Naslov
Traffic speed prediction for highway operations based on a symbolic regression algorithm

Autori
Li, Linchao ; Fratrović, Tomislav ; Jian, Zhang ; Bin, Ran

Izvornik
Promet - Traffic & Transportation (0353-5320) 29 (2017), 4; 431-441

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
highway congestion ; traffic state ; sensor data ; speed prediction ; incident ; symbolic regression ; genetic programming

Sažetak
Due to the increase of congestion on highway, providing real-time information about the traffic state becomes a crucial issue. Hence, it is the aim of this research to build an accurate traffic speed prediction model using symbolic regression to generate significant information for travelers. It is built based on genetic programming using Pareto front technique. With real world data from microwave sensor, the performance of the proposed model is compared with two other widely used models. The results indicate that the symbolic regression is the most accurate among these models. Especially, after an incident occurs, the performance of the proposed model is still the best which means it is robust and suitable to predict traffic state of highway under different conditions.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Tehnologija prometa i transport

POVEZANOST RADA