Vehicular traffic optimisation and even distribution using ant colony in smart city environment

被引:31
|
作者
Rehman, Abdul [1 ]
Rathore, Muhammad Mazhar [1 ]
Paul, Anand [1 ]
Saeed, Faisal [1 ]
Ahmad, Raja Wasim [2 ]
机构
[1] Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea
[2] COMSATS Inst IT, Abbottabad, Pakistan
基金
新加坡国家研究基金会;
关键词
vehicle routing; road traffic; ant colony optimisation; vehicular traffic optimisation; smart city environment; ant colony optimization; traffic flow; route optimisation; urban environment; traffic jams; ACO algorithm; vehicular traffic optimization; smart traffic distribution; city traffic optimization; up-to-date city traffic data; BIG DATA; SYSTEM;
D O I
10.1049/iet-its.2017.0308
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For a few years, route optimisation and efficient traffic flow are a big challenge, especially in a current situation when 54.5% population is living in the urban environment all over the world. At peak hours, the traffic jams in urban areas are frequent. Lots of works have been done in finding the shortest path to optimise the route to the destination in minimum time. However, moving vehicles toward the shorter paths causes a severe traffic jam in the city. Therefore, in this study, the authors proposed a framework to enhance the efficiency of the ant colony optimisation (ACO) algorithm to optimise the vehicular traffic, i.e. named as smart traffic distribution ACO. It helps to optimise the route and city traffic efficiently while avoiding congestion in all circumstances using up-to-date city traffic data. Their proposed framework finds the optimal path in such a way that the traffic flow on each road remains normal. The detection of congestion on the road at an early stage and even distribution of traffic on all roads helps to achieve maximum flow, speed, and optimum density of the roads.
引用
收藏
页码:594 / 601
页数:8
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