Optimal Routing with Spatial-Temporal Dependencies for Traffic Flow Control in Intelligent Transportation Systems  

作　　者：R.B.Sarooraj S.Prayla Shyry 

机构地区：[1]School of Computing,Sathyabama Institute of Science and Technology,Chennai,600119,India

出　　处：《Intelligent Automation & Soft Computing》2023年第5期2071-2084,共14页智能自动化与软计算（英文）

摘　　要：In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major challenge.Particularly,allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the trafficflow.So,in this paper,the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is optimized.Initially,the hotspots in a region are clustered using the density-based spatial clustering of applications with noise(DBSCAN)algorithm tofind the hot spots at the peak hours in an urban area.Then,the optimal route is allocated to the taxi driver to pick up the customer in the hotspot.Before allocating the optimal route,each route between the taxi driver and the hot spot is mapped to the number of taxi drivers.Among the map function,the optimal map is selected using the rain opti-mization algorithm(ROA).If more than one map function is obtained as the opti-mal solution,the map between the route and the taxi driver who has done the least number of trips in the day is chosen as thefinal solution This optimal route selec-tion leads to control of the trafficflow at peak hours.Evaluation of the approach depicts that the proposed trafficflow control scheme reduces traveling time,wait-ing time,fuel consumption,and emission.

关 键 词：Intelligent transportation system(ITS) DBSCAN rain optimization algorithm(ROA) trafficflow control 

分 类 号：U495[交通运输工程—交通运输规划与管理]