Potential of cellular signaling data for time-of-day estimation and spatial classification of travel demand: a large-scale comparative study with travel survey and land use data

2021 ◽  
pp. 1-19
Author(s):  
Mariem Fekih ◽  
Loïc Bonnetain ◽  
Angelo Furno ◽  
Patrick Bonnel ◽  
Zbigniew Smoreda ◽  
...  
Keyword(s):  
Land Use ◽  
Comparative Study ◽  
Large Scale ◽  
Travel Demand ◽  
Cellular Signaling ◽  
Time Of Day ◽  
Spatial Classification ◽  
Travel Survey

Household Travel, Household Characteristics, and Land Use: An Empirical Study from the 1994 Portland Activity-Based Travel Survey

1998 ◽  
Vol 1617 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Xiaoduan Sun ◽  
Chester G. Wilmot ◽  
Tejonath Kasturi
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Land Development ◽  
Data Set ◽  
Travel Survey ◽  
Forecasting Models ◽  
Demand Models ◽  
Residence Location ◽  
Household Travel ◽  
Use Factors

How a household’s travel behavior is influenced by its socioeconomic and land use factors has been a subject of interest for the development of travel demand forecasting models. This study investigates the relative importance of these factors based on the number of household daily trips and vehicle miles traveled (VMT). The travel data used in the study come from the 1994 Portland Activity-Based Travel Survey. In addition to income, vehicle ownership, and household size, other significant factors in household travel have been identified, such as the presence of car phones, dwelling type, home ownership, and even the length of resident’s time in the current home. Most important, this study has qualitatively revealed that land use makes a big difference in household VMT, whereas its impact on the number of daily trips is rather limited. After controlling for the land use variables, such as density and land development balance, it appears that there is little difference in household income distribution among three different land use areas. The household life stage/lifestyle appears to be more relevant to the residence location. And the land use development of the residence location imposes the greatest impact on the household daily VMT. The results from this study provide some empirical evidence to the development of travel forecasting models. Especially by examining the relationship between land use and household travel, the results shed light on how to incorporate land use factors into comprehensive travel demand models that can be used by policy makers in evaluation of alternative land use policies. This study serves as a step toward more comprehensive studies on transportation and land use. The results presented represent a preliminary analysis of an extensive data set; considerable additional analysis is already in process.

Travel Demand Modeling and Conformity Determination: Atlanta Regional Commission Case Study

2002 ◽  
Vol 1817 (1) ◽  
pp. 172-176 ◽  
Author(s):  
Guy Rousseau ◽  
Tracy Clymer
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Mode Choice ◽  
Time Of Day ◽  
Traffic Model ◽  
Demand Model ◽  
Primary Input ◽  
Land Use Model ◽  
Home Based ◽  
Travel Demand Model

The Atlanta Regional Commission (ARC) regional travel demand model is described as it relates to its link-based emissions postprocessor. In addition to conformity determination, an overview of other elements is given. The transit networks include the walk and highway access links. Trip generation addresses trip production, trip attraction, reconciliation of productions and attractions, and special adjustments made for Hartsfield Atlanta International Airport. Trip distribution includes the application of the composite impedance variable. In the mode choice model, home-based work uses a logit function, whereas nonwork uses information from the home-based work to estimate modal shares. Traffic assignment includes preparation of time-of-day assignments. The model assigns single-occupancy vehicles, high-occupancy vehicles, and trucks by using separate trip tables. The procedures can accept or prohibit each of the three types of vehicles from each highway lane. Feedback between the land use model and the traffic model is accounted for via composite impedances generated by the traffic model and is a primary input to the land use model DRAM/EMPAL. The land use model is based on census tract geography, whereas the travel demand model is based on traffic analysis zones that are subareas within census tracts. The ARC model has extended the state of the practice by using the log sum variable from mode choice as the impedance measure rather than the standard highway time. This change means that the model is sensitive not only to highway travel time but also to highway and transit costs.

scholarly journals SPATIAL CLASSIFICATION OF TRANSPORT NETWORKS AND ITS CONNECTION WITH THE TYPOLOGY OF TRANSIT-ORIENTED DEVELOPMENT FOR THE CITIES OF NAJAF AND KUFA OF THE PROVINCE OF NAJAF

2020 ◽  
Vol 5 (9) ◽  
pp. 57-66
Author(s):  
A. Al-jaberi
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Road Network ◽  
Structural Features ◽  
Transit Oriented Development ◽  
Spatial Classification ◽  
The Road ◽  
Different Types ◽  
Gis Environment

Transport is a link between territories with different types of land use in urban areas. At the same time, the improved accessibility associated with the transport network can lead to increased segregation and a change in land use. The article analyzes the road network of the Najaf and Kufa cities, Najaf province, Iraq, in order to identify the spatial classification of roads and streets. Based on the analysis, three main types of roads and streets are identified with respect to their structural features and characteristics: regional, city and district. The dependence of the typology and location of transit-oriented zones on the classification of the road network is indicated. In the process of analyzing the study area, the most optimal points for the practice of transit-oriented development (TOD) are identified, the territories most favorable for the location of transit-oriented zones of regional, city and district significance are introduced, the main characteristics of these zones are given. In order to reach goals, this article includes the collection of data and the creation of a database for land use applying a geographic information systems (GIS) environment. The result of the spatial analysis are five regional nodes, six urban nodes and seven district nodes

Person-Based Micro-Simulation Demand Model for National Long-Distance Travel in the U.S.A.

2020 ◽  
Vol 2674 (6) ◽  
pp. 297-309
Author(s):  
Lei Zhang ◽  
Yijing Lu ◽  
Sepehr Ghader ◽  
Carlos Carrion ◽  
Arash Asadabadi ◽  
...  
Keyword(s):  
Large Scale ◽  
Travel Demand ◽  
Demand Model ◽  
Long Distance ◽  
Fuel Price ◽  
Travel Survey ◽  
Passenger Travel ◽  
Micro Simulation ◽  
Distance Travel ◽  
Long Distance Travel

As the nation and various states engage in funding transportation infrastructure improvements to meet future long-distance passenger travel demand, it is imperative to develop effective and practical modeling methods for analysis of long-distance passenger travel. Evaluating national-level infrastructure improvements requires a reliable analysis tool to model the demand for long-distance travel. The national travel demand model presented in this paper implements a person-level tour-based micro-simulation approach for modeling individuals’ long-distance or national activities in the U.S.A. This paper reviews the model framework, explains the model calibration, and presents applications of the model for policy evaluation and demand prediction. The model was estimated using the latest long-distance travel survey in the U.S.A., which is the 1995 American Travel Survey. As the estimation data is old, and no new long-distance travel survey with appropriate sample size is available to re-estimate the model, model calibration is the solution used to update the model and make it capable of capturing up-to-date travel patterns. Calibrating such a large-scale model can be challenging, because each calibration iteration is very costly. This paper describes the calibration effort conducted on the national long-distance micro-simulation model to showcase how a large-scale travel demand model can be calibrated efficiently. A fuel price scenario is analyzed to show how the national travel demand will change under a national fuel price increase scenario in the future year 2040. Another scenario analysis corresponding to construction of high-speed rail (HSR) is conducted to observe the effects of adding a HSR system to the northeast corridor on travel demand from a national perspective.

scholarly journals Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data

2019 ◽  
Vol 11 (3) ◽  
pp. 643 ◽  
Author(s):  
Jianmin Jia ◽  
Chenhui Liu ◽  
Tao Wan
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Travel Demand ◽  
Cellular Signaling ◽  
Sustainable Transportation ◽  
Charging Station ◽  
Step Model ◽  
Pollutants Emission ◽  
Effective Component ◽  
Charging Stations

Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. This paper presents the approach to locate charging stations utilizing the reconstructed EVs trajectory derived from the Cellular Signaling Data (CSD). Most previous work focused on the commute trips estimated from the number of jobs and households between traffic analysis zones (TAZs). This paper investigated the large-scale CSD and illustrated the method to generate the 24-hour travel demand for each EV. The complete trip in a day for EV was reconstructed through merging the time sequenced trajectory derived from simulation. This paper proposed a two-step model that grouped the charging demand location into clusters and then identified the charging station site through optimization. The proposed approach was applied to investigate the charging behavior of medium-range EVs with Cellular Signaling Data collected from the China Unicom in Tianjin. The results indicate that over 50% of the charging stations are located within the central urban area. The developed approach could contribute to the planning of future charging stations.

scholarly journals Influence of Land Use, Socio-demographic and Travel Attributes on Travel Behaviour in City of Lahore

2019 ◽  
Vol 15 (1) ◽  
pp. 67-74
Author(s):  
Nabeel Shakeel ◽  
Muhammad Jahanzaib
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Multinomial Logit Model ◽  
Travel Behaviour ◽  
Travel Information ◽  
Surrounding Environment ◽  
Joint Influence ◽  
Motorized Transport ◽  
Structured Questionnaire

AbstractTravel behaviour exists in both culture and the surrounding environment. It is crucial to understand it because it helps the policymakers to effectively develop the urban and transportation planning policies. Large scale mobility of people by motorized transport is making our cities polluted and more congested that ultimately affects urban assets. A single paradigm, e.g. land use or socio-demographics, might not clearly demonstrate people’s preferences, it is necessary to take several paradigms in isolation. This study examined the joint influence of multiple attributes that includes land use, socio-demographic and travel information on travel behaviour and particularly preferred travel mode. A structured questionnaire was designed and interviews were conducted to obtain the data. Multinomial logit model (MNL) was applied to estimate the relationships among variables. Furthermore, spatial maps were prepared to highlight the classification of land uses. It was estimated that with the increase in income level people switched from walking to riding a vehicle and most of them prefer to ride a vehicle for longer trips. It was further investigated that people prefer to walk or ride a vehicle in residential and commercial areas. Based on the results, several planning related policies were recommended.

scholarly journals Study on the Spatial Classification of Construction Land Types in Chinese Cities: A Case Study in Zhejiang Province

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 523
Author(s):  
Lin Dong ◽  
Jiazi Li ◽  
Yingjun Xu ◽  
Youtian Yang ◽  
Xuemin Li ◽  
...  
Keyword(s):  
Land Use ◽  
Asset Allocation ◽  
Confusion Matrix ◽  
Zhejiang Province ◽  
City Management ◽  
Visual Interpretation ◽  
Construction Land ◽  
Spatial Classification ◽  
Land Types

Identifying the land-use type and spatial distribution of urban construction land is the basis of studying the degree of exposure and the economic value of disaster-affected bodies, which are of great significance for disaster risk predictions, emergency disaster reductions, and asset allocations. Based on point of interest (POI) data, this study adopts POI spatialization and the density-based spatial clustering of applications with noise (DBSCAN) algorithm to accomplish the spatial classification of construction land. Zhejiang province is selected as a study area, and its construction land is divided into 11 land types using an accurate spatial classification method based on measuring the area of ground items. In the research, the POI dataset, which includes information, such as spatial locations and usage types, was constructed by big data cleaning and visual interpretation and approximately 620,000 pieces in total. The overall accuracy of the confusion matrix is 76.86%, which is greatly improved compared with that constructed with EULUC data (61.2%). In addition, compared with the official statistical data of 11 cities in Zhejiang Province, the differences between the calculated spatial proportions and statistics are not substantial. Meanwhile, the spatial characteristics of the studied land-use types are consistent with the urban planning data but with higher accuracy. The research shows that the construction land in Zhejiang Province has a high degree of land intensity, concentrated assets, and high economic exposure. The approach proposed in this study can provide a reference for city management including urbanization process, risk assessment, emergency management and asset allocation.

scholarly journals Classification of Cancer Pathology Reports: A Large-Scale Comparative Study

2020 ◽  
Vol 24 (11) ◽  
pp. 3085-3094
Author(s):  
Stefano Martina ◽  
Leonardo Ventura ◽  
Paolo Frasconi
Keyword(s):  
Comparative Study ◽  
Large Scale ◽  
Cancer Pathology ◽  
Pathology Reports

Classification of woody-shrub vegetation of the forest-steppe complex of Privolzhskaya Upland

2009 ◽  
pp. 27-53
Author(s):  
A. Yu. Kudryavtsev
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Dominant Species ◽  
Large Scale ◽  
Nature Reserve ◽  
Vegetation Mapping ◽  
Vegetation Classification ◽  
Forest Steppe ◽  
Mapping Data

Diversity of plant communities in the nature reserve “Privolzhskaya Forest-Steppe”, Ostrovtsovsky area, is analyzed on the basis of the large-scale vegetation mapping data from 2000. The plant community classi­fication based on the Russian ecologic-phytocoenotic approach is carried out. 12 plant formations and 21 associations are distinguished according to dominant species and a combination of ecologic-phytocoenotic groups of species. A list of vegetation classification units as well as the characteristics of theshrub and woody communities are given in this paper.

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