Optimal Lane Management in Heterogeneous Traffic Network

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS

Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9040

Pouria Karimi Shahri, Shubhankar Chintamani Shindgikar, B. Homchaudhuri, A. Ghasemi

引用次数: 11

Abstract

This paper aims to determine an optimal allocation of autonomous vehicles in a multi-lane heterogeneous traffic network where the road is shared between autonomous and human-driven vehicles. The fundamental traffic diagram for such heterogeneous traffic networks is developed wherein the capacity of the road is determined as a function of the penetration rate and the headways of autonomous and human-driven vehicles. In this paper, we define two cost functions to maximize the throughput of the network and minimize the variation between flow rates. To solve the proposed optimization problem, an exhaustive search optimization approach is performed. Several numerical examples are presented to highlight the different influence of different design parameters on the allocation of autonomous vehicles.

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异构交通网络中的最优车道管理

本文旨在确定自动驾驶车辆在多车道异构交通网络中的最佳配置，其中自动驾驶车辆和人类驾驶车辆共享道路。开发了这种异构交通网络的基本交通图，其中道路容量是由自动驾驶车辆和人工驾驶车辆的渗透率和行驶速度决定的。在本文中，我们定义了两个代价函数来最大化网络的吞吐量和最小化流量之间的变化。为了解决所提出的优化问题，采用了一种穷举搜索优化方法。通过数值算例分析了不同设计参数对自动驾驶车辆配置的不同影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.40

自引率

66.70%

发文量

期刊介绍： This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.