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How to define starting point and trip purpose of each trip on highway? 


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To define the starting point and trip purpose of each trip on a highway, various methodologies and models have been proposed in the research. The determination of trip purpose is crucial for tasks in intelligent transportation systems and urban planning . Trip purpose prediction can be enhanced by leveraging GPS data, land use data, and machine learning methods for accurate and dynamic inference . Additionally, the analysis of trip start modes, such as cold starts and hot starts, based on factors like trip purpose and time of day, can provide insights into emission modeling and transportation planning . By utilizing clustering algorithms, decision trees, and relevant features, researchers have successfully detected trips and inferred trip purposes, aiding in transportation modeling . These approaches collectively contribute to defining the starting point and trip purpose of each trip on highways.

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Starting points can be defined using GPS data, while trip purpose can be predicted using a Hidden Markov Model incorporating GPS and land use data for highway trips.
The paper proposes using DBscan clustering algorithm and decision tree with relevant features to automate trip purpose detection, including defining starting points and trip purposes on highways.
The paper proposes a Dual-Flow Attentive Network with Feature Crossing (DACross) to infer chained trip purposes, considering spatial correlations and unequal importance within trip chains.
Trip starts on highways can be classified as cold or hot starts based on engine temperature. Trip purpose significantly influences start mode, with urban area size and time of day also playing roles.
Not addressed in the paper.

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