A traffic flow hierarchy induction algorithm based on VANET

The centralized traffic flow induction algorithm has the disadvantages of high computational complexity and large information delay. The distributed traffic flow induction algorithm has the disadvantage of local optimization. For the above two characteristics, this algorithm proposes a traffic flow layered induction algorithm (TFLIA). Firstly, "stratification" means that the algorithm sets up a two-layer control center. The first layer is at the level of the independent scheduling area. This center plans the travel path of the vehicle nodes. At the entire city level, this center controls the transit path of the traffic flow. Two levels of synergy induce traffic flow. Secondly, this paper proposes a short-term prediction and data decision analysis algorithm to induce the vehicle nodes to enter the planned path. Finally, the algorithm carries out the traffic flow induced simulation experiment. The experimental results show that the algorithm can balance the global flow of traffic flow, reasonably induce traffic flow and alleviate traffic congestion.

[1]  De-gan Zhang,et al.  A Low Duty Cycle Efficient MAC Protocol Based on Self-Adaption and Predictive Strategy , 2018, Mob. Networks Appl..

[2]  Yue Dong,et al.  A kind of effective data aggregating method based on compressive sensing for wireless sensor network , 2018, EURASIP Journal on Wireless Communications and Networking.

[3]  Xiao-huan Liu,et al.  Dynamic Analysis for the Average Shortest Path Length of Mobile Ad Hoc Networks Under Random Failure Scenarios , 2019, IEEE Access.

[4]  Ting Zhang,et al.  Novel self-adaptive routing service algorithm for application in VANET , 2018, Applied Intelligence.

[5]  Xin Pei,et al.  A simulation system and speed guidance algorithms for intersection traffic control using connected vehicle technology , 2019, Tsinghua Science and Technology.

[6]  Yue Dong,et al.  Novel optimized link state routing protocol based on quantum genetic strategy for mobile learning , 2018, J. Netw. Comput. Appl..

[7]  Ting Zhang,et al.  Novel dynamic source routing protocol (DSR) based on genetic algorithm‐bacterial foraging optimization (GA‐BFO) , 2018, Int. J. Commun. Syst..

[8]  Si Liu,et al.  Novel PEECR-based clustering routing approach , 2017, Soft Comput..

[9]  Xiaodan Zhang,et al.  A Kind of Novel Method of Power Allocation With Limited Cross-Tier Interference for CRN , 2019, IEEE Access.

[10]  Chen Chen,et al.  New Method of Energy Efficient Subcarrier Allocation Based on Evolutionary Game Theory , 2018, Mob. Networks Appl..

[11]  De-gan Zhang,et al.  Novel approach of distributed & adaptive trust metrics for MANET , 2019, Wirel. Networks.

[12]  Yu-ya Cui,et al.  A New Algorithm of the Best Path Selection Based on Machine Learning , 2019, IEEE Access.

[13]  Ting Zhang,et al.  Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education , 2017, J. Netw. Comput. Appl..

[14]  Jie Liang,et al.  Design of Highway Intelligent Vehicle Guidance System , 2018 .

[15]  Ting Zhang,et al.  Novel reliable routing method for engineering of internet of vehicles based on graph theory , 2018, Engineering Computations.

[16]  Guoqiang Mao,et al.  New Multi-Hop Clustering Algorithm for Vehicular Ad Hoc Networks , 2019, IEEE Transactions on Intelligent Transportation Systems.