Search

Your search keyword '"TRAFFIC flow measurement"' showing total 2 results
Start Over Descriptor "TRAFFIC flow measurement" Topic intelligent transportation systems Topic traffic flow
2 results on '"TRAFFIC flow measurement"'

1. Traffic Stream Analysis by Radar Sensors on Two-Lane Roads for Free-Moving and Constrained Vehicles Identification.

Author

Cantisani, Giuseppe, Del Serrone, Giulia, Mauro, Raffaele, Peluso, Paolo, and Pompigna, Andrea

Subjects
*INTELLIGENT transportation systems, *TRAFFIC flow, *RADAR, *TRAFFIC monitoring, *DETECTORS, *TRACKING radar, TRAFFIC flow measurement
Abstract

This paper focuses on the analysis of traffic streams on two-lane highways, which are crucial components of transportation networks. Traffic flow measurement technologies, such as detection stations, radar guns, or video cameras, have been used over the years to detect the level of traffic and the operating conditions. This type of sensor can record a large amount of data which is useful to evaluate and monitor road traffic conditions, and it is possible to identify free-moving and constrained vehicles by processing the collected data. This study introduces an exponential headway model to identify the headway threshold above which vehicles can be considered as unconditioned. However, this value could identify vehicles which still retain some autonomy in their speed and maneuvering. Therefore, an additional criterion to distinguish between apparently and actually conditioned vehicles has been introduced, analyzing the speed differences between a vehicle and the preceding one. Three-month sequences of traffic monitored through radar devices placed on some Italian two-lane roads have been analyzed and an exponential headway model has been introduced, as an illustrative example. The results show that introducing the criterion of maneuvering freedom can significantly improve traffic flow analysis, modifying the starting critical values of 4 and 8 s per each studied section, to 2.5 and 3 s, approaching the values suggested by international manuals for traffic flow quality analysis. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

2. On improving the regional transportation efficiency based on federated learning.

Author

Su, Zhongqing and Li, Congduan

Subjects
*INTELLIGENT transportation systems, *DATA privacy, *TRAVEL time (Traffic engineering), *TRAFFIC flow, *TRAFFIC congestion, *CITY traffic, TRAFFIC flow measurement
Abstract

• Federated learning is applied in the regional transportation systems to improve the accuracy of traffic flow prediction and protect the privacy of vehicles. • Road weight measurement with a traffic flow prediction model is used for vehicle route optimization. • Departure strategies are used to optimize the scheduling of vehicles to improve overall regional travel efficiency. • Experiments show that the proposed scheme can optimize the transportation system while protecting data privacy. In recent years, regional traffic congestion has become increasingly frequent, which seriously affects the safety and efficiency of urban vehicles. Therefore, traffic flow prediction methods based on artificial intelligence are widely used in traffic management. However, the existing traffic flow prediction methods need to collect raw data, which involves risks of vehicle privacy leakage. Federated learning, which shares model updates without exchanging local data, has gradually become an effective solution to achieve privacy protection. A federated learning traffic flow prediction model for regional transportation systems is proposed in this paper. At the same time, due to the emergence of highly intelligent automatic driving vehicles, a vehicle scheduling system, which can control the departure and routes of vehicles in urban regions is developed in the proposed approach. A road weight measurement method combined with real time traffic information is introduced to optimize the driving routes of vehicles to reduce the average travel time. Additionally, departure strategy, is another factor that has a great influence on traffic efficiency, but is usually ignored in the past, and is also carefully compared and studied in this paper. The numerical results illustrate that the proposed schemes can effectively improve the privacy protection ability of model updates, reduce the scheduling completion time by using the traffic flow prediction model, and realize the comparative research between departure strategies, which provides a reference for developing a safe and efficient regional transportation system. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results