scholarly journals Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips

2021 ◽  
Vol 11 (10) ◽  
pp. 4523
Author(s):  
Diego O. Rodrigues ◽  
Guilherme Maia ◽  
Torsten Braun ◽  
Antonio A. F. Loureiro ◽  
Maycon L. M. Peixoto ◽  
...  
Keyword(s):  
New York ◽  
User Experience ◽  
Waiting Times ◽  
Routing Algorithm ◽  
Transportation Mode ◽  
Main Research ◽  
Traffic Conditions ◽  
Transportation Modes ◽  
Spatio Temporal ◽  
Time Price

Millions of individuals rely on urban transportation every day to travel inside cities. However, it is not clear how route parameters (e.g., traffic conditions, waiting times) influence users when selecting a particular route option for their trips. These parameters play an important role in route recommendation systems, and most of the currently available applications omit them. This work introduces a new hybrid-multimodal routing algorithm that evaluates different routes that combine different transportation modes. Hybrid-multimodal routes are route options that might consist of more than one transportation mode. The motivation to use different transportation modes is to avoid unpleasant trip segments (e.g., traffic jams, long walks) by switching to another mode. We show that the possibility of planning a trip with different transportation modes can lead to improvement of cost, duration, and quality of experience urban trips. We outline the main research contributions of this work, as (i) an user experience model that considers time, price, active transportation (i.e., non-motorized transport) acceptability, and traffic conditions to evaluate the hybrid routes; and, (ii) a flow clustering technique to identify relevant mobility flows in low-sampled datasets for reducing the data volume and allow the execution of the analytical evaluation. (i) uses a Discrete Choice Analyses framework to model different variables and estimate a value for user experience in the trip. (ii) is a methodology to aggregate mobility flows by using Spatio-temporal Clustering and identify the most relevant of these flows using Curvature Analysis. We evaluate the proposed hybrid-multimodal routing algorithm with data from the Green and Yellow Taxis of New York, Citi Bike NYC data, and other publicly available datasets; and, different APIs, such as Uber and Google Directions. The results reveal that selecting hybrid routes can benefit passengers by saving time or reducing costs, and sometimes both, when compared to routes using a single transportation mode.

scholarly journals Real-time spatio-temporal event detection on geotagged social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yasmeen George ◽  
Shanika Karunasekera ◽  
Aaron Harwood ◽  
Kwan Hui Lim
Keyword(s):  
New York ◽  
Social Media ◽  
Event Detection ◽  
Detection System ◽  
Time And Space ◽  
Social Media Data ◽  
Event Time ◽  
Spatio Temporal ◽  
Geographical Space ◽  
Media Data

AbstractA key challenge in mining social media data streams is to identify events which are actively discussed by a group of people in a specific local or global area. Such events are useful for early warning for accident, protest, election or breaking news. However, neither the list of events nor the resolution of both event time and space is fixed or known beforehand. In this work, we propose an online spatio-temporal event detection system using social media that is able to detect events at different time and space resolutions. First, to address the challenge related to the unknown spatial resolution of events, a quad-tree method is exploited in order to split the geographical space into multiscale regions based on the density of social media data. Then, a statistical unsupervised approach is performed that involves Poisson distribution and a smoothing method for highlighting regions with unexpected density of social posts. Further, event duration is precisely estimated by merging events happening in the same region at consecutive time intervals. A post processing stage is introduced to filter out events that are spam, fake or wrong. Finally, we incorporate simple semantics by using social media entities to assess the integrity, and accuracy of detected events. The proposed method is evaluated using different social media datasets: Twitter and Flickr for different cities: Melbourne, London, Paris and New York. To verify the effectiveness of the proposed method, we compare our results with two baseline algorithms based on fixed split of geographical space and clustering method. For performance evaluation, we manually compute recall and precision. We also propose a new quality measure named strength index, which automatically measures how accurate the reported event is.

scholarly journals An Eco-Routing Algorithm for HEVs Under Traffic Conditions

2020 ◽  
Vol 53 (2) ◽  
pp. 14242-14247
Author(s):  
Arthur Le Rhun ◽  
Frédéric Bonnans ◽  
Giovanni De Nunzio ◽  
Thomas Leroy ◽  
Pierre Martinon
Keyword(s):  
Routing Algorithm ◽  
Traffic Conditions

scholarly journals Lost in transportation: Information measures and cognitive limits in multilayer navigation

2016 ◽  
Vol 2 (2) ◽  
pp. e1500445 ◽  
Author(s):  
Riccardo Gallotti ◽  
Mason A. Porter ◽  
Marc Barthelemy
Keyword(s):  
New York ◽  
Transportation Networks ◽  
Transportation Systems ◽  
Traditional View ◽  
Multimodal Transportation ◽  
Large Cities ◽  
Amount Of Information ◽  
Information Measures ◽  
Transportation Modes ◽  
Metropolitan Networks

Cities and their transportation systems become increasingly complex and multimodal as they grow, and it is natural to wonder whether it is possible to quantitatively characterize our difficulty navigating in them and whether such navigation exceeds our cognitive limits. A transition between different search strategies for navigating in metropolitan maps has been observed for large, complex metropolitan networks. This evidence suggests the existence of a limit associated with cognitive overload and caused by a large amount of information that needs to be processed. In this light, we analyzed the world’s 15 largest metropolitan networks and estimated the information limit for determining a trip in a transportation system to be on the order of 8 bits. Similar to the “Dunbar number,” which represents a limit to the size of an individual’s friendship circle, our cognitive limit suggests that maps should not consist of more than 250 connection points to be easily readable. We also show that including connections with other transportation modes dramatically increases the information needed to navigate in multilayer transportation networks. In large cities such as New York, Paris, and Tokyo, more than 80% of the trips are above the 8-bit limit. Multimodal transportation systems in large cities have thus already exceeded human cognitive limits and, consequently, the traditional view of navigation in cities has to be revised substantially.

Multi-Head Spatio-Temporal Attention Mechanism for Urban Anomaly Event Prediction

2021 ◽  
Vol 5 (3) ◽  
pp. 1-21
Author(s):  
Huiqun Huang ◽  
Xi Yang ◽  
Suining He
Keyword(s):  
New York ◽  
Experimental Studies ◽  
Attention Mechanism ◽  
City Management ◽  
Temporal Attention ◽  
Spatial Correlations ◽  
Time Step ◽  
Event Prediction ◽  
Spatio Temporal ◽  
Prediction Approach

Timely forecasting the urban anomaly events in advance is of great importance to the city management and planning. However, anomaly event prediction is highly challenging due to the sparseness of data, geographic heterogeneity (e.g., complex spatial correlation, skewed spatial distribution of anomaly events and crowd flows), and the dynamic temporal dependencies. In this study, we propose M-STAP, a novel Multi-head Spatio-Temporal Attention Prediction approach to address the problem of multi-region urban anomaly event prediction. Specifically, M-STAP considers the problem from three main aspects: (1) extracting the spatial characteristics of the anomaly events in different regions, and the spatial correlations between anomaly events and crowd flows; (2) modeling the impacts of crowd flow dynamic of the most relevant regions in each time step on the anomaly events; and (3) employing attention mechanism to analyze the varying impacts of the historical anomaly events on the predicted data. We have conducted extensive experimental studies on the crowd flows and anomaly events data of New York City, Melbourne and Chicago. Our proposed model shows higher accuracy (41.91% improvement on average) in predicting multi-region anomaly events compared with the state-of-the-arts.

scholarly journals The Influence of Demographic Matters and Interest on Passenger’s Switching Intention: Evidence of Travelers in the Developing Country Indonesia

2021 ◽  
Vol 15 (1) ◽  
pp. 122-132
Author(s):  
Icuk Rangga Bawono ◽  
Ratno Purnomo ◽  
Cris Kuntadi ◽  
Apriani Kartika Rahayu
Keyword(s):  
Response Rate ◽  
Jel Classification ◽  
Education Level ◽  
Switching Behavior ◽  
Future Research ◽  
Transportation Mode ◽  
Classification Code ◽  
Transportation Modes ◽  
Quantitative Descriptive ◽  
Potential Customers

Background: After the official operation of the Jakarta-Cikampek elevated highway, a socio-demographic picture of Indonesian travel passengers, as well as their interest in switching transportation preferences was provided. This elevated highway shortened travel time and discouraged users from changing to other transportation modes. This study is likely to become a future research foundation for the switching behavior of passengers. Objective: This study aims to analyze demographic factors and interests on passenger’s switching of transportation preference. Methods: A total of 720 questionnaires were distributed to land transportation passengers at concentrated points with a response rate of 89.17% and 642 valid answers. The obtained data were analyzed using quantitative descriptive techniques with cross tab methods. Results: The results showed that age, education level, and type of work influenced the desire of passengers to switch transportation modes, as opposed to gender. Most of the passengers interested in using land modes, such as the highway, were dominated by intercity between provinces travel buses and refused to change to other means of transportation. Meanwhile, passengers that used rented cars tended to switch to other forms of transportation. Conclusion: This research is useful and acts as a reference for managers of each transportation mode to set high priorities for particular consumers based on detailed socio-demographics to retain or attract new potential customers. JEL Classification Code: D12, L92, R41.

SOCIOLOGICAL ASSESSMENT OF THE STUDY OF PATIENTS ‘ OPINIONS ABOUT THE DRUG SUPPLY SYSTEM IN RUSSIA

2021 ◽  
Vol 9 (2) ◽  
pp. 12-17
Author(s):  
E.A. Telnova ◽  
A.V. Belova ◽  
A.A. Zagoruichenko
Keyword(s):  
Comparative Analysis ◽  
Research Methods ◽  
Significant Role ◽  
Waiting Times ◽  
Age Groups ◽  
Supply System ◽  
Drug Supply ◽  
Main Research ◽  
Law System ◽  
Popu Lation

This article analyzes the results of a sociological survey, which con- firmed the relevance of the issues of accessibility of providing medicines to various categories of citizens. The purpose of this study was to study the attitude of citizens to the existing system, as well as to identify the strengths and weaknesses of preferential security. The main research methods were: the method of studying and generalizing experience; comparative analysis; sociological survey; statistical. According to the presented data, the distribution of answers to questions is determined in % depending on the total number of respondents, including in the dynamics for the analyzed period (2019-2021). This study served as a tool for studying the key problems in obtaining preferential medicines (waiting times for a doctor to issue a prescription, the absence of a prescription in a pharmacy, the refusal of a doctor to issue medicines, etc.). Thus, the results of the conducted sociological survey showed that the LAW system plays a significant role in the structure of healthcare. At the same time, first of all, it is necessary to carry out additional work with various age groups of the popu- lation in the framework of providing information about the possibilities of the additional preferential security system.

Some Experiences of Puebla's Entrepreneurs in New York

2016 ◽  
pp. 408-430
Author(s):  
Tomás Milton Muñoz Bravo ◽  
Lizbeth Alicia González Tamayo ◽  
Margarita Herrera Avilés
Keyword(s):  
New York ◽  
Social Entrepreneurs ◽  
Main Research ◽  
Research Questions ◽  
Political Entrepreneurs ◽  
State Area

For decades, New York, and the tri-State area, has become a major attraction for Poblano immigrants seeking opportunities. Some of these immigrants, not only have worked to send remittances to their families in Mexico, but also have made their way to become productive, social and political entrepreneurs in the communities of destination and/or origin. But what are the conditions that have allowed certain Poblanos to become economic, political and social entrepreneurs in the so-called Big Apple and its surroundings? What have been the challenges they have had to overcome? And what is their relationship with their origin communities in Mexico? These are the main research questions of this study part.

A Practioner-Centered Assessment of a User-Experience Framework

2007 ◽  
pp. 96-127
Author(s):  
Peter Wright ◽  
John McCarthy ◽  
Lisa Meekison
Keyword(s):  
Content Analysis ◽  
User Experience ◽  
Internet Shopping ◽  
Action Research Project ◽  
Thematic Content Analysis ◽  
Sequential Structure ◽  
Spatio Temporal ◽  
Participative Action Research ◽  
Ongoing Programme

In this paper we outline a relational approach to experience, which we have used to develop a practitioner-oriented framework for analysing user experience. The framework depicts experience as compositional, emotional, spatio-temporal, and sensual, and as intimately bound up with a number of processes that allow us to make sense of experience. It was developed and assessed as part of a participative action research project involving interested practitioners. We report how these practitioners used the framework, what aspects of experience they felt that it missed, and how useful they found it as a tool for evaluating Internet shopping experiences. A thematic content analysis of participants’ reflections on their use of the framework to evaluate Internet shopping experiences revealed some strengths and some weaknesses. For example, certain features of the framework led participants to reflect on aspects of experience that they might not otherwise have considered e.g. the central role of anticipation in experience. The framework also captured aspects of experience that relate to both the sequential structure of the activity and its subjective aspects. However it seemed to miss out on the intensity of some experiences and participants sometimes found it difficult to distinguish between some of the sense making processes, for example, interpreting and reflecting. These results have helped to refine our approach to deploying the framework and have inspired an ongoing programme of research on experience-centered design.

scholarly journals Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM

2019 ◽  
Vol 11 (19) ◽  
pp. 5525 ◽  
Author(s):  
Jinjun Tang ◽  
Fan Gao ◽  
Fang Liu ◽  
Wenhui Zhang ◽  
Yong Qi
Keyword(s):  
New York ◽  
Travel Demand ◽  
Geographical Area ◽  
Temporal Characteristic ◽  
Temporal Variations ◽  
Road Density ◽  
Transit System ◽  
Factors Affecting ◽  
Urban Travel ◽  
Spatio Temporal

Taxis are an important part of the urban public transit system. Understanding the spatio-temporal variations of taxi travel demand is essential for exploring urban mobility and patterns. The purpose of this study is to use the taxi Global Positioning System (GPS) trajectories collected in New York City to investigate the spatio-temporal characteristic of travel demand and the underlying affecting variables. We analyze the spatial distribution of travel demand in different areas by extracting the locations of pick-ups. The geographically weighted regression (GWR) method is used to capture the spatial heterogeneity in travel demand in different zones, and the generalized linear model (GLM) is applied to further identify key factors affecting travel demand. The results suggest that most taxi trips are concentrated in a fraction of the geographical area. Variables including road density, subway accessibility, Uber vehicle, point of interests (POIs), commercial area, taxi-related accident and commuting time have significant effects on travel demand, but the effects vary from positive to negative across the different zones of the city on weekdays and the weekend. The findings will be helpful to analyze the patterns of urban travel demand, improve efficiency of taxi companies and provide valuable strategies for related polices and managements.

A Congestion Controlled and Load Balanced Selection Strategy for Networks on Chip

2020 ◽  
Vol 11 (1) ◽  
pp. 1-14
Author(s):  
Ashima Arora ◽  
Neeraj Kumar Shukla
Keyword(s):  
Traffic Flow ◽  
Free Path ◽  
Routing Algorithm ◽  
Experimental Results ◽  
Selection Strategy ◽  
Selection Function ◽  
Networks On Chip ◽  
Traffic Conditions ◽  
On Chip ◽  
Selection Of

For an on-chip router, the suitability of a particular routing algorithm relies on its selection of the best possible output paths. For representing congestion, the selection function of a routing algorithm uses an appropriate metric. The preferred selection metric will thus help in deciding the congested free path for any incoming flit. In this article, the fuzzy-based selection function is designed by using a cumulative flit count as a global metric of traffic estimation. The strategy provides an added advantage of effectively utilizing the links and thus regulates the traffic flow by keeping track of buffer usage and flits flow history simultaneously. The experimental results obtained under different traffic conditions, shows the proposed scheme outperforms other traditional, fuzzy based schemes in terms of both performance and power requirements.

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