Examples of corporate distribution and transportation planning using the princeton transportation network model and graphic information system

1984 ◽  
Vol 9 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Alain L. Kornhauser
2021 ◽  
Vol 44 (2) ◽  
pp. 7-8
Author(s):  
Stephanie VandenBerg ◽  
Gillian Harvey ◽  
Heather Hair ◽  
Eddy Lang ◽  
David Stringer

The patient journey map: Improving the emergency department communication experience for patients and their family and friends. Stephanie VandenBerg, Heather Hair, Gillian Harvey, Eddy Lang, David Stringer Background: The 2013 Urban and Regional Emergency Department (ED) Patient Experience Report indicates that the most important factor influencing a patients’ ED experience is a combination of staff care and communication. Lack of communication in the emergency room experience can be addressed by design methods and processes. The Emergency Strategic Care NetworkTM assembled an interdisciplinary team of experts from various clinical, academic, and information design backgrounds to engage patients, families and providers to improve the ED intake experience. This innovative partnership resulted in the development of a graphic information system that directs, informs and educates patients in EDs in Alberta. Implementation: Using the Plan-Do-Study-Act (PDSA) framework, focus groups were conducted to understand the communication needs of emergency department patients. An information design specialist co-created a graphic information system (the patient journey map) and worked with AHS communications to ensure it met AHS guidelines. Patients were then approached to participate in a 14-question survey about the usability and accuracy of the journey map as well as the impact it had on their ED visit. Our team consisted of Heather Hair, Executive Director of the (ESCN) who provided leadership in identifying communication as a key area for improvement and coordinating ED partners and patient involvement. Gillian Harvey is an assistant professor of Design Studies at the University of Alberta. She used the data collected in focus groups to design a 2-D communication map. David Stringer acted as project manager for the implementation and evaluation of the journey map. Stephanie Vandenberg is an emergency physician and was responsible for designing the evaluation strategy including research methods and data analysis. An official journey map is now available to print for emergency departments across Alberta. Evaluation Methods: The objective was to understand what information ED patients require during their visit to better understand the process by which they are triaged and receive care. Data collection consisted of a 10-minute, 14 question interview. Each question allowed for positive, neutral or negative feedback to capture unintended consequences of the journey map. Quantitative demographic and journey map-specific variables were collected and reported as frequencies. Qualitative data was analyzed using thematic analysis with thematic codes developed and assigned to the qualitative responses. Both quantitative and qualitative analysis was undertaken by two members of the research team. Responses were analyzed against the demographic variable of age category to determine if age impacts communication needs and desired medium of communication in the ED. Results: Seven hospitals took part in this survey, conducted between September 1, 2019 and May 5, 2020. 162 emergency department patients participated. Most people agreed that the journey map clarified the ED patient process and accurately reflected their experience of the ED journey. The journey map did not seem to make the wait less confusing. Participants reported the journey map was good at helping them understand the overall emergency department intake process and did a good job of helping them understand the reason for waiting/delays. The journey map was excellent at helping the participant understand why specific tests/treatments were needed but was poor at helping them to understand the total time it would take them to be seen.


2018 ◽  
Vol 7 (2.11) ◽  
pp. 1
Author(s):  
Adel Gohari ◽  
Abdul Nasir Bin Matori ◽  
Khamaruzaman Wan Yusof ◽  
Iraj Toloue ◽  
Khin Cho Myint

Intermodal transportation is a research topic of great interest at present. This paper presents a route choice analysis on an intermodal freight transportation network. The aim of this study was to determine the optimum route and mode of transportation based on least distance and least time criteria for the movement of containers from origin to the destination. Geographic Information System (GIS) was adopted to build the hypothetical freight transportation network and MATLAB software was used to model the travel distance and travel time. The results showed that the model can be used effectively to identify the shortest path and modes of transportation according to objective functions.  


2018 ◽  
Vol 29 (01) ◽  
pp. 1850005
Author(s):  
Zundong Zhang ◽  
Xiaoyang Xu ◽  
Zhaoran Zhang ◽  
Huijuan Zhou

The Beijing road transportation network (BRTN), as a large-scale technological network, exhibits very complex and complicate features during daily periods. And it has been widely highlighted that how statistical characteristics (i.e. average path length and global network efficiency) change while the network evolves. In this paper, by using different modeling concepts, three kinds of network models of BRTN namely the abstract network model, the static network model with road mileage as weights and the dynamic network model with travel time as weights — are constructed, respectively, according to the topological data and the real detected flow data. The degree distribution of the three kinds of network models are analyzed, which proves that the urban road infrastructure network and the dynamic network behavior like scale-free networks. By analyzing and comparing the important statistical characteristics of three models under random attacks and intentional attacks, it shows that the urban road infrastructure network and the dynamic network of BRTN are both robust and vulnerable.


2012 ◽  
Vol 256-259 ◽  
pp. 2976-2982
Author(s):  
Adewole Oladele ◽  
Vera Vokolkova ◽  
Jerome Egwurube

Botswana is a Southern African country with an area of about 582,000 sq. km and its small population of about 2 million people. The road transportation network has grown beyond all expectations since independence in 1966. Out of the 18,300 km Botswana Public Highway Networks, gravel road networks are significant in providing access to rural areas where the majority of the population lives. Modelling of gravel loss conditions are required in order to predict their conditions in the future and provide information on the manner in which pavements perform. Such information can be applied to transportation planning, decision making processes and identification of future maintenance interventions. The results of previous attempts to develop gravel loss condition forecasting models using multiple linear regression (MLR) approach have not been reliable. This paper intended to develop accurate and reliable performance models which best capture the effects of gravel loss condition influencing factors using Feed Forward Neural Network (FFNN) modeling technique. As extension of knowledge in unpaved road transportation network, FFNN trained with Levenberg-Marquardt (L-M) method was used to develop gravel loss performance prediction model for Botswana gravel road networks to achieve a reliable result of a higher coefficient of determinant R2 = 0.94 compared with MLR analysis of R2 = 0.74.


Author(s):  
Hyunmyung Kim ◽  
Jun-Seok Oh ◽  
R. Jayakrishnan

In many major metropolitan areas, taxi services have played an important role as a semipublic transportation mode without public support. However, there has not been much modeling effort–-despite the importance of taxis in urban transportation systems–-mainly because of the difficulty in modeling taxi drivers’ behavior. This study models a taxi service system in urban areas, taking into account taxi drivers’ knowledge of the transportation network built from their day-to-day experience. Passenger-seeking behavior by taxi drivers is modeled on the basis of their expected travel time and expected waiting time. The model considers the stochastic and dynamic transportation network and various levels of network knowledge on the part of drivers. This modeling approach provides flexibility in modeling the characteristics of taxi operation as well as understanding how taxi drivers’ capability evolves. The study analyzes the fleet size of taxi service systems and the effects of the taxi company's information systems by considering quality and operational efficiency of taxi services, from both the passengers’ and taxi operators’ points of view. A simulation experiment shows that the taxi information system can provide benefits equivalent to increasing the number of taxis by 20% in regard to the quality of taxi service.


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