Identifying intercity freight trip ends of heavy trucks from GPS data

06/22/2021
by   Yitao Yang, et al.
0

The intercity freight trips of heavy trucks are important data for transportation system planning and urban agglomeration management. In recent decades, the extraction of freight trips from GPS data has gradually become the main alternative to traditional surveys. Identifying the trip ends (origin and destination, OD) is the first task in trip extraction. In previous trip end identification methods, some key parameters, such as speed and time thresholds, have mostly been defined on the basis of empirical knowledge, which inevitably lacks universality. Here, we propose a data-driven trip end identification method. First, we define a speed threshold by analyzing the speed distribution of heavy trucks and identify all truck stops from raw GPS data. Second, we define minimum and maximum time thresholds by analyzing the distribution of the dwell times of heavy trucks at stop location and classify truck stops into three types based on these time thresholds. Third, we use highway network GIS data and freight-related points-of-interest (POIs) data to identify valid trip ends from among the three types of truck stops. In this step, we detect POI boundaries to determine whether a heavy truck is stopping at a freight-related location. We further analyze the spatiotemporal characteristics of intercity freight trips of heavy trucks and discuss their potential applications in practice.

READ FULL TEXT

page 13

page 14

research
06/18/2021

Identifying intracity freight trip ends from heavy truck GPS trajectories

Intracity heavy truck freight trips are basic data in city freight syste...
research
04/14/2023

An elaborated pattern-based method of identifying data oscillations from mobile device location data

In recent years, passively collected GPS data have been popularly applie...
research
02/14/2018

Inference for Continuous Time Random Maxima with Heavy-Tailed Waiting Times

In many complex systems of interest, inter-arrival times between events ...
research
06/19/2019

Estimating Commuting Patterns from High Resolution Phone GPS Data

The rise of location positioning technologies has generated enormous vol...
research
08/24/2019

A statistical framework for measuring the temporal stability of human mobility patterns

Despite the growing popularity of human mobility studies that collect GP...
research
04/05/2018

Inferring transportation modes from GPS trajectories using a convolutional neural network

Identifying the distribution of users' transportation modes is an essent...
research
04/19/2019

Identifying Points of Interest and Similar Individuals from Raw GPS Data

Smartphones and portable devices have become ubiquitous and part of ever...

Please sign up or login with your details

Forgot password? Click here to reset