scispace - formally typeset
Search or ask a question

How to list POI/AOI as trip purpose around highway? 


Best insight from top research papers

To list Points of Interest (POIs) or Areas of Interest (AOIs) as trip purposes around highways, one can utilize methods like enhancing POI categorization through text classification and identifying entrances for POIs in large land areas using cluster analysis . Another approach involves associating POIs with intersections or highway exits within a predetermined travel time, calculating travel time and distance to each POI, and storing this data in an electronic database for reference . Additionally, displaying relevant POIs based on a user's travel purpose by associating a travel category with the trip destination and showing POIs corresponding to that category can be effective for trip planning around highways . These methods leverage machine learning techniques, GPS data, and navigational instructions to enhance trip planning accuracy and efficiency.

Answers from top 5 papers

More filters
Papers (5)Insight
The method involves storing POIs with category labels, entering a destination, associating a travel category, and displaying relevant POIs based on the trip purpose, such as around a highway.
The POIs of highway transportation can be classified as stationary (S-POI) and mobile (M-POI) points, including logistic centers, ports, gas stations, and more, serving as trip purposes around highways.
The paper proposes methods to identify and associate Points of Interest (POIs) within a set travel time from an intersection or highway exit, storing their travel time and distance in a database.
The study enhances trip purpose inference around highways by improving POI categorization with text classification and identifying entrances for large land area POIs using machine learning techniques.
The study enhances trip purpose inference around highways by improving POI categorization with text classification and identifying entrances for POIs from cluster analysis using machine learning techniques.

Related Questions

How to list POI/AOI around highway?4 answersTo list Points of Interest (POIs) or Areas of Interest (AOIs) around a highway, one can utilize innovative methods proposed in the research papers. Firstly, the wPOI framework can be employed to calculate weather forecasts at POIs, aiding in recommending safe and suitable locations based on weather conditions. Additionally, the SNN query can be utilized to find the safest paths to POIs, considering road safety and avoiding potential risks like crime incidents or protests. Furthermore, the unsupervised system design for obtaining polygon representations of POIs can help in identifying and clustering various POIs around the highway based on address locations and texts, significantly expanding the list of potential POIs. By integrating these approaches, one can effectively compile a comprehensive list of POIs and AOIs around a highway while prioritizing safety and relevance.
How is travel challenged by interstate highways?5 answersInterstate highways present challenges to travel in various ways. Highway congestion, particularly in urban areas, poses a significant challenge to efficient travel. Work zones during highway construction contribute to nonrecurring congestion, impacting safety and mobility for users. Freeway traffic management remains a challenge despite advancements in Intelligent Transportation Systems, with strategies like controlling freeway inflow/outflow being crucial. Dust storms on interstate highways can lead to accidents due to visibility loss and traction issues, influenced by factors like wind and soil type. Additionally, motorists on Interstate highways face increased vulnerability to weather hazards, with tornadoes impacting vehicles and necessitating improved warning systems and preparedness measures. These challenges highlight the complexity of ensuring safe and efficient travel on interstate highways.
How do highways benefit road users?5 answersHighways benefit road users in various ways. They offer improved route planning through connected highway sensor systems, enhancing safety and efficiency for drivers of autonomous and semi-autonomous vehicles. Additionally, vehicular social networks like SOR facilitate social interactions among users on the road, providing timely and localized infotainments through low-cost inter-vehicle communications. Furthermore, highway networks result in net benefits to society by reducing travel time and minimizing delays due to construction and maintenance operations, thus saving costs for users. Moreover, methodologies and software tools have been developed to calculate road user costs, perform economic analyses, and aid decision-makers in selecting the most desirable alternatives for highway improvements. Overall, highways offer users improved connectivity, safety, efficiency, and cost-effectiveness.
How does the aesthetic of a road affect tourism and the economy?5 answersThe aesthetic of a road can have implications for tourism and the economy. Aesthetics play a role in the interpretation of signs within a landscape, and aesthetic modes such as the beautiful, the sublime, and the picturesque are important for creating meaning during tourism. In the context of road development, economic benefits can accrue from reduced transport and travel costs, which can have a positive impact on reducing poverty. However, the economic benefits of roads may not always be straightforward, as they can have unintended consequences that may negate some of the benefits. Additionally, the appearance of hotels and commercial environments is increasingly characterized by a form of commodified enchantment, which aims to create novelty, surprise, and excitement, reflecting capitalism's drive to turn pleasure and comfort into profit. Therefore, the aesthetic of a road can influence tourist visits, the local economy, and the overall experience of tourism.
What is Route survey?5 answersRoute survey is a process of exploring and planning routes in various contexts such as spatial data management, location-based social services, power line exploration, mine warfare, and geodesic survey. It involves techniques and apparatus to improve signal reception, remove noise, detect current signals, and digitize signals for analysis and display. Route survey aims to improve the accuracy of exploration, minimize surrounding influences, and counter potential threats. It also involves the use of change detection to compare previous and recent scans, classify objects, and reduce unnecessary searches. Additionally, route survey utilizes optimization methods and spline approximation to determine the curve and shape of the desired route.
What is the road map for GIS?5 answersA road map for GIS is a representation of the road network within a geographic information system. It provides detailed information about the roads, including their layout, connectivity, and attributes. The road map is essential for various applications, such as vehicle navigation systems, autonomous driving, and transportation planning. Different methods and technologies are used to generate road maps for GIS. One approach involves using geographic information system (GIS) databases and applying the constrained Delaunay triangular network method to extract road network models. Another method utilizes open street map (OSM) data sources, which provide editable geographic information for road network modeling. Additionally, a GIS can be created by correcting the moving track of a vehicle with GPS using reference points and coordinates. There are also systems and methods that automatically detect accurate positions of points on a road map and connect them to update road centerline data. Overall, road maps for GIS play a crucial role in analyzing and managing road networks for socio-economic development.

See what other people are reading

Is 12 imformants is ok in perception research topuc?
5 answers
Using multiple informants in perception research can help mitigate perceptual biases. Research suggests that perceptual differences between key informants can arise due to various factors like role differences, education gap, communication gap, and the dynamic nature of integration processes. Perception plays a crucial role in interpreting information in fields like medical imaging, where subjective notions of image quality impact diagnostic success. In the context of medical education, residents perceive research experience as essential for career development, with factors like education, encouragement, and time allocation influencing research participation. Understanding how mental representations are formed, especially in visual perception, highlights the importance of prior knowledge and symmetry constraints in making successful inferences. Therefore, involving 12 informants in perception research can provide a more comprehensive understanding by capturing diverse perspectives and minimizing individual biases.
What limitations do call detail records (CDR) have for mobility research in Germany?
5 answers
Call Detail Records (CDRs) pose limitations for mobility research in Germany due to issues such as low spatial resolution, the presence of hidden visits, and spatio-temporal sparsity. CDR data lacks precise user location identification, and hidden visits, where users travel without being recorded, hinder the extraction of reliable mobility information. While CDRs can estimate radii of gyration and important locations, they lose some location details, emphasizing the challenge of obtaining accurate long-term position estimations. Addressing these limitations requires innovative methodologies like data fusion approaches to infer hidden visits and improve the understanding of individual mobility patterns based on telecommunication records. These challenges highlight the need for advanced techniques to enhance the utility of CDRs in mobility research in Germany.
What are the current advancements in the Pointcloud Machine Learning field?
5 answers
Current advancements in Pointcloud Machine Learning include innovative approaches like PointGPT, which extends the GPT concept to point clouds, achieving state-of-the-art performance on various tasks. Additionally, PointNeXt has shown significant improvements by incorporating neighborhood point features and implementing weight averaging strategies, enhancing classification accuracies on real-world datasets. Furthermore, PointStack introduces multi-resolution feature learning and learnable pooling to extract high-semantic point features effectively, enabling the representation of both global and local contexts of point clouds while comprehending their structure and shape details. These advancements address challenges related to disorder properties, low information density, and task gaps, pushing the boundaries of feature learning and classification accuracy in the Pointcloud Machine Learning domain.
How to find noisy features in tabular dataset?
5 answers
To identify noisy features in a tabular dataset, various techniques can be employed. One approach involves injecting noise into the dataset during training and inference, which can help detect noisy features and improve model robustness. Another method is to utilize unsupervised feature selection algorithms designed to handle noisy data, such as the Robust Independent Feature Selection (RIFS) approach, which separates noise as an independent component while selecting the most informative features. Additionally, a novel methodology called Pairwise Attribute Noise Detection Algorithm (PANDA) can be used to detect noisy attributes by focusing on instances with attribute noise, providing valuable insights into data quality for domain experts. By leveraging these techniques, noisy features in tabular datasets can be effectively identified and addressed to enhance the overall data quality and model performance.
Is precordial lead placement has the capability to detect coronary artery disease?
5 answers
Precordial lead placement plays a significant role in detecting coronary artery disease (CAD). Studies have shown that utilizing innovative techniques like the SafOne precordial lead ECG can aid in accurate CAD detection by reducing errors in lead placement and improving efficiency. Additionally, research suggests that the use of ultrashort one-lead ECG recordings, including noisy inputs from smartwatches, in combination with advanced algorithms like autoencoder neural networks and Support Vector Machines, can effectively detect CAD. Moreover, investigations focusing on the acoustic approach for CAD screening highlight the importance of ideal microphone placement on the chest to enhance accuracy in CAD detection, with specific positions above the apex of the heart showing promising results. Overall, proper precordial lead placement techniques are crucial for enhancing the detection of CAD, especially when combined with innovative technologies and analysis methods.
What are Models of Trauma Transmission?
5 answers
Models of trauma transmission encompass various theoretical frameworks that explain the intergenerational transfer of trauma-related experiences. These models delve into the mechanisms through which trauma can be passed from one generation to the next, impacting parent-child relationships and attachment dynamics. The dissociative mechanism proposed by Main and Hesse, along with Lyons Ruth's model of emotional communication breakdown, are prominent theories in understanding the transmission of disorganized attachment from parents to children. Additionally, the exploration of trauma transmission within specific contexts, such as post-genocide Rwanda, sheds light on the determinants and pathways of PTSD transmission, emphasizing the complex interplay between parental trauma, attachment, and child traumatization.
What are Models of intergenerational Trauma Transmission?
5 answers
Models of intergenerational trauma transmission encompass various pathways through which trauma can be passed down from one generation to the next. These models include the impact of parental trauma on dysfunctional attachment patterns in the next generation, the intersection of PTSD in parents and parent-infant attachment, the role of storytelling in addressing intergenerational trauma in families, the transgenerational transmission of trauma observed in families with historical trauma experiences, and the psychotherapeutic exploration of trauma transmission dynamics between a Holocaust survivor and his son. These models highlight the complex interplay of biological, psychological, and sociological factors in understanding how trauma can be transmitted across generations.
How accurate is google earth mapping?
5 answers
Google Earth mapping accuracy varies based on the specific application and methodology used. Studies have shown high accuracy levels in mapping built-up areas when combining Synthetic Aperture Radar (SAR) data of Sentinel-1 and Multispectral Instrument (MSI) images of Sentinel-2 through Google Earth Engine (GEE) platform, achieving an overall accuracy of 97%. Additionally, the use of bidirectional reflectance distribution function (BRDF) signatures captured by multi-angle observation data has shown moderate improvements in land cover classification accuracy, with an overall validation accuracy increase of up to 4.9%. Furthermore, in mapping alpine grassland aboveground biomass, machine learning models like deep neural network (DNN) have demonstrated high accuracy, with DNN outperforming other models with an R2 of 0.818. These findings collectively suggest that Google Earth mapping can be highly accurate when utilizing advanced techniques and data sources.
What are the most common methods used for breast cancer detection and classification?
5 answers
The most common methods used for breast cancer detection and classification include various machine learning algorithms such as Naïve Bayes, K-nearest neighbors (KNN), Support Vector Machine (SVM), Random Forest, Logistic Regression, Multilayer Perceptron (MLP), fuzzy classifier, and Convolutional Neural Network (CNN). Additionally, logistic regression, decision tree, and random forest classifiers have been implemented successfully for breast cancer classification, with the random forest classifier showing a high accuracy of 98%. Machine learning, particularly Multilayer Perceptron (MLP), is widely utilized for breast cancer detection due to its ability to classify data accurately, with an accuracy rate of 85%. Furthermore, support vector machine (SVM) has been identified as a top-performing classifier, achieving an accuracy of 97.7% in breast cancer prediction.
How does sentiment analysis contribute to organizational decision-making?
5 answers
Sentiment analysis plays a crucial role in organizational decision-making by providing insights into stakeholders' opinions and emotions. It helps organizations understand the sentiments expressed towards their products, services, or initiatives, enabling them to make informed decisions for improvement. By utilizing sentiment analysis tools, decision-makers can analyze vast amounts of data, such as executive board meeting minutes or student feedback, to gauge the overall sentiment - whether positive, neutral, or negative. This analysis aids in identifying areas for enhancement, enhancing customer satisfaction, and ultimately impacting the organization's brand image. Through machine learning and deep learning approaches, sentiment analysis enhances accuracy and performance, providing valuable insights for strategic decision-making in various sectors.
How many teenagers in the Philippines have access to pornography?
5 answers
Approximately 80% of Filipino children have experienced online sexual exploitation, making the issue prevalent among teenagers in the Philippines. The easy access to the internet, coupled with a lack of knowledge about data privacy, exposes younger generations to online adult content and abuse. Moreover, reports on commercial sexual exploitation (CSE) in the Philippines indicate that up to 2% of adolescents and young women are subjected to such exploitation, highlighting the broader issue of sexual exploitation affecting teenagers in the country. These findings underscore the urgent need for comprehensive internet safety education programs to protect teenagers from accessing harmful content and falling victim to exploitation online.