Abstract
With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.
Highlights
With the rapid construction of urban intelligent transportation systems, large-scale acquisition of urban traffic data has become possible
Common traffic information collection methods include fixed detection represented by induction coil detector and microwave radar detector, mobile detection represented by floating car system, and satellite navigation system
The traffic detector is still an important part of the urban traffic information collection system, and its optimal layout is of great significance
Summary
With the rapid construction of urban intelligent transportation systems, large-scale acquisition of urban traffic data has become possible. Common traffic information collection methods include fixed detection represented by induction coil detector and microwave radar detector, mobile detection represented by floating car system, and satellite navigation system. Efficient traffic signal control methods have been proven to be one of the important ways to alleviate traffic problems. For the present investigation we are interested in traffic flow models for road networks using the above models based on partial differential equations. Two such models were introduced by Holden and Risebro [1]. Both models use a cumulative description of traffic on each road without distinguishing between single lanes. Suitable conditions at the junctions are defined in order to obtain a uniquely solvable network problem
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