An Intelligent Route Guidance Strategy based on Congestion Type for ITS

Weilong Zhu1; Chunsheng Zhu1; Yangjie Cao2; Edith C.H. Ngai3; Jiehan Zhou4

10.1109/ICC45855.2022.9838612

2022

IEEE International Conference on Communications (ICC)

1550-3607

978-1-5386-8348-4

ICC 2022 - IEEE International Conference on Communications

2022-May

5047-5052

16-20 May 2022

Seoul, Korea, Republic of

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Traffic congestion is a severe challenge for intelligent transportation system (ITS). So far, if traffic congestion is perceived in a route, a common solution is searching for another congestion-free route. However, it is observed that not all congestions should be tackled with rerouting, since the extra overhead (e.g., extra travel time, extra fuel consumption, and extra CO2 emission) caused by certain congestions might be lower than that of re-routing. Against this backdrop, an intelligent route guidance strategy is proposed, in which vehicles will trade off the extra overhead of re-routing and that of waiting in congestion. Firstly, the perceived congestion is divided into four basic types. Then, the prediction method about the duration of each congestion type is formulated. Finally, the intelligent route planning mechanism is developed. Simulations demonstrate that the proposed strategy can reduce the travel time, fuel consumption, and CO2 emission for vehicles.

Traffic congestion intelligent transportation system re-routing overhead route guidance

第一

英语

EI ; CPCI-S

National Key R&D Program of China[2020YFB2104301] ; Project "Beihang Beidou Technological Achievements Transformation and Industrialization Funds[BARI2005]

Telecommunications

Telecommunications

WOS:000864709905040

20223712711073

Carbon dioxide ; Economic and social effects ; Intelligent systems ; Intelligent vehicle highway systems ; Transportation routes ; Travel time

Highway Systems:406.1 ; Air Transportation:431 ; Highway Transportation:432 ; Railroad Transportation:433 ; Waterway Transportation:434 ; Artificial Intelligence:723.4 ; Computer Applications:723.5 ; Inorganic Compounds:804.2 ; Social Sciences:971

IEEE

1.Southern University of Science and Technology, Shenzhen, China
2.Zhengzhou University, Zhengzhou, China
3.The University of Hong Kong, Hong Kong
4.University of Oulu, Finland

Weilong Zhu,Chunsheng Zhu,Yangjie Cao,et al. An Intelligent Route Guidance Strategy based on Congestion Type for ITS[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:5047-5052.