基于Python与Tensorflow的交通信号决策系统

为改变目前我国道路信号配时方案与实际交通流不匹配的情况,提高道路交叉口的通行能力,增加绿灯的使用率,提出基于Python与Tensorflow的交通信号决策系统。介绍交通信号决策系统的整体框架及各个模块的层次关系,详细说明每部分的原理及实现方法。通过Python在互联网上实现实时交通数据自动采集,将搜集的数据分类存储。采用TensorFlow框架建立车速预测模型,通过机器学习不断调整优化模型。根据优化后的车速模型预测未来交通流状态变化趋势,交通信号决策系统能够在不同的交通流状态下自适应决策采取不同的绿波信号配时方案。通过VISSIM仿真结果表明,交通信号决策系统能够显著降低道路的拥堵程度,有效降低了道路机动车的停车次数和停车延误,极大地提高路网的运行效率,增大区域协调控制系统的自动化。     

基于仿真的城市信号交叉口优化与评估

交叉口作为交通流的中转站,其路口的拥堵影响着整个交通路网的安全与效率,信号控制优化与道路渠化能有效地缓解交叉口处拥堵。本文以恩施市金桂大道—金山大道交叉口为例,通过对交叉口处的交通路况、几何现状、交通流量和信号控制方案的分析,制定了交叉口信号控制优化与道路渠化结合的综合优化方案,最后利用VISSIM软件对优化前后的交叉口进行仿真分析,获得了车辆排队长度及平均延误时长。结果表明：实施新的优化方案后,车辆的排队长度显著降低,平均延误降低16.8%,有效缓解了交叉口处的拥堵,提高了道路的通行能力,相关研究可为恩施市道路的发展与规划提供有效参考。     

城市交通信号控制系统发展分析

作为城市道路交通管理的核心部分,城市交通信号控制系统是实现城市道路交通流有效运行的重要保障。本文对当前的城市交通信号控制系统的发展进行了分析。首先从技术和应用两个方面分析了当前交通信号控制系统的发展特点,包括新型检测技术对信号控制系统的推进、主动控制思想的引入、交通控制与仿真的集成、特种车辆优先考虑、过饱和交叉口的优化控制等,在此基础上探讨了未来城市交通信号控制发展的三个趋势:集成化、智能化、多模式化,以期对我国城市交通信号控制系统的发展有所启示。     

数据通信在城市交通控制系统中的应用

一、城市交通控制系统在改善道路通行状况、减轻交通堵塞所造成的损失等方面，城市交通控制系统发挥着不可替代的作用。城市交通控制系统是由计算机、信号控制机、检测系统、通信系统组成的。它依据路网上的实际交通流数据和各个路口机的运行参数，来对分散在各路口的信号控制机进行集中式的协调和控制，从整体上统一控制各个路口交通流和路口机运行参数，控制交通秩序。交通信息系统是城市交通控制系统的重要组成部分之一，它通过数据采集、传输和管理技术，使得交通管理人员能够准确获得路网各个路口的交通流量和路口机的运行状态，从而为…     

中小城市交通信号控制策略与方法研究

随着我国城镇化、工业化进程不断加快,中小城市建设得到迅猛发展,但交通拥堵问题也日益凸显,而成熟应用于特大城市、大城市的交通信号控制优化策略却未必适合直接应用于低出行距离、高出行次数、多种出行方式的中小城市。因此,本文在对中小城市交通信号概况分析的基础上,从交通设施、交通出行、道路资源等方面分析中小城市交通特征,提出适合中小城市的交通信号控制优化策略与方法。选取吴江区信号交叉口进行验证,结果表明本文提出的信号控制优化策略与方法能够有效提高中小城市信号控制水平。     

基于计算机视觉技术的交通场景检测平台的设计与应用

文章针对当前城市智慧交通监管的路口交通的饱和度、拥堵以及闯红灯等问题,设计了基于计算机视觉技术的交通场景检测平台,结合机器学习算法,并融合多项高新技术,实现对路口过往车辆的流量和车速检测,对机动车闯红灯、斑马线不礼让行人、占用公交车道、违停或违规越线等违章行为进行检测识别,为公共交通的管理提供极大便利,实现了“智慧交通”和“平安交通”。     

基于大数据分析和多模型融合的交通拥堵高效预测技术

文章利用可变系数加权优化方法对交通大数据进行聚类分析,并为了适用于常发性和偶发性拥堵,采用改进的两级加权优化ELM对分类进行模式识别,以期提高拥堵预测的精确度。同时,引入了上下游关联的拥堵传导模型,进一步提高拥堵预测的关联性。当预测到或已检测到交通拥堵时,在拥堵诱导上采用路网局部最优化模型为出行者规划路线,路网全局最优化模型则为管理部门使用并为未来规划提供辅助决策。仿真实验结果表明,多模型融合技术能预测较长时间后的拥堵情况并维持较高的准确率,为构建高效、经济、安全和便捷的现代化综合交通体系提供科技支撑。     

大数据技术驱动下的城市道路智能交通信号控制方法分析

为了分析大数据技术在信号灯控制领域中的应用方法和现实意义,首先,分析城市道路交通信号控制的基本方法,包括单个交叉口交通控制、多交叉口信号协调控制与区域交通信号控制;其次,结合目前交通信号控制技术现状,重点论述Agent代理程序、车道饱和流量以及信号配时方法在交通控制领域的应用路径。最终取得预期效果,这不仅可以提升交通信号数据的获取能力,还能加快城市道路的智能化管控进程。     

先进交通控制系统相关技术的探讨（一）

什么是先进的交通控制系统?笔者认为：先进的交通控制系统就是在对关键交通控制理论模型研究的基础上，集现代计算机、信息技术、通信技术、电子控制技术于一体的综合系统，是一种实时自适应信号区域控制系统，该系统依靠先进适用的交通控制模型和算法对交通控制参数(周期、绿信比和相位差)进行自动调整，从而实现路网交通信号的最佳协调控制。     

地理信息系统与城市交通管理

1 城市交通控制系统和地理信息系统1.1 城市交通控制系统城市交通控制系统在交通管理中应实现如下功能:一是控制参数的输入及人工调整,系统自动控制,能够实现绿波控制、单点控制、区域控制、手动控制、自动控制等多种交通控制方式;二是交通数据自动采集与处理,通过检测器可对路口每个车道的车流量、噪音等环境参数进行自动采集、存储和处理,在数据分析处理的基础上,提出改进方案,为改善城市交通控制提供决策依据;三是对系统硬件、软件的工作状态和故障情况进行全面监视。随着计算机技术和自动控制技术的发展、以及交通流理论的不断完善、…     

Integration of signal timing estimation model and dynamic traffic assignment in feedback loops: system design and case study

This paper presents an integrated framework for effective coupling of a signal timing estimation model and dynamic traffic assignment (DTA) in feedback loops. There are many challenges in effectively integrating signal timing tools with DTA software systems, such as data availability, exchange format, and system coupling. In this research, a tight coupling between a DTA model with various queue‐based simulation models and a quick estimation method Excel‐based signal control tool is achieved and tested. The presented framework design offers an automated solution for providing realistic signal timing parameters and intersection movement capacity allocation, especially for future year scenarios. The framework was used to design an open‐source data hub for multi‐resolution modeling in analysis, modeling and simulation applications, in which a typical regional planning model can be quickly converted to microscopic traffic simulation and signal optimization models. The coupling design and feedback loops are first demonstrated on a simple network, and we examine the theoretically important questions on the number of iterations required for reaching stable solutions in feedback loops. As shown in our experiment, the current coupled application becomes stable after about 30 iterations, when the capacity and signal timing parameters can quickly converge, while DTA's route switching model predominately determines and typically requires more iterations to reach a stable condition. A real‐world work zone case study illustrates how this application can be used to assess impacts of road construction or traffic incident events that disrupt normal traffic operations and cause route switching on multiple analysis levels. Copyright © 2014 John Wiley & Sons, Ltd.     

Study on road section environmental traffic capacity model and algorithm under double constraints

The coordinated development of city traffic and environment is a key research content in traffic field in twenty-first Century. Among them, road section environmental traffic capacity analysis is one of the important research issues. It can provide solid theoretical basis and reliable data support for road network traffic optimization control, road traffic pollution control and city traffic structure optimization. This paper analyzed main factors which impacted environmental traffic capacity from two aspects, including road capacity constraint conditions and road traffic pollution control constraint conditions. Then, road section environmental traffic capacity optimization model was established, and method of improved augmented Lagrange function was used to solve the model. Case study showed that, (1) The environmental traffic capacity optimal model and methodology were effective; (2) In order to ensure road section environmental traffic capacity greater than (or equal to) road capacity, some measures could be taken including adjusting motor vehicle type proportion as well as improving emission characteristics of motor vehicles exhausting pollutants.     

基于DSP的先进视频交通数据采集系统探讨

DSP是一种先进的视频交通数据采集系统,它操作简单,不仅能够有效的融入于道路交通数据采集系统,还能够与感应式十字路口信号灯控制系统、电子警察抓拍系统相结合,其双重功用被广泛应用于城市道路、高速公路交通数据采集,以及公路隧道、桥梁的意外事故监控系统中,并且可以适应各种天气,具有全天候检测的能力。文章从系统特点、检测数据精度、系统的多功能性及系统操作的方便性等方面介绍了该系统的先进性、实用性。     

Real-time network-wide traffic signal optimization considering long-term green ratios based on expected route flows

We propose a novel real-time network-wide traffic signal control scheme which is (1) applicable under modern data technologies, (2) flexible in response to variations of traffic flows due to its non-cyclic feature, (3) operable on a network-wide and real-time basis, and (4) capable of considering expected route flows in the form of long-term green time ratios for intersection movement. The proposed system has a two-level hierarchical architecture: (1) strategy level and (2) control level. Considering the optimal states for a long-term period found in the strategy level, the optimal signal timings for a short-term period are calculated in the control level which consists of two steps: (1) queue weight update and (2) signal optimization. Based on the ratio of the cumulative green time to the desired green time is the first step to update the queue weights, which are then used in the optimization to find signal timings for minimum total delay. A parametric queue weight function is developed, discussed and evaluated. Two numerical experiments were given. The first demonstrated that the proposed system performs effectively, and the second shows its capability in a real-world network.     

Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections

Urban air quality is generally poor at traffic intersections due to variations in vehicles’ speeds as they approach and leave. This paper examines the effect of traffic, vehicle and road characteristics on vehicular emissions with a view to understand a link between emissions and the most likely influencing and measurable characteristics. It demonstrates the relationships of traffic, vehicle and intersection characteristics with vehicular exhaust emissions and reviews the traffic flow and emission models. Most studies have found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, deceleration speed, queuing time in idle mode with a red signal time, acceleration speed, queue length, traffic-flow rate and ambient conditions. The vehicular composition also affects emissions. These parameters can be quantified and incorporated into the emission models. There is no validated methodology to quantify some non-measurable parameters such as driving behaviour, pedestrian activity, and road conditions     

Efficient intersection control for minimally guided vehicles: A self-organised and decentralised approach

An important question for the practical applicability of the highly efficient traffic intersection control is about the minimal level of intelligence the vehicles need to have so as to move beyond the traffic light control. We propose an efficient intersection traffic control scheme without the traffic lights, that only requires a majority of vehicles on the road to be equipped with a simple driver assistance system. The algorithm of our scheme is completely decentralised, and takes into full account the non-linear interaction between the vehicles at high density. For vehicles approaching the intersection in different directions, our algorithm imposes simple interactions between vehicles around the intersection, by defining specific conditions on the real-time basis, for which the involved vehicles are required to briefly adjust their dynamics. This leads to a self-organised traffic flow that is safe, robust, and efficient. We also take into account of the driver comfort level and study its effect on the control efficiency. The scheme has low technological barrier, minimal impact on the conventional driving behaviour, and can coexist with the traffic light control. It also has the advantages of being easily scalable, and fully compatible with both the conventional road systems as well as the futuristic scenario in which driverless vehicles dominate the road. The mathematical formulation of our scheme permits large scale realistic numerical simulations of busy intersections, allowing a more complete evaluation of the control performance, instead of just the collision avoidance at the intersection.     

Using high-resolution event-based data for traffic modeling and control: An overview

Research on using high-resolution event-based data for traffic modeling and control is still at early stage. In this paper, we provide a comprehensive overview on what has been achieved and also think ahead on what can be achieved in the future. It is our opinion that using high-resolution event data, instead of conventional aggregate data, could bring significant improvements to current research and practices in traffic engineering. Event data records the times when a vehicle arrives at and departs from a vehicle detector. From that, individual vehicle’s on-detector-time and time gap between two consecutive vehicles can be derived. Such detailed information is of great importance for traffic modeling and control. As reviewed in this paper, current research has demonstrated that event data are extremely helpful in the fields of detector error diagnosis, vehicle classification, freeway travel time estimation, arterial performance measure, signal control optimization, traffic safety, traffic flow theory, and environmental studies. In addition, the cost of event data collection is low compared to other data collection techniques since event data can be directly collected from existing controller cabinet without any changes on the infrastructure, and can be continuously collected in 24/7 mode. This brings many research opportunities as suggested in the paper.     

A two-stage fuzzy logic controller for traffic signals

This paper presents the design and evaluation of a fuzzy logic traffic signal controller for an isolated intersection. The controller is designed to be responsive to real-time traffic demands. The fuzzy controller uses vehicle loop detectors, placed upstream of the intersection on each approach, to measure approach flows and estimate queues. These data are used to decide, at regular time intervals, whether to extend or terminate the current signal phase. These decisions are made using a two-stage fuzzy logic procedure. In the first stage, observed approach traffic flows are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine whether the current signal phase should be extended or terminated. The performance of this controller is compared to that of a traffic-actuated controller for different traffic conditions on a simulated four-approach intersection.     

New approach for developing warrants of protected left-turn phase at signalized intersections

The research embodied in this paper presents a new approach for the development of guidelines for the installation of a protected left-turn phase at signalized intersections when permissive-only left-turn operation is present. This approach is based on maintaining intersection traffic operation at optimum efficiency. Three analyses were presented and discussed and they involved the use of the new approach on some hypothetical basic scenarios at a four-legged intersection with single lane in each approach. The first scenario involved exclusive left-turn lane operation while the other two scenarios involved shared-lane operation. Exhaustive signal optimization analyses were conducted using a signal optimization software package called “Signal Expert”. Regression models were developed from optimization results that allow the analyst to make the decision on protected left-turn phase installation using the basic input data of signal timing design without the need to perform field measurements. The regression results showed that the transition from permissive to protected/permissive left-turn operation, based on system optimization, is mainly a function of traffic conditions and that this transition (interface) is predictable. The results also suggested that these warrants are of reasonable accuracy when compared with those in the current practice.     

Spatiotemporal intersection control in a connected and automated vehicle environment

Current research on traffic control has focused on the optimization of either traffic signals or vehicle trajectories. With the rapid development of connected and automated vehicle (CAV) technologies, vehicles equipped with dedicated short-range communications (DSRC) can communicate not only with other CAVs but also with infrastructure. Joint control of vehicle trajectories and traffic signals becomes feasible and may achieve greater benefits regarding system efficiency and environmental sustainability. Traffic control framework is expected to be extended from one dimension (either spatial or temporal) to two dimensions (spatiotemporal). This paper investigates a joint control framework for isolated intersections. The control framework is modeled as a two-stage optimization problem with signal optimization at the first stage and vehicle trajectory control at the second stage. The signal optimization is modeled as a dynamic programming (DP) problem with the objective to minimize vehicle delay. Optimal control theory is applied to the vehicle trajectory control problem with the objective to minimize fuel consumption and emissions. A simplified objective function is adopted to get analytical solutions to the optimal control problem so that the two-stage model is solved efficiently. Simulation results show that the proposed joint control framework is able to reduce both vehicle delay and emissions under a variety of demand levels compared to fixed-time and adaptive signal control when vehicle trajectories are not optimized. The reduced vehicle delay and CO₂ emissions can be as much as 24.0% and 13.8%, respectively for a simple two-phase intersection. Sensitivity analysis suggests that maximum acceleration and deceleration rates have a significant impact on the performance regarding both vehicle delay and emission reduction. Further extension to a full eight-phase intersection shows a similar pattern of delay and emission reduction by the joint control framework.