基于智能交通系统的交通拥堵预测与缓解策略研究

随着城市化进程的不断推进,交通拥堵已成为当今城市面临的严峻问题之一。交通拥堵不仅影响着市民的日常出行,也对城市经济、环境和社会稳定产生深远影响。针对这一问题,智能交通系统的出现为解决交通拥堵提供了新的思路和技术手段。深入探讨智能交通系统在交通拥堵管理中的关键作用,对数据收集、分析方法和缓解策略进行分析,通过利用先进的数据采集和处理技术、数据分析算法以及实时信息传递系统,智能交通系统能够实现对交通流的精准监测与调控,从而为交通拥堵的预测与缓解提供有力支持,为构建更为智能高效的城市交通管理体系提供参考。     

潮汐车道的设计及其对交通拥堵缓解效果的研究

为了管理和解决潮汐式交通拥堵,本文对拥堵特性进行了分析,对使用潮汐车道解决潮汐式交通拥堵问题进行了研究。给出潮汐车道的设置条件和设置方法,调查了选定路段的交通现状及高峰交通量,通过VISSIM软件进行路段仿真,论证了潮汐车道对潮汐式交通拥堵的缓解效果。     

基于交通状态识别的信号交叉口模糊控制方法

1引言城市交通的拥堵问题已成为城市化发展过程中最为突出的问题之一。城市道路的信号控制技术,是调节路网交通需求,改善路网服务水平,最终缓解交通拥堵的重要手段。长期以来,对交通系统的控制一直是一个具有挑战性的难题。传统的控制方法在简化假设的条件下对交通流状况做出预测,并以平均延误、排队长度和停车次数等为优化目标,运用模糊控制算法,遗传算法,迭代学习,神经网络,多智能体算法等实施相应的控制策略。然而,这些模型多     

黄骅市中心交通拥堵成因分析及对策

我国交通拥堵问题已逐渐向小城市蔓延,黄骅市已受到交通拥堵的困扰。本文通过对黄骅市市中心主要交通干道的分析和现场交通拥堵现状的调查,分析其交通拥堵主要原因,并提出合理的改善方案,不仅有效地解决了黄骅市交通拥堵问题,也为其他县级市提供了借鉴意义。     

基于ITS的解决城市道路交通拥堵的有效措施研究

城市道路交通拥堵已成为世界各国普遍存在的问题,严重影响着城市的经济建设、运转效率和人们的工作与生活。如何解决城市道路交通拥堵问题,越来越受到人们的重视。在明确我国城市道路交通概念、特征和城市道路交通拥堵涵义的基础上,提出了ITS是解决城市道路交通拥堵的有效治理措施的思路。     

高速公路交通拥堵问题反思

文章针对我国高速公路建设现状及典型交通拥堵问题,分析了发生交通拥堵的表征原因,并从工程可行性研究报告编制角度探讨了高速公路交通拥堵的解决对策。     

基于指数模型的城市路网交通拥堵评判方法研究

城市路网交通拥堵评判方法研究一直是拥堵评判技术领域内的重点、难点问题之一。交通拥堵指数模型能够把复杂的城市路网交通运行状况进行简单化、透明化,并能应用到其他城市或区域路网评判体系研究中。文章提出了基于交通拥堵指数模型的一般性交通拥堵评判方法,介绍了该模型各评判指标的计算过程。并以兰州市七里河区和城关区的路网交通为例,对该模型的实用性进行验证,最终得出两城区整体交通拥堵规律及指数变化趋势,说明了该评判方法的可行性和有效性。     

公路隧道通风的模糊PID控制

通风控制就是要在节约电能消耗的前提下,将隧道内CO浓度和烟雾浓度控制在允许的范围内.对于这样一个大滞后的检测控制过程,利用模糊控制不需要建立被控对象精确数学模型的特点,提出了一种基于CO浓度和烟雾浓度检测的变频通风模糊PID控制方法,实现了在控制过程中对不确定的条件、参数、延迟和干扰等因素进行检测分析.采用模糊推理的方法对PID参数的在线自整定,可减小系统超调量、提高系统反应速度、缩短调节时间,从而改善了系统的动态性能,能降低电能消耗,延长通风机使用寿命,降低运营成本.     

特大城市交通拥堵治理对策研究——以上海为例

交通拥堵是我国特大城市面临的普遍问题。本文以上海为例总结了特大城市"道路车堵车,轨道人挤人"的交通拥堵现状,系统分析了人口与交通需求增长、用地布局调整、道路设施及运行管理不足、公交系统服务吸引力不佳、交通偶发性事件等交通拥堵症结所在,并提出优化城市用地布局、控制个体机动化出行需求、推进道路建设与交通管理、提升公共交通系统服务能力等对策措施,以期为特大城市交通拥堵治理提供参考借鉴。     

城市快速路入口匝道交通控制算法综述

入口匝道控制在缓解城市快速路交通拥堵、提升瓶颈路段通行能力以及加强快速路安全性与稳定性具有显著效果。本文根据调节方法与实时交通状态之间的关系将匝道控制分为定时控制与自适应控制,并对自适应控制中的局部控制、合作型协调控制、竞争型协调控制、交通集成型协调控制典型算法的原理及优缺点进行分析,比较。最后在总结现在算法的基础上,对未来快速路匝道控制的研究方向进行了分析展望。     

山区城市交通拥挤成因分析及对策研究

文章以重庆市道路交通为例,从特殊地理环境因素、城市道路管理及城市规划等方面分析了山区城市道路交通拥挤的原因,并基于道路因素,从城市道路规划和整合建筑与交通空间方面提出了缓解交通拥堵的措施和建议。     

基于贝叶斯网络模型的交通状态预测

城市的交通状态是可以预测的。有效的交通状态预测能优化交通状态,减少交通阻塞。贝叶斯网络(Bayesian Networks,BN)是目前不确定知识和推理领域最有效的理论模型之一。文章在综合考虑交通阻塞成因的基础上构建网络模型,在已有的交通状态数据的基础上提出基于贝叶斯法则的学习算法,并通过计算变量间的条件概率来计算交通阻塞发生的可能性,达到预测的目的。     

Data mining using regularized adaptive B‐splines regression with penalization for multi‐regime traffic stream models

This paper presents a new data mining method that integrates adaptive B‐spline regression and traffic flow theory to develop multi‐regime traffic stream models (TSMs). Parameter estimation is implemented adaptively and optimally through a constrained bi‐level programming method. The slave programming determines positions of knots and coefficients of the B‐spline by minimizing the error of B‐spline regression. The master programming model determines the number of knots through a regularized function, which balances model accuracy and model complexity. This bi‐level programming method produces the best fitting to speed–density observations under specific order of splines and possesses great flexibility to accommodate the exhibited nonlinearity in speed–density relationships. Jam density can be estimated naturally using spline TSM, which is sometimes hardly obtainable in many other TSM. Derivative continuity up to one order lower than the highest spline degree can be preserved, a desirable property in some application. A five‐regime B‐spline model is found to exist for generalized speed–density relationships to accommodate five traffic operating conditions: free flow, transition, synchronized flow, stop and go traffic, and jam condition. A typical two‐regime B‐spline form is also explicitly given, depending only on free‐flow speed, optimal speed, optimal density, and jam density. Copyright © 2013 John Wiley & Sons, Ltd.     

小金口枢纽互通立交拥堵改造分析

文章以广惠高速公路小金口枢纽互通立交工程为依托,在预测交通量的基础上从拥堵匝道的通行能力、服务水平和交通事故等方面分析匝道拥堵的原因,并提出基于光流率和边缘率的主线改善措施和匝道改善方案,为小金口枢纽互通立交及其他立交的拥堵改造提供参考。     

如何建立多商业中心模式解决城市交通问题

文章对城市交通拥堵及其解决措施进行了探讨,为优化单商业中心城市交通资源使用,缓解城市交通拥堵,提出建立多个次级商业中心的设想和实现方式。并建立简单模型对单商业中心模式与多商业中心模式进行比较分析,证明从解决交通问题的角度考虑,城市采取多商业中心模式优于单商业中心模式。     

Connectivity-based optimization of vehicle route and speed for improved fuel economy

Traditionally, vehicle route planning problem focuses on route optimization based on traffic data and surrounding environment. This paper proposes a novel extended vehicle route planning problem, called vehicle macroscopic motion planning (VMMP) problem, to optimize vehicle route and speed simultaneously using both traffic data and vehicle characteristics to improve fuel economy for a given expected trip time. The required traffic data and neighbouring vehicle dynamic parameters can be collected through the vehicle connectivity (e.g. vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-cloud, etc.) developed rapidly in recent years. A genetic algorithm based co-optimization method, along with an adaptive real-time optimization strategy, is proposed to solve the proposed VMMP problem. It is able to provide the fuel economic route and reference speed for drivers or automated vehicles to improve the vehicle fuel economy. A co-simulation model, combining a traffic model based on SUMO (Simulation of Urban MObility) with a Simulink powertrain model, is developed to validate the proposed VMMP method. Four simulation studies, based on a real traffic network, are conducted for validating the proposed VMMP: (1) ideal traffic environment without traffic light and jam for studying the fuel economy improvement, (2) traffic environment with traffic light for validating the proposed traffic light penalty model, (3) traffic environment with traffic light and jam for validating the proposed adaptive real-time optimization strategy, and (4) investigating the effect of different powertrain platforms to fuel economy using two different vehicle platforms. Simulation results show that the proposed VMMP method is able to improve vehicle fuel economy significantly. For instance, comparing with the fastest route, the fuel economy using the proposed VMMP method is improved by up to 15%.     

Theory of jam-absorption driving

“Can a single car really absorb a traffic jam without making new jams?” In this paper, we focus on this frequently-discussed question, and have succeeded in making a theoretical framework of a driving technique how to absorb a traffic jam by using a minimal microscopic model. Jam-absorption driving comes from Beaty (Beaty, 1998, Beaty, 2013), and it is composed of a sequence of two actions termed the “slow-in” and “fast-out”. The “slow-in” is the action to avoid being captured by a jam and remove it by decelerating and taking a longer headway in advance. The “fast-out” is performed after the “slow-in”, and it is the action to follow the car in front without unnecessary time gaps by accelerating quickly. In our theoretical framework, we have represented the recipe of the actions such as the time–space points and the velocity. Moreover, we have clarified the condition of no secondary jams due to this driving, i.e., the condition that compression and expansion waves caused by this driving meet each other and disappear. Particularly, we have calculated how these waves propagates to the following cars and the point where and when they disappear. Besides, we have analyzed how this point moves in time–space diagrams by varying the timing to start the jam-absorption, and revealed that the pattern of this movement is not constant but changes greatly by the velocity-headway relationships. Furthermore, as a more realistic problem, we have formulated the driving for jam-absorption in two steps of deceleration, which brings rich patterns of collisions among compression and expansion waves.     

南宁市交通拥堵成因及对策分析

文章基于对南宁市交通状况的调查,分析了南宁市交通拥堵问题产生的原因,提出了相应的对策与建议。     

A macroscopic traffic model for highway work zones: Formulations and numerical results

This study presents a multilane model for analyzing the dynamic traffic properties of a highway segment under a lane‐closure operation that often incurs complex interactions between mandatory lane‐changing vehicles and traffic at unblocked lanes. The proposed traffic flow formulations employ the hyperbolic model used in the non‐Newtonian fluid dynamics, and assume the lane‐changing intensity between neighboring lanes as a function of their difference in density. The results of extensive simulation experiments indicate that the proposed model is capable of realistically replicating the impacts of lane‐changing maneuvers from the blocked lanes on the overall traffic conditions, including the interrelations between the approaching flow density, the resulting congestion level, and the exiting flow rate from the lane‐closure zone. Our extensive experimental analyses also confirm that traffic conditions will deteriorate dramatically and evolve to the state of traffic jam if the density has exceeded its critical level that varies with the type of lane‐closure operations. This study also provides a convenient way for computing such a critical density under various lane‐closure conditions, and offers a theoretical basis for understanding the formation as well as dissipation of traffic jam.     

On the fundamental diagram for freeway traffic: A novel calibration approach for single-regime models

The speed-density or flow-density relationship has been considered as the foundation of traffic flow theory. Existing single-regime models calibrated by the least square method (LSM) could not fit the empirical data consistently well both in light-traffic/free-flow conditions and congested/jam conditions. In this paper, first, we point out that the inaccuracy of single-regime models is not caused solely by their functional forms, but also by the sample selection bias. Second, we apply a weighted least square method (WLSM) that addresses the sample selection bias problem. The calibration results for six well-known single-regime models using the WLSM fit the empirical data reasonably well both in light-traffic/free-flow conditions and congested/jam conditions. Third, we conduct a theoretical investigation that reveals the deficiency associated with the LSM is because the expected value of speed (or a function of it) is nonlinear with regard to the density (or a function of it).