Abstract
Dynamic traffic flow, which can facilitate the efficient operation of traffic road networks, is an important prerequisite for the application of reasonable assignment of traffic demands in an urban road network. In order to improve the accuracy of dynamic traffic flow assignment, this paper proposes a dynamic traffic flow assignment model based on GPS trajectory data and the influence of POI. First, this paper explores the impact patterns of POI on regional road network congestion during peak hours through qualitative and quantitative analysis. Then, based on the user equilibrium theory, a dynamic traffic flow assignment model, in which the effect of POI on links is reflected using the link-node impedance function, is proposed. Finally, the accuracy of the model is validated by the GPS trajectory data and origin–destination (OD) traffic data of motor vehicles in Xuhui District, Shanghai, China. The results show that the model can be used to coordinate and optimize the traffic assignment of the regional road network under the influence of POI during peak hours and alleviate the congestion of the road network. The findings can provide a powerful reference for developing scientific and rational traffic assignment decisions and management strategies for urban road network traffic.
Highlights
With the rapid development of urban construction, traffic congestion has become a thorny issue
In the link where the POI is located, the red area of the model result is significantly reduced compared with the status quo, indicating that the traffic assignment result relieves the congestion of the POI link effectively
The model introduces dynamic user equilibrium theory and node–link imimpedance function,which whichmakes makesthe thetraffic trafficflow flow assignment assignment results results not pedance function, only fit fit the theactual actual road help to to alleviate thethe congestion of the regional road road network
Summary
With the rapid development of urban construction, traffic congestion has become a thorny issue. In 2019, 4.438 million motor vehicles were registered in Shanghai, China, with a year-on-year rise of 5.3%. The total length of the city’s road network increased by 0.6% year-on-year [1]. Among mega cities, Shanghai has the lowest average speed of 24.29 km/h during peak hours [2]. It is urgent for Shanghai to solve the traffic congestion problem. Dynamic traffic flow assignment, which can automatically allocate spatial resources according to the travel demand based on real-time traffic information in a timely manner, has attracted attention of scholars [3,4,5,6]
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