Improving the efficiency of freight traffic at congested freeway merging sections
被引:4
|
作者:
Sarvi, Majid
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h-index: 0
机构:
Monash Univ, Dept Civil Engn, Inst Transport Studies, Melbourne, Vic 3800, AustraliaMonash Univ, Dept Civil Engn, Inst Transport Studies, Melbourne, Vic 3800, Australia
Sarvi, Majid
[1
]
Kuwahara, Masao
论文数: 0引用数: 0
h-index: 0
机构:
Univ Tokyo, Inst Ind Sci, Kuwahara Lab, Meguro Ku, Tokyo 1538505, JapanMonash Univ, Dept Civil Engn, Inst Transport Studies, Melbourne, Vic 3800, Australia
Kuwahara, Masao
[2
]
机构:
[1] Monash Univ, Dept Civil Engn, Inst Transport Studies, Melbourne, Vic 3800, Australia
[2] Univ Tokyo, Inst Ind Sci, Kuwahara Lab, Meguro Ku, Tokyo 1538505, Japan
Freight;
Heavy commercial vehicles;
Intelligent Transportation Systems (ITS);
Truck Merging Model;
Micro-simulation;
Lane Changing Management;
Dynamic Lane Changing;
Truck Following Model;
FEATURES;
D O I:
10.3328/TL.2009.01.04.309-322
中图分类号:
U [交通运输];
学科分类号:
08 ;
0823 ;
摘要:
This work investigates the effect of heavy commercial vehicles on the traffic characteristics and operation of freeway merging sections and examines potential of intelligent transport system control strategies for freeway merging points to mitigate traffic congestion. Freeways are designed to facilitate the flow of traffic including passenger cars and trucks. The impact of these different vehicle types is not uniform, creating problems in freeway operations and safety particularly in the vicinity of merging sections. There have been very few studies concerned with the traffic behavior and characteristics of heavy vehicles in these situations. This study draws on extensive data captured under a wide range of traffic and geometric conditions using detectors, videotaping, and surveys at several interchanges. The macroscopic detector data were used to identify and quantify the impact of heavy commercial vehicles on the capacity of merging sections. The microscopic data were then utilized to establish a model for the merging and lane changing behavior of heavy vehicles. Based on this behavioral model, a micro-simulation program was developed to simulate the actual traffic conditions. This model evaluates the capacity of a merging section for a given geometric design, flow condition, and traffic composition (presence of freight vehicles). The model is used to develop a variety of intelligent transport system control strategies associated with heavy commercial vehicles in order to design safer and less congested freeway merging points. The implementation of the proposed strategies showed significant improvement in the merging capacity and assisting in reducing the travel time experienced by all vehicles including freight traffic.