A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection

The advancements in communication and sensing technologies can be exploited to assist the drivers in making better decisions. In this paper, we consider the design of a real-time cooperative eco-driving strategy for a group of vehicles with mixed automated vehicles (AVs) and human-driven vehicles (HVs). The lead vehicles in the platoon can receive the signal phase and timing information via vehicle-to-infrastructure (V2I) communication and the traffic states of both the preceding vehicle and current platoon via vehicle-to-vehicle (V2V) communication. We propose a receding horizon model predictive control (MPC) method to minimise the fuel consumption for platoons and drive the platoons to pass the intersection on a green phase. The method is then extended to dynamic platoon splitting and merging rules for cooperation among AVs and HVs in response to the high variation in urban traffic flow. Extensive simulation tests are also conducted to demonstrate the performance of the model in various conditions in the mixed traffic flow and different penetration rates of AVs. Our model shows that the cooperation between AVs and HVs can further smooth out the trajectory of the latter and reduce the fuel consumption of the entire traffic system, especially for the low penetration of AVs. It is noteworthy that the proposed model does not compromise the traffic efficiency and the driving comfort while achieving the eco-driving strategy.     

物流一体化理论对中国第三方物流企业发展的启示

物流一体化作为一体化管理的一种形式,是20世纪末期最有影响的物流趋势之一,并因具有使物流活动各环节实现协同管理,达到共同利益最优化的功能而受到人们的广泛关注。物流一体化理论的运用不仅大大降低了物流总成本,而且提高了物流服务水平和企业的竞争力,物流一体化已成为物流管理发展的主题。本文论述了物流一体化理论及发展、物流一体化的重要性、我国实现物流一体化理论应注意解决的问题及物流一体化理论对中国第三方物流企业发展的启示。     

基于合作对策的江苏沿江港口合作竞争研究

江苏沿江港口群功能定位混乱、恶性竞争严重,不利于其整体竞争力的提高和"组合港"的发展,为此有必要形成良性竞争的合作模式。利用合作对策理论,建立了沿江港口在航线开辟上的合作模型。研究发现,沿江港口间的合作是有实质意义的,但各个港口在联盟中的地位是不同的,必须建立一定的利益分配原则来维持联盟的稳定性。研究结果表明:基于合作对策的沿江港口合作竞争模型有效地揭示各港的动态竞争行为,为研究港口合作竞争提供了一条新的途径。     

Cooperative traffic control of a mixed network with two urban regions and a freeway

Currently most optimization methods for urban transport networks (i) are suited for networks with simplified dynamics that are far from real-sized networks or (ii) apply decentralized control, which is not appropriate for heterogeneously loaded networks or (iii) investigate good-quality solutions through micro-simulation models and scenario analysis, which make the problem intractable in real time. In principle, traffic management decisions for different sub-systems of a transport network (urban, freeway) are controlled by operational rules that are network specific and independent from one traffic authority to another. In this paper, the macroscopic traffic modeling and control of a large-scale mixed transportation network consisting of a freeway and an urban network is tackled. The urban network is partitioned into two regions, each one with a well-defined Macroscopic Fundamental Diagram (MFD), i.e. a unimodal and low-scatter relationship between region density and outflow. The freeway is regarded as one alternative commuting route which has one on-ramp and one off-ramp within each urban region. The urban and freeway flow dynamics are formulated with the tool of MFD and asymmetric cell transmission model, respectively. Perimeter controllers on the border of the urban regions operating to manipulate the perimeter interflow between the two regions, and controllers at the on-ramps for ramp metering are considered to control the flow distribution in the mixed network. The optimal traffic control problem is solved by a Model Predictive Control (MPC) approach in order to minimize total delay in the entire network. Several control policies with different levels of urban-freeway control coordination are introduced and tested to scrutinize the characteristics of the proposed controllers. Numerical results demonstrate how different levels of coordination improve the performance once compared with independent control for freeway and urban network. The approach presented in this paper can be extended to implement efficient real-world control strategies for large-scale mixed traffic networks.     

非规则铁路连续梁桥抗震体系优化

从非规则铁路连续梁桥各桥墩协同抗震的角度,引入墩底摇摆隔震及支座减隔震,以1座(60+100+60)m连续梁桥为例,建立全桥动力分析模型进行地震反应分析,研究具有中等高度(20~30m)实心桥墩的非规则铁路连续梁桥采用摇摆隔震的适用性,以及全桥采用支座减隔震时的桥墩优化配筋准则。结果表明:采用摇摆隔震时,摇摆墩墩底恒载轴力大,提离位移敏感性高,地震作用下墩顶位移可控制在较小的范围且提离后墩底弯矩变化稳定,易随其余各墩协同抗震,经抗震性能验算确定摇摆墩配筋率为0.6%;采用支座减隔震时,桥墩本身地震反应贡献率最高可达71%,桥墩惯性力主控墩底内力,以地震作用下各墩同步保持弹性为原则,优化后各墩配筋率依次为0.7%,0.3%,0.5%和0.7%。以上2种优化均可使非规则铁路连续梁桥达到"大震不坏"的设防水平。     

Modelling supported driving as an optimal control cycle: Framework and model characteristics

Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of automated vehicles are controlled to optimise a cost function, assuming other vehicles driving at stationary conditions over a prediction horizon. The flexibility of the framework is demonstrated with controller design of Adaptive Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and C-ACC model characteristics are investigated analytically, with focus on equilibrium solutions and stability properties. The proposed ACC model produces plausible human car-following behaviour and is unconditionally locally stable. By careful tuning of parameters, the ACC model generates similar stability characteristics as human driver models. The proposed C-ACC model results in convective downstream and absolute string instability, but not convective upstream string instability observed in human-driven traffic and in the ACC model. The control framework and analytical results provide insights into the influences of ACC and C-ACC systems on traffic flow operations.     

Handling Cut-In Vehicles in Strings of Cooperative Adaptive Cruise Control Vehicles

Cooperative adaptive cruise control (CACC) systems are a candidate to improve highway capacity by shortening headways and attenuating traffic disturbances. Although encouraging results have been obtained until now, a wide range of traffic circumstances has to be investigated in order to get reliable CACC systems driving on real roads. Among them, handling both vehicle-to-vehicle (V2V) communications-equipped and unequipped vehicles merging into the string of CACC vehicles is a commonly mentioned challenge. In this article, an algorithm for managing the transitions in response to cut-ins from V2V- or non-V2V-equipped vehicles is developed and tested using a string of four CACC vehicles. A CACC controller is implemented in four production Infiniti M56s vehicles and tested in real traffic, where non-V2V-equipped vehicles can cut in. The effects of a vehicle performing a cut-out are also investigated. Then responses to cut-ins by equipped and nonequipped vehicles are simulated for longer strings of vehicles using car-following models for both the production adaptive cruise control (ACC) system and the newly developed CACC controller. Results demonstrate that the CACC system is able to handle cut-in vehicles without causing major perturbations, while also reducing significantly the impact of this maneuver on the following vehicles, improving traffic flow.