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Wyszukujesz frazę "Logit model" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
The application of a logistic regression model for predicting preferences of transport system users
Zastosowanie modelu regresji logistycznej do przewidywania preferencji użytkowników systemu transportowego
Autorzy:
Brzeziński, A.
Brzeziński, K.
Dybicz, T.
Szymański, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/230493.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
system transportowy
modelowanie podróży
podział zadań przewozowych
regresja logistyczna
model logitowy
transport system
travel modelling
modal split
logistic regression
logit model
Opis:
Within the INMOP 3 research project, an attempt was made to solve a number of problems associated with the methodology of modelling travel in urban areas and the application of intermodal models. One of these is the ability to describe the behaviour of transport system users, when it comes to making decisions regarding the selection of means of transport and searching for relationships between travel describing factors and the decisions made in regard of means of transport choice. The paper describes a probabilistic approach to the determination of modal split, and the application of a logistic regression model to determine the impact of variables describing individual and mass transport travels on the probability of selecting specific means of transport. Travels in local model of Warsaw city divided into 9 motivation groups were tested, for which ultimately 8 models were developed, out of which 7 were deemed very well fitted (obtained pseudoR2 was well above 0.2).
Umiejętność opisania zachowań użytkowników systemu transportowego w zakresie podejmowanych decyzji dotyczących wyboru środka transportowego stanowi podstawę tworzenia modeli podróży, służących analizom i prognozowaniu ruchu. Wiąże się to z poszukiwaniem zależności pomiędzy czynnikami opisującymi podróże, a podejmowanymi decyzjami o wyborze środków transportu. Decyzje o tym, jaki rodzaj transportu wybrać są zdeterminowane różnymi czynnikami dotyczącymi samej podróży, ale również indywidualnymi preferencjami użytkowników systemu transportowego. Tworząc modele podziału zadań przewozowych nie sposób jest, ze względu na dostępność danych, uwzględnić wszystkie możliwe czynniki, zatem trzeba uznać, że o mechanizmie wyboru będą decydować czynniki niekontrolowane, losowe. Dlatego też uzasadnione jest stosowanie podejścia probabilistycznego. Prawidłowe opisanie procesu podziału zadań przewozowych jest bardzo ważne zwłaszcza przy analizach wariantowych inwestycji transportu indywidualnego i publicznego. Oszacowanie pasażerów przeniesionych pomiędzy systemami jest wymagane m.in. w projektach aplikujących o dofinansowanie z programów Unii Europejskiej i jest oceniane przez jednostki opiniujące (np. CUPT i Jaspers). Rosnące zapotrzebowanie na stosowanie modeli ruchu wymusza konieczność rozwijania i wzmacniania metod ich budowy, poprawiania wiarygodności i funkcjonalności. Tematykę wyboru środka transportu podjęto w projekcie badawczym INMOP 3 („Zasady prognozowania ruchu drogowego z uwzględnieniem innych środków transportu”) realizowanym w okresie 1 luty 2016 - 30 kwietnia 2019 r. na zamówienie Narodowego Centrum Badań i Rozwoju (NCBiR) oraz Generalnej Dyrekcji Dróg Krajowych i Autostrad (GDDKiA)6. Projekt zajmuje się hierarchicznym podejściem do modelowania i prognozowana podróży, tj. dotyczy metod modelowania ruchu na poziomie krajowym, regionalnym i lokalnym. INMOP 3 stawia sobie za cel podjęcie próby rozwiązania szeregu problemów szczegółowych, także związanych z modelowaniem podróży w obszarach zurbanizowanych, gdzie zagadnienie intermodalności modelu i podział zadań przewozowych jest szczególnie ważne.
Źródło:
Archives of Civil Engineering; 2018, 64, 4/I; 145-159
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Impact assessment of short-term management measures on travel demand
Autorzy:
D'Cruz, Jinit J.M.
Alex, Anu P.
Manju, V. S.
Peter, Leema
Powiązania:
https://bibliotekanauki.pl/articles/223500.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
public transportation
travel demand management
four stage model
linear regression
modal shift
multinomial logit model
transport publiczny
zarządzanie podróżą
przesunięcie modalne
Opis:
Travel Demand Management (TDM) can be considered as the most viable option to manage the increasing traffic demand by controlling excessive usage of personalized vehicles. TDM provides expanded options to manage existing travel demand by redistributing the demand rather than increasing the supply. To analyze the impact of TDM measures, the existing travel demand of the area should be identified. In order to get quantitative information on the travel demand and the performance of different alternatives or choices of the available transportation system, travel demand model has to be developed. This concept is more useful in developing countries like India, which have limited resources and increasing demands. Transport related issues such as congestion, low service levels and lack of efficient public transportation compels commuters to shift their travel modes to private transport, resulting in unbalanced modal splits. The present study explores the potential to implement travel demand management measures at Kazhakoottam, an IT business hub cum residential area of Thiruvananthapuram city, a medium sized city in India. Travel demand growth at Kazhakoottam is a matter of concern because the traffic is highly concentrated in this area and facility expansion costs are pretty high. A sequential four-stage travel demand model was developed based on a total of 1416 individual household questionnaire responses using the macro simulation software CUBE. Trip generation models were developed using linear regression and mode split was modelled as multinomial logit model in SPSS. The base year traffic flows were estimated and validated with field data. The developed model was then used for improving the road network conditions by suggesting short-term TDM measures. Three TDM scenarios viz; integrating public transit system with feeder mode, carpooling and reducing the distance of bus stops from zone centroids were analysed. The results indicated an increase in public transit ridership and considerable modal shift from private to public/shared transit.
Źródło:
Archives of Transport; 2020, 53, 1; 37-52
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An analysis of influential factors associated with rural crashes in a developing country: a case study of Iran
Autorzy:
Sheykhfard, Abbas
Haghighi, Farshidreza
Abbasalipoor, Reza
Powiązania:
https://bibliotekanauki.pl/articles/2173931.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
rural roads
severity of crashes
crashes
injury-fatal crashes
logit model
crash data collected
drogi wiejskie
ciężkość wypadków
awarie
wypadki śmiertelne
model logiczny
Opis:
Road traffic deaths continue to rise, reaching 1.35 million in recent years. Road traffic injuries are the eighth leading cause of death for people of all ages. Note that there is a wide difference in the crash rate between developed and developing countries and that developed countries report much lower crash rates than developing and underdeveloped countries. World Health Organization reports that over 80% of fatal road crashes occur in developing countries, while developed countries account for about 7% of the total. The rate of road crashes in developing countries is higher than the global average, despite some measures reducing deaths over the last decade. Numerous studies have been carried out on the safety of urban roads. However, comprehensive research evaluating influential factors associated with rural crashes in developing countries is still neglected. Therefore, it is crucial to understand how factors influence the severity of rural road crashes. In the present study, rural roads in Mazandaran province were considered a case study. The Crash data collected from the Iranian Legal Medicine Organization covers 2018 to 2021, including 2047 rural crashes. Dependent variables were classified as damage crashes and injury-fatal crashes. Besides, independent variables such as driver specifications, crash specifications, environment specifications, traffic specifications, and geometrical road specifications were considered parameters. The logit model data indicate that factors associated with driver and crash specifications influence rural crashes. The type of crashes is the most critical factor influencing the severity of crashes, on which the fatal rate depends. The findings suggested that implementing solutions that minimize the effect of the factors associated with injury and death on rural roads can reduce the severity of crashes on rural roads that share the same safety issues as the case study. Further studies can also be conducted on the safety and mechanics of the vehicle by focusing the research on the types of vehicles and the sources of the damage.
Źródło:
Archives of Transport; 2022, 63, 3; 53--65
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mode choice analysis of school trips using random forest technique
Autorzy:
D'Cruz, Jinit J.M.
Alex, Anu P.
Manju, V. S.
Powiązania:
https://bibliotekanauki.pl/articles/2173923.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
city transport
Multinomial Logit model
analysis of the travel model
school trips
peak hour traffic
commuting to schools
transport miejski
analiza trybu przejazdów
przejazdy do szkół
ruch w godzinach szczytu
Opis:
Mode choice analysis of school trips becomes important due to the fact that these trips contribute to the second largest share of peak hour traffic. This scenario is more relevant in India, which has almost 265 million students enrolled in different accredited urban and rural schools of India, from Class I to XII as per the UDISE report of 2019-20. Thus, it becomes necessary to understand what mode of transport will be mostly used for school trips in order to design an efficient transportation system. Modal attributes and socio-economic characteristics are mostly considered as explanatory variables in travel mode choice models. Multinomial Logit (MNL) model is one of the classic models used in the development of mode choice models. These logistic regression models predict outcomes based on a set of independent variables. With the recent advances in machine learning, transportation problems are getting a wide arena of methods and solutions. Among them the method of ensemble learning is finding a prominent place in contemporary modelling. This study explores the potential of using ensembles of random decision trees in mode choice analysis by Random Forest Technique with a comparative analysis on conventional method. It was observed that Random Forest method outperforms MNL method in predicting the mode choice preference of students. The high accuracy of machine learning models is mainly due to its ability to consider complex nonlinear relationship between socio-economic attributes and travel mode choice. These models can learn and identify pattern characteristics extracted from sample data and form adaptive structures through computational process thereby offering insights into the relationships between variables that random utility models cannot recognize. This study considered activity -travel information, personal data and household characteristics of students as attributes for model development and observed that the age of the student and distance of school from home plays a significant role in deciding the mode choice of school trips.
Źródło:
Archives of Transport; 2022, 62, 2; 39--48
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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