Analysis of trip generation rates in residential commuting based on mobile phone signaling data
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In this paper, mobile phone signaling data are first processed to extract information such as the trip volume and spatial distribution from the starting point to the termination point. This information is then used to identify the residential and employment locations of users. Next, multiple Thiessen polygons based on cell towers are aggregated into Traffic Analysis Zones (TAZs) to minimize differences between the actual cell tower coverage and the theoretical coverage. Then, based on TAZ cluster analysis involving transport accessibility and commuting population density, multiple stepwise regression is applied to obtain the commuting trip production rates and attraction rates for overall residential land and each subdivided housing type during the peak morning hours. The obtained commuting trip generation rates can be directly applied to local transport analysis models. This paper suggests that as information and data sharing continue, mobile phone signaling data will become increasingly important for use in future trip rate research.Keywords:
Mobile phone
Trip generation
현재 통행발생량 산정 등 교통계획 정보의 생성 체계가 기존 조사 중심 체계에서 외부 데이터를 접목하여 조사 비용을 저감시키고 정확성을 높이는 방향으로 전환되고 있다. 우리나라는 인구보다 많은 휴대전화가 보급되어 있기 때문에 이로부터 구축된 무선통신 자료는 교통계획에 매우 유용한 정보를 줄 수 있을 것이다. 본 연구에서는 이동통신사에서 제공하는 수도권 지역 성 연령별 유동인구 자료로부터 교통계획의 중요한 자료인 통행발생량을 산정하기 위한 방안을 제시하고 이를 KTDB의 통행발생량과 상관성 분석을 통하여 자료의 활용 가능성을 확인하였다. 그 결과 무선통신 자료를 이용한 통행발생량 추정은 기존의 KTDB에서 구축한 직접 조사 방식 기반에 의한 결과와 매우 높은 상관관계를 가지는 것으로 분석되었다. The recent trend in transportation planning information is to reduce traffic survey costs and enhance accuracy by using and converging various sources of external data. In Korea, mobile phone data can help generate useful transportation planning information, thanks to the universal use of mobile phones, which are present in a number greater than that of the population. This paper addresses measures to derive trip generation information from mobile phone data and verifies the value of the system for practical use by correlation analysis with KTDB trip generation data. The results show that trip generation information produced by mobile phone data correlates with existing (KTDB) trip generation data.
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Trip generation
Mobile broadband
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This paper introduces a set of articles about how transportation planners need better tools for estimating trip generation, and to develop better tools we need more data collection, especially methods that capture passenger trips by personal vehicles, transit, walking, and bicycling, as well as freight trips. With such data in hand, researchers would be able to develop models that both produce more accurate estimates of vehicle trips and generate trip estimates for other passenger modes and for freight. Such estimates would help to ensure adequate provision for these modes and not just for cars.
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Guidelines for trip and parking generation in the United States come mainly from the Institute of Transportation Engineers (ITE). However, their trip and parking manuals focus on suburban locations with limited transit and pedestrian access. This study aims to determine how many fewer vehicle trips are generated at transit-oriented developments (TODs), and how much less parking is required at TODs, than ITE guidelines would suggest. Our sample of TODs is small, which limits our ability to generalize. However, the five cases selected for this study are more or less exemplary of the D variables, at least in comparison with US norms. They are characterized by land-use diversity and pedestrian-friendly designs. They minimize distance to transit, literally abutting transit stations. They have varying measures of destination accessibility to the rest of the region via transit. Three have progressive parking policies, which fall under the heading of demand management. Two have high residential densities, and one has a high intensity of commercial development. Simply put, our case study TODs create significantly less demand for parking and driving than do conventional suburban developments. With one exception, peak parking demand in these TODs is less than one half the parking supply guideline in the ITE Parking Generation manual. Also, with one exception, vehicle trip generation rates are about half or less of what is predicted in the ITE Trip Generation Manual. Automobile mode shares are as low as one quarter of all trips, with the remainder being mostly transit and walk trips.
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Transit-oriented development
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The trip generation phase of urban transportation planning is one of the most important stages of the travel demand forecasting process. Trip generation helps to estimate vehicular trips generated by a parcel of land or zone from a knowledge of the land use properties of the land or zone. This article has examined trip generation of 15 post offices in Cincinnati, Ohio. The data on trips that have destinations at the post offices were collected manually during the business hours of a typical weekday. The average, minimum, and maximum daily and peak-hour vehicle trip rates were calculated for 9 independent variables selected by this study. Regression analysis was performed to examine the strength of association between the vehicle trip generation and the independent variables.
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There is currently limited data on urban, multimodal trip generation at the individual site level. This lack of data limits the ability of transportation agencies to assess development impacts on the transportation system in urban and multimodal contexts. This project sought to begin addressing this gap by developing and testing a protocol for collecting trip generation by mode at the site level. The report provides a comprehensive review of previous research and develops and defines a data collection protocol for site and context data. The report documents the results of a pilot data collection that tests the protocol. The results of the pilot data collection are compared to the predicted impacts based on the industry standard, the Institute of Transportation Engineers (ITE) Trip Generation Manual, and to six alternative methods, all of which pivot from ITE’s data. None of the existing methods reliably predict the field data. The report identifies next steps for the District Department of Transportation (DDOT) and other agencies to take to improve multimodal trip generation estimation. To that end, a field-guide for future data collection, based on this pilot, is included as an appendix.
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Abstract The Coronavirus disease pandemic has disrupted survey systems globally and especially in low- and middle-income countries. Phone surveys started being implemented at a national scale in many places that previously had limited experience with them. As in-person data collection resumes, the experience gained provides the grounds to reflect on how phone surveys may be incorporated into survey and data systems in low- and middle-income countries. Reviewing evidence and experiences from before and during the pandemic, the paper provides guidance on the scope of and considerations for using phone surveys for agricultural data collection and the integration of phone interviews with in-person data.
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A park-and-ride (P&R) is a parking facility with connections to public transit service. The ITE Trip Generation Manual, ninth edition, presented trip generation rates separately for P&R facilities with bus and light rail service; however, the small sample sizes (maximum sample size was six studies) and outdated trip generation rates (between the 1980s and the 2000s) may not be an accurate representation for transportation engineers and planners to estimate the traffic impacts of P&R facilities correctly. This paper describes a comprehensive trip generation study that was performed at 40 regional transportation district P&R facilities in the Denver, Colorado, region with regional bus and light rail transit service. Similar to the ITE manual, this study estimated and produced weighted-average trip rates and regression equations. The sample size and variation in the data collected in this study can be used as a good representation for computing trip generation locally or for being applied to cities with similar transit systems and P&R design criteria.
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There is a growing need for quantitative traffic-estimating tools to improve pedestrian transportation safety, access, and mobility. A sketch-plan method is introduced to estimate peak-hour pedestrian trips for crossings at intersections (node) and parallel sidewalk-midblock (link) locations. This tool integrates pedestrian travel into routine trip-estimating by applying standard traffic data to quantify pedestrian trips. The method presented is based on access-egress mode trip generation and applies peak vehicle-per-hour turning movements, transit vehicle or passenger counts, and walk and bike counts or projections to produce total peak pedestrian-per-hour (pph) trips. A previous method used trip rates based on land use to generate pph trips. However, that model is 20 years old, requires detailed land use data, and does not distribute and assign pedestrian trips. The following sketch-plan method was developed in a case-study of a suburban growth corridor in Plattsburgh, New York. Sample applications of pedestrian trip-generation estimates are presented to illustrate how pedestrian travel-demand projections, in addition to vehicular traffic forecasting, can support the adoption of balanced facility treatments to meet the mobility and safety needs of all modes of transportation.
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The Institute of Transportation Engineers (ITE) guidelines serve as the most widely used reference for trip and parking generation estimates for any new development in the U.S.A. However, recent empirical studies question the efficacy of ITE guidelines in forecasting trip and parking generation in transit-oriented developments (TODs). Following the methodology of studies on seven TODs across the U.S.A., this study focuses on Dallas (TX), as a more auto-oriented American city, to explore the trip and parking generation at Mockingbird TOD. It finds that, with the exception of Station Park in Salt Lake City (which is really a transit-adjacent development rather than a TOD), the Mockingbird TOD has the lowest walk mode share (13.6%), the lowest bike mode share (0.22%), the lowest bus transit mode share (1.09%), and by far the lowest rail transit mode share (5.9%) of all the other seven TODs. Similarly, the Mockingbird TOD ranks first in relation to the driving mode share, with about 80% of its daily trips generated by driving. This is almost twice as many driving trips as the average of the other six TODs, which makes Mockingbird an auto-oriented TOD located in an auto-oriented region where more than 96% of commuting trips are by automobile. Still, the total automobile trip generation rate in Mockingbird is about 12% lower than the ITE estimates. Similarly, while the parking supply in Mockingbird TOD is less than 48% of the ITE recommended supply rate, its peak parking occupancy is only about 55% of the TOD supply.
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Transit-oriented development
Occupancy
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Twin cities
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