Cluster Analysis and Spatial Modeling for Urban Freight. Identifying Homogeneous Urban Zones Based on Urban Form and Logistics Characteristics

Ducret, Raphaëlle; Lemarié, Bernard; Roset, Alain

doi:10.1016/j.trpro.2016.02.067

Cited by 56 publications

(32 citation statements)

References 20 publications

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“…Because logistics emerged as the main organizational system for the flow of materials and shipping logistics intensively formed by the traffic of goods and logistics facilities. Ducret et al (2016) sees that from the point of view of urban transportation is there a relationship between the characteristics of urban forms to the spatial and movement of logistics. The urban transport movement that spatial interaction significantly influences the decision making process with other customers has a greater influence on customers than the interaction between alternative zones (Wisetjindawat et al, 2006).…”

Section: Resultsmentioning

confidence: 99%

Distribution Intensity Model of Retail Logistics Outlets in Metropolitan Scale Cities Based on Spatial Structures

Aksa¹,

Adisasmita²,

Ramli³

et al. 2019

J. Eng. Appl. Sci.

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This study uses the term distribution intensity of Retail Logistics Outlets (RLO) to see its effect on the dynamics of the development of RLO in the metropolitan area. RLO in Makassar city contributes to the formation of spatial structures. This is seen as a change in the function of the area into services by mushrooming RLO in areas with high density levels. The cause of the change in the emergence of RLO as a pull factor in the movement system in general, so that, it impacts spatial interactions. The researcher considers that this is still a new and very interesting thing to do in this research. The focus is on the effect of RLO on the development of spatial structures in the Metropolitan city of Makassar using the analysis of the distribution of the nearest neighboring regions and linear regression. The results of this study can provide several references for spatial planners in space control policies towards the development of city logistics.

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Section: Resultsmentioning

confidence: 99%

Distribution Intensity Model of Retail Logistics Outlets in Metropolitan Scale Cities Based on Spatial Structures

Aksa¹,

Adisasmita²,

Ramli³

et al. 2019

J. Eng. Appl. Sci.

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show abstract

“…This corresponds to a situation where, in the morning and until midday, drivers set out from home, and their destinations are spread randomly over the area of the city, with a concentration of points in the centre. At other times the assumptions were reversed: start points were randomly distributed over the city, and finish points were sampled according to the population density map [25].…”

Section: Start and Finish Pointsmentioning

confidence: 99%

Identification of parameters and verification of an urban traffic flow model. A case study in Wrocław

Chalfen

Kamińska

2018

ITM Web Conf.

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A macroscopic model of road traffic flow in an entire city is constructed, using the example of Wrocław. The model is of deterministic-random type. The start and finish points of each vehicle journey are random elements of the model, while the street graph, routes of travel and traffic parameters are obtained in a deterministic manner. Vehicle speed is dependent on traffic density, and the time needed to cross an intersection depends on the number of waiting vehicles. The route of travel between given start and finish points is determined using Dijkstra’s algorithm, minimising the journey time. The street graph of Wrocław was constructed using data from the Open Street Map website. Identification of parameters and verification of the model were performed using hourly data on traffic volumes at the city’s major intersections in the years 2015–16, obtained from the Intelligent Transport System (ITS). Identification was made of the total number of vehicles travelling in the city at each time of day, a quantity that is difficult to determine by other methods. An accuracy of around 15% was obtained for times between 6.00 and 22.00, while for night-time the verification error exceeded 30%. The model may be used to analyse the impact of planned modifications to the transport system on traffic parameters in the city. It may also serve as a constituent of a larger model for investigating the effect of road transport on atmospheric pollution or for identifying areas at risk of noise pollution.

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“…The principal component analysis and K-Means cluster analysis have been applied to classify the urban area in different French cities in [8]. Sixteen territorial clusters have been provided based on the following criteria-population density; urban density; network density; type of housing; population incomes; land use; age of the population.…”

Section: Introductionmentioning

confidence: 99%

“…The travel behaviours in Nanjing City of China have been estimated by using the cluster analysis, [8]. The authors investigated two types of travel: the transit (bus and metro) and car.…”

Section: Introductionmentioning

confidence: 99%

Methodology for classification sections of railway network using cluster analysis

Stoilova

2019

Engineering for Rural Development

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Categorization of sections of the rail network is an important problem related to the development of railway infrastructure, the organization and management of train movements. In this study a methodology is elaborated to classify the sections of railway network. The methodology includes three steps. In the first step the sections and modules for research are determined. The modules are formed based on the type of railway transportation-passenger trains, fast and express trains, freight trains. The common module with all categories of trains also has been studied. The criteria for categorization, which include infrastructural and operational factors, have been defined in the second step. Nineteen criteria have been proposed in this study. The third step applies the hierarchical cluster analysis method to classify the sections for each of modules. The methodology was applied to Bulgarian railway network and 170 sections have been investigated. The cluster analysis has been used for each of the predefined modules. For each module clusters of sections have been determined. The impact of each criterion has been studied. It was found that the passenger network usage intensity (passenger•km•km-1) is most important in the module related to the passenger transport; the freight network usage (ton•km•km-1) is the main criterion for the freight transportation and the train network usage intensity (gross ton-km/km) is primary for the common module. The methodology can be used to analyse the state of the railway network; traffic assessment; evaluation of the significance of the section in relation to the load; defining infrastructure charges; determination of the capacity of the railway lines; planning of reconstructive events, etc.

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Cluster Analysis and Spatial Modeling for Urban Freight. Identifying Homogeneous Urban Zones Based on Urban Form and Logistics Characteristics

Cited by 56 publications

References 20 publications

Distribution Intensity Model of Retail Logistics Outlets in Metropolitan Scale Cities Based on Spatial Structures

Distribution Intensity Model of Retail Logistics Outlets in Metropolitan Scale Cities Based on Spatial Structures

Identification of parameters and verification of an urban traffic flow model. A case study in Wrocław

Methodology for classification sections of railway network using cluster analysis

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