Temat: travel time prediction - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Community Traffic: a technology for the next generation car navigation
Autorzy:: Dembczyński, K.
Gaweł, P.
Jaszkiewicz, A.
Kotłowski, W.
Kubiak, M.
Susmaga, R.
Wesołek, P.
Wojciechowski, A.
Zielniewicz, P.
Powiązania:: https://bibliotekanauki.pl/articles/205706.pdf
Data publikacji:: 2012
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: community traffic
satellite car navigation
reliability analysis
travel time prediction
Opis:: The paper presents the NaviExpert’s Community Traffic technology, an interactive, community–based car navigation system. Using data collected from its users, Community Traffic offers services unattainable to earlier systems. On the one hand, the current traffic data are used to recommend the best routes in the navigation phase, during which many potentially unpredictable traffic-delaying and traffic-jamming events, like unexpected roadworks, road accidents, or diversions, can be taken into account and thereby successfully avoided. On the other hand, a number of istinctive features, like immediate location of various traffic dangers, are offered. Using exclusively real-life data, provided by NaviExpert, the paper presents two illustrative case studies concerned with experimental evaluation of solutions to computational problems related to the community-based services offered by the system.
Źródło:: Control and Cybernetics; 2012, 41, 4; 867-883
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 2.

Tytuł:: Analysis of spatiotemporal data to predict traffic conditions aiming at a smart navigation system for sustainable urban mobility
Autorzy:: Kyriakou, Kalliopi
Lakakis, Konstantinos
Savvaidis, Paraskevas
Basbas, Socrates
Powiązania:: https://bibliotekanauki.pl/articles/223718.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: spatio-temporal data
travel time prediction
smart navigation
urban mobility
Opis:: Urban traffic congestion created by unsustainable transport systems and considered as a crucial problem for the urbanised areas provoking air pollution, heavy economic losses due to the time and fuel wasted and social inequity. The mitigation of this problem can improve efficiency, connectivity, accessibility, safety and quality of life, which are crucial parameters of sustainable urban mobility. Encouraging sustainable urban mobility through smart solutions is essential to make the cities more liveable, sustainable and smarter. In this context, this research aims to use spatiotemporal data that taxi vehicles adequately provide, to develop an intelligent system able to predict traffic conditions and provide navigation based on these predictions. GPS (Global Positioning System) data from taxi are analysed for the case of Thessaloniki city. Trough data mining and map-matching process, the most appropriate data are selected for travel time calculations and predictions. Several algorithms are investigated to find the optimum for traffic states prediction for the specific case study concluding that ANN (Artificial Neural Networks) outperforms. Then, a new road network map is created by producing spatiotemporal models for every road segment under investigation through a linear regression implementation. Moreover, the possibility to predict vehicle emissions from travel times is investigated. Finally, an application with a graphical user interface is developed, that navigates the users with the criteria of the shortest path in terms of trip length, travel time shortest path and “eco” path. The outcome of this research is an essential tool for drivers to avoid congestion spots saving time and fuel, for stakeholders to reveal the problematic of the road network that needs amendments and for emergency vehicles to arrive at the emergency spot faster. Besides that, according to an indicator-based qualitative assessment of the proposed navigation system, it is concluded that it contributes significantly to environmental protection and economy enhancing sustainable urban mobility.
Źródło:: Archives of Transport; 2019, 52, 4; 27-46
0866-9546
2300-8830
Pojawia się w:: Archives of Transport
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 3.

Tytuł:: Some aspects of Intelligent Transport System auditing
Autorzy:: Bazan, M.
Bożek, M.
Ciskowski, P.
Halawa, K.
Janiczek, T.
Kozaczewski, P.
Rusiecki, A.
Powiązania:: https://bibliotekanauki.pl/articles/393760.pdf
Data publikacji:: 2015
Wydawca:: Polskie Stowarzyszenie Telematyki Transportu
Tematy:: intelligent transportation
system audit
travel time prediction
fundamental diagram
inteligentny transport
audit systemu
przewidywanie czasu podróży
diagram fundamentalny
Opis:: Nowadays, in urbanized areas one of the most important matters is to determine a priori the time of driving from one zone of the city to another at various times of the day. The problem of travel time prediction is crucial in Intelligent Transportation Systems. The solution to this problem is a foundation of any route guidance system that will redirect drivers to their target destination via routes that have a lighter traffic load and thus higher travel velocity. In this paper is present a concept of a statistical methodology, developed by the ArsNumerica Group, that enables a quantity audit a travel time prediction algorithm. The methodology assumes that we are given database records of vehicles recognized by their unique identifier as well as duration times for which the messages with the predicted travel time are displayed VMS. the second aspect of ITS auditing considered in this paper is a placement of video cameras to measure vehicle stream velocity. Inappropriate camera location results in the fact that the stream velocity measured by them has a low usefulness for travel time prediction.
Źródło:: Archives of Transport System Telematics; 2015, 8, 3; 3-8
1899-8208
Pojawia się w:: Archives of Transport System Telematics
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 4.

Tytuł:: Quantum road traffic model for ambulance travel time estimation
Autorzy:: Bernas, M.
Wisniewska, J.
Powiązania:: https://bibliotekanauki.pl/articles/333463.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: ambulance travel time prediction
quantum processing
traffic modelling
przewidywany czas jazdy pogotowia
przetwarzanie informacji kwantowej
modelowanie ruchu drogowego
Opis:: Efficient management of ambulance utilisation is a vital issue for life saving. Knowledge of the amount of time needed for an ambulance to get to the hospital and when it will be available for a new task, can be estimated using modern Intelligent Transport Systems. Their main feature is an ability to simulate the state of traffic not only in long term, but also the real time events like accidents or high congestion, using microscopic models. The paper introduces usage of Quantum Computing paradigm to propose a quantum model of road traffic, which can track the state of traffic and estimate the travel time of vehicles. Model, if run on quantum computer can simulate the traffic in vast areas in real time. Proposed model was verified against the cellular automata model. Finally, application of quantum microscopic traffic models for ambulance vehicles was taken into consideration.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 257-264
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 5.

Tytuł:: Real-time travel time prediction models in routing for car navigation applications
Autorzy:: Gaweł, P.
Dembczyński, K.
Kotłowski, W.
Jaszkiewicz, A.
Powiązania:: https://bibliotekanauki.pl/articles/393980.pdf
Data publikacji:: 2013
Wydawca:: Polskie Stowarzyszenie Telematyki Transportu
Tematy:: FCD
travel time
prediction
navigation
routing
czas podróży
prognoza
nawigacja
trasowanie
Opis:: We consider the problem of using real-time floating car data to construct vehicle travel time prediction models meant to be used as input to routing algorithms for finding the fastest (time-shortest) path in the traffic network. More specifically we target the on-line car navigation systems. The travel time estimates for such a system need to be computed efficiently and provided for all short segments (links) of the roads network. We compare several fast real-time methods such as last observation, moving average and exponential smoothing, each combined with a historical traffic pattern model. Through a series of large-scale experiments on real-world data we show that the described approach yields promising results and conclude that specific prediction function form may be less important than a proper control of bias-variance trade-off (achieved by historical and real-time models combination). In addition, we consider two different settings for testing the prediction quality of the models. The first setting concerns measuring the prediction error on short road segments, while the second on longer paths through the traffic network. We show the quality and model parameters vary depending on the assessment method.
Źródło:: Archives of Transport System Telematics; 2013, 6, 4; 4-8
1899-8208
Pojawia się w:: Archives of Transport System Telematics
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Informacja

Wyszukujesz frazę "travel time prediction" wg kryterium: Temat

Źródło danych

Dostawca treści

Kolekcja

Rok wydania

Wydawca

Temat

Autor

Typ dokumentu

Język