信号控制下交叉口延误计算方法研究

为了对交通信号控制参数进行优化,需要对交叉口延误进行定量的分析与计算。根据信号控制交叉口理论,在以往定时信号延误研究的基础上,基于交叉口一个进口方向的车辆延误分析,针对交叉口各进口方向同时处于非饱和与同时处于过饱和交通状况,分析并推导了交叉口延误公式.并用具体的算例说明了公式的用法。公式表明了交叉口延误与信号控制参数、车辆到达率等参数之间的动态关系,为进一步研究交通信号自适应控制方法和建立交通信号控制参数优化的性能指标函数提供了信息。     

智能网联混合交通流交叉口控制：研究进展与前沿

交叉口是城市道路交通运行的瓶颈点,是造成交通拥堵的问题所在。交通控制是调控交通流、预防和缓解交通拥堵的关键策略,在效费比上具有较大优势。智能网联、自动驾驶技术的发展催生了常规车辆(Regular Vehicle, RV)、网联车辆(Connected Vehicle, CV)和智能网联车辆(Connected and Automated Vehicle, CAV)组成的智能网联新型混合交通流,推动着城市道路交通控制对象、数据环境和控制手段的变革,为交通控制提出巨大挑战的同时,也为交通控制理论方法的创新发展创造了新的条件。智能网联混合交通流交叉口控制已成为国内外研究热点,尚处于研究起步阶段。根据路权特征,先从单点交叉口、干线交叉口和路网多交叉口3个层面梳理智能网联混合交通流环境下的共用设施交叉口控制研究,包括交通信号配时、车辆轨迹/路径规划以及车辆轨迹-信号配时协同控制。然后介绍自动驾驶专用设施交叉口控制研究,包括CAV专用车道、CAV专用路段、CAV专用区域和快速公交-CAV混合专用车道。通过对现有成果的梳理发现：虽然新型混合交通流交叉口控制研究取得了部分进展,但RV驾驶行为的随机性、...     

A self-regulation traffic-condition-based route guidance strategy with realistic considerations: Overlapping routes,stochastic traffic,and signalized intersections

Variable message signs that provide various types of route guidance information have been widely deployed in large cities. To release proper information only using easily collected data, a simple traffic-condition-based (TCB) route guidance strategy was recently proposed. The strategy works based on the estimation of free-flow and congested traffic conditions and is capable of approximating user optimal equilibrium stably. Due to little consideration of the complexity of urban road networks, the TCB strategy is still away from field applications in urban areas. To further push the strategy toward field tests, this article improves the TCB strategy in the following aspects: supplementing the strategy with a self-regulation ability by considering existing traffic conditions; decomposing link capacity to solve the problem of overlapping routes by comparing link capacity on alternative routes; coping with stochastic traffic; and the impact of signalized intersections by utilizing aggregated data. A scenario for an urban road network in Beijing, China, is simulated to test the improved strategy, and the simulation results clearly indicate the effectiveness of the proposed improvements. The improvements extend the TCB strategy on moderately complicated urban road networks, and still have the advantages of simple diversion rules, easily obtained input data, and stable and effective diversion processes.     

A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO₂ relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal reservation scheme, ensure that vehicles proceed through the intersection without colliding with other vehicles while at the same time reducing the intersection delay and environmental impacts. Specifically, the spatiotemporal reservation scheme provides each vehicle a collision-free path that is decomposed into a speed profile along with navigational instructions. The integration of the developed microscopic traffic simulator with instantaneous emission model, provides improved assessments of the environmental impact of traffic control strategies at intersections. The simulator architecture integrates several ITM algorithms, vehicle sensors, V2V/V2I communications, and emission and fuel consumption models. Each vehicle is modeled by an agent and each agent provides information depending on the specific vehicle sensors. The ITM system is supported by V2V and V2I communications, allowing the exchange of information among vehicles and infrastructure. The data include the estimated vehicle position and speed. Compared with traditional traffic management techniques, the simulation results prove that the proposed ITM system reduces CO₂ emissions significantly. The research also shows that these reductions are more significant when the traffic flow increases.