingly important in many real applications such as location-based services, supply chain management, traffic control, and so on. These applications usually involve queries over spatial road networks with dynamically changing and complicated traffic conditions. In this paper, we model such a network by a probabilistic time-dependent graph (PT-Graph), whose edges are associated with uncertain delay functions . We propose a useful query in the PT-Graph, namely a trip planner query (TPQ), which retrieves trip plans that traverse a set of query points in PT-Graph, having the minimum traveling time with high confidence. To tackle the efficiency issue, we present the pruning methods time interval pruning and probabilistic pruning to effectively rule out false alarms of trip plans. Furthermore, we design a pre-computation technique based on the cost model and construct an index structure over the pre-computed data to enable the pruning via the index. We integrate our proposed pruning methods into an efficient query procedure to answer TPQs. Through extensive experiments, we demonstrate the efficiency and effectiveness of our TPQ query answering approach.

The influence of terrorism risk perception on purchase involvement and safety concern of international travellers

Using a sample of 600 international tourists travelling in Portugal, Spain and Italy, this study identifies key issues related with terrorism, risk perception, involvement and safety concerns of international tourists. A structural equation model reveals that tourists are motivated to acquire information about terrorism in the media, revealing attention to and interest in news regarding this topic, which in turn influences directly their risk perception. This risk perception influences directly the tourist’s involvement in trip planning, specifically information seeking before and during the trip. Tourists’ risk perception and involvement finally influences their safety concern. Discussion centres on the implications of this model for both theory and tourism management strategies. Last, recommendations are proposed to tourism service and destination managers and promoters regarding ways to deal with terrorism and tourists’ safety concerns.

Leveraging multi-criteria customer feedback for satisfaction analysis and improved recommendations

Travel websites and online booking platforms represent today’s major sources for customers when gathering information before a trip. In particular, community-provided customer reviews and ratings of various tourism services represent a valuable source of information for trip planning. With respect to customer ratings, many modern travel and tourism platforms—in contrast to several other e-commerce domains—allow customers to rate objects along multiple dimensions and thus to provide more fine-granular post-trip feedback on the booked accommodation or travel package. In this paper, we first show how this multi-criteria rating information can help to obtain a better understanding of factors driving customer satisfaction for different segments. For this purpose, we performed a Penalty-Reward contrast analysis on a data set from a major tourism platform, which reveals that customer segments significantly differ in the way the formation of overall satisfaction can be explained. Beyond the pure identification of segment-specific satisfaction factors, we furthermore show how this fine-granular rating information can be exploited to improve the accuracy of rating-based recommender systems. In particular, we propose to utilize user- and object-specific factor relevance weights which can be learned through linear regression. An empirical evaluation on datasets from different domains finally shows that our method helps us to predict the customer preferences more accurately and thus to develop better online recommendation services.

A new outlook on map use in social sciences and humanities research

Since their first appearance, maps increasingly secured their irreplaceable role in our civilization. As the human society develops, so is cartography to become more useful than ever. Transforming from their designated role as a tool of positioning or navigating, maps have become a second language to visualize real world, and a useful tool in scientific research. Particularly, recent decades have experienced the creative use of map in social sciences and humanities researches that yield interesting results. However, in Viet Nam this is still a relatively new approach that has not yet received the attention it deserves. This paper systematically illustrates how maps can be applied in social sciences and humanities researches, as such suggesting how researchers in social sciences and humanities can employ maps in a greater variations and more effective, creative ways. Researches done in social sciences and humanities (in which maps had been used) accompanied with indepth-interviews are closely observed, studied and analyzed to identify how maps are being used in different stages of research. To enhance ease and flexibility of map usage in research, we have presented all the situations according to map functionalities. It is concluded that maps can be used for pre-arrival to site analysis, studysite selection (multi-criteria analysis function), field trip planning (navigating function). Maps could also be used as primary data collection tool in associated with questionnaires, indepth interviews and focus groups, in order to explore spatial aspect of collected data (multi-criteria and multi-time analysis functions). Last but not least, map use is a great way to illustrate spatial research information in a more creative and visualized way.

‘Informal Travel’: A New Conceptualization of Travel Patterns?

In transportation, informal transport refers mainly to the use of paratransit services in the developing world. In this paper we argue that informal travel may include, in addition to mode and users, also other travel pattern elements, such as trip planning, structure, purpose, and destination. Each of these can be placed along an axis ranging from formal manifestations to informal ones, thus creating a ‘formality scale’. Moreover, these elements may be combined in numerous ways, creating a multitude of travel patterns that may be placed all along the formality scale. After providing a definition of formal, semi-formal, and informal travel and characterizing travel patterns according to the formality scale we identify population groups which exemplify semi-formal and informal travel patterns. Next, we analyze the 2009 US National Household Travel Survey, which suggests informal travel may be growing. This leads to a discussion on various factors that might affect travel formality. Most notably, the growing use of information and communication technologies may be shifting travel toward the informal end of the axis. In turn, this might affect trip symmetry, which may result in further effects on the transportation system.