Pregled bibliografske jedinice broj: 1236522
Static Stochastic Model-Based Prediction of City Bus Velocity
Static Stochastic Model-Based Prediction of City Bus Velocity // 5th International Conference on Smart Systems and Technologies (SST)
Osijek, Hrvatska, 2022. str. 1-6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1236522 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Static Stochastic Model-Based Prediction of City
Bus Velocity
Autori
Topić, Jakov ; Škugor, Branimir ; Deur, Joško
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
5th International Conference on Smart Systems and Technologies (SST)
Mjesto i datum
Osijek, Hrvatska, 19.-21.10.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Keywords—driving cycle, velocity, prediction, stochastic model, neural network, road vehicles
Sažetak
This paper proposes a static, stochastic, deep feed-forward neural network-based model for prediction of city bus velocity along a regular route. The emphasis is on a proper formation of model outputs to consistently learn the conditional probability distribution of vehicle velocity based on the vehicle position as only input feature. First, a rich set of recorded driving cycles of a representative fleet of ten city buses is statistically analyzed. Next, the recorded dataset is properly downsampled and used for computationally-efficient training and validation of the neural network. Finally, the prediction accuracy is demonstrated on a test dataset by considering different prediction quality indices.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
IP-2018-01-8323 - Adaptivno i prediktivno upravljanje utičnim hibridnim električnim vozilima (ACHIEVE) (Deur, Joško, HRZZ - 2018-01) ( CroRIS)
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
