Global Positioning System–Assisted Prompted Recall Household Travel Survey to Support Development of Advanced Travel Model in Jerusalem, Israel

2011 ◽  
Vol 2246 (1) ◽  
pp. 16-23 ◽  
Author(s):  
Marcelo G. Simas Oliveira ◽  
Peter Vovsha ◽  
Jean Wolf ◽  
Yehoshua Birotker ◽  
Danny Givon ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Global Positioning ◽  
Household Travel

Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey

2003 ◽  
Vol 1854 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Jean Wolf ◽  
Marcelo Oliveira ◽  
Miriam Thompson
Keyword(s):  
Travel Time ◽  
Global Positioning System ◽  
Travel Demand ◽  
Positioning System ◽  
Gps Technology ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Time Estimates ◽  
Global Positioning ◽  
Household Travel

Trip underreporting has long been a problem in household travel surveys because of the self-reporting nature of traditional survey methods. Memory decay, failure to understand or to follow survey instructions, unwillingness to report full details of travel, and simple carelessness have all contributed to the incomplete collection of travel data in self-reporting surveys. Because household trip survey data are the primary input into trip generation models, it has a potentially serious impact on transportation model outputs, such as vehicle miles of travel (VMT) and travel time. Global Positioning System (GPS) technology has been used as a supplement in the collection of personal travel data. Previous studies confirmed the feasibility of applying GPS technology to improve both the accuracy and the completeness of travel data. An analysis of the impact of trip underreporting on modeled VMT and travel times is presented. This analysis compared VMT and travel time estimates with GPS-measured data. These VMT and travel time estimates were derived by the trip assignment module of each region's travel demand model by using the trips reported in computer-assisted telephone inter views. This analysis used a subset of data from the California Statewide Household Travel Survey GPS Study and was made possible through the cooperation of the metropolitan planning organizations of the three study areas (Alameda, Sacramento, and San Diego, California).

Understanding Trip Misreporting Behavior Using Global Positioning System-Assisted Household Travel Survey

2014 ◽  
pp. 91-103
Author(s):  
Xia Jin ◽  
Hamidreza Asgari ◽  
Md Sakoat Hossan
Keyword(s):  
Global Positioning System ◽  
Econometric Models ◽  
Positioning System ◽  
Indicator Variable ◽  
Travel Information ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Global Positioning ◽  
Household Travel ◽  
Household Travel Surveys

Trip misreporting has been a persistent and well-known problem with household travel surveys. Global Positioning System (GPS)-based prompted-recall method provides the opportunity to capture reliable and accurate travel information from the respondents. By comparing the GPS sample with the diary sample, this chapter investigates the pattern and magnitude of trip misreporting behavior, with a focus on shopping and discretionary tours within 15-minutes trip distance. Econometric models are developed to account for trip misreporting in tour frequency models by introducing a sample-indicator variable. The interaction effects of the sample-indicator variable with various personal and household variables are tested, which reflect the influences of these personal and household attributes on trip misreporting behavior. A number of personal and household characteristics showed significant impacts on misreporting, including driver license status, race, person type, household type, household income, and number of household vehicles.

Aplikasi Pemosisi Lokal Berbasis Android Dengan Menggunakan GPS

INTI TALAFA ◽  
2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Yaman Khaeruzzaman
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Database Server ◽  
Global Positioning

Seiring dengan pesatnya kemajuan teknologi saat ini, kebutuhan manusia menjadi lebih beragam, termasuk kebutuhan akan informasi. Tidak hanya media informasinya yang semakin beragam, jenis informasi yang dibutuhkan juga semakin beragam, salah satunya adalah kebutuhan informasi akan posisi kita terhadap lingkungan sekitar. Untuk memenuhi kebutuhan itu sebuah sistem pemosisi diciptakan. Sistem pemosisi yang banyak digunakan saat ini cenderung berfokus pada lingkup ruang yang besar (global) padahal, dalam lingkup ruang yang lebih kecil (lokal) sebuah sistem pemosisi juga diperlukan, seperti di ruang-ruang terbuka umum (taman atau kebun), ataupun dalam sebuah bangunan. Sistem pemosisi lokal yang ada saat ini sering kali membutuhkan infrastruktur yang mahal dalam pembangunannya. Aplikasi Pemosisi Lokal Berbasis Android dengan Menggunakan GPS ini adalah sebuah aplikasi yang dibangun untuk memenuhi kebutuhan pengguna akan informasi lokasi dan posisi mereka terhadap lingkungan di sekitarnya dalam lingkup ruang yang lebih kecil (lokal) dengan memanfaatkan perangkat GPS (Global Positioning System) yang telah tertanam dalam perangkat smartphone Android agar infrastruktur yang dibutuhkan lebih efisien. Dalam implementasinya, Aplikasi Pemosisi Lokal ini bertindak sebagai klien dengan dukungan sebuah Database Server yang berfungsi sebagai media penyimpanan data serta sumber referensi informasi yang dapat diakses melalui jaringan internet sehingga tercipta sebuah sistem yang terintegrasi secara global. Kata kunci: aplikasi, informasi, pemosisi, GPS.

The Distribution of Hospitality Services in Uyo Urban, Nigeria

2018 ◽  
pp. 137-150
Author(s):  
Violet Bassey Eneyo
Keyword(s):  
Data Collection ◽  
Global Positioning System ◽  
Central Area ◽  
Positioning System ◽  
Nearest Neighbour ◽  
Global Positioning ◽  
Neighbour Analysis

This paper examines the distribution of hospitality services in Uyo Urban, Nigeria. GIS method was the primary tool used for data collection. A global positioning system (GPS) Garmin 60 model was used in tracking the location of 102 hospitality services in the study area. One hypothesis was stated and tested using the nearest neighbour analysis. The finding shows evidence of clustering of the various hospitality services. The tested hypothesis further indicated that hospitality services clustered in areas that guarantee a sustainable level of patronage to maximize profit. Thus, the hospitality services clustered in selected streets in the metropolis while limited numbers were found outside the city’s central area.

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