Model based urban traffic control,part II: Coordinated model predictive controllers

The present paper describes how to use coordination between neighbouring intersections in order to improve the performance of urban traffic controllers. Both the local MPC (LMPC) introduced in the companion paper (Hao et al., 2018) and the coordinated MPC (CMPC) introduced in this paper use the urban cell transmission model (UCTM) (Hao et al., 2018) in order to predict the average delay of vehicles in the upstream links of each intersection, for different scenarios of switching times of the traffic lights at that intersection. The feedback controller selects the next switching times of the traffic light corresponding to the shortest predicted average delay. While the local MPC (Hao et al., 2018) only uses local measurements of traffic in the links connected to the intersection in comparing the performance of different scenarios, the CMPC approach improves the accuracy of the performance predictions by allowing a control agent to exchange information about planned switching times with control agents at all neighbouring intersections. Compared to local MPC the offline information on average flow rates from neighbouring intersections is replaced in coordinated MPC by additional online information on when the neighbouring intersections plan to send vehicles to the intersection under control. To achieve good coordination planned switching times should not change too often, hence a cost for changing planned schedules from one decision time to the next decision time is added to the cost function. In order to improve the stability properties of CMPC a prediction of the sum of squared queue sizes is used whenever some downstream queues of an intersection become too long. Only scenarios that decrease this sum of squares of local queues are considered for possible implementation. This stabilization criterion is shown experimentally to further improve the performance of our controller. In particular it leads to a significant reduction of the queues that build up at the edges of the traffic region under control. We compare via simulation the average delay of vehicles travelling on a simple 4 by 4 Manhattan grid, for traffic lights with pre-timed control, traffic lights using the local MPC controller (Hao et al., 2018), and coordinated MPC (with and without the stabilizing condition). These simulations show that the proposed CMPC achieves a significant reduction in delay for different traffic conditions in comparison to these other strategies.     

Congestion and pollution consequences of driving-to-school trips: A case study in Beijing

Parents compete for high-quality education for their children by enrolling them in good schools. However, in a Chinese mega-city like Beijing, three factors jointly lead to the spatial separation between schools and homes: the centralized public goods provision mechanism, the historical dependency in school location, and the constrained supply of housing in downtown. Without an adequate number of school buses, this spatial separation of schools and homes triggers the numerous long-distance driving-to-school trips by private vehicle during workday morning rush hours in Beijing. We use the start and end dates of “school holiday” as exogenous repeated shocks to the aggregate traffic congestion, and employ the two-stage least squares (2SLS) regression approach to examine the congestion and pollution consequences of such driving-to-school trips in Beijing. We find that, all else being equal, workdays during school holidays have a traffic congestion index 20% lower than that of non-school-holiday workdays. Such a sharp reduction in congestion leads to a significant decrease in PM₁₀ concentration. Policymakers should lower such “extra” congestion and environmental costs via optimizing the spatial balance between school supply and demand.     

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.     

Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide.     

上海松江区现代有轨电车规划研究

现代有轨电车因其环保、舒适、高效、低造价、高品质等特点,在国际上得到广泛应用,我国多个城市也在规划和建设之中。但是,由于其在国内尚为一种全新的交通方式,没有标准或规范予以指导,规划及设计体系不完善,有些已建项目已呈现问题。文章结合上海松江区规划背景及交通特征,阐述有轨电车示范线T1、T2线的布局规划、建设的必要性及适应性,为即将开展有轨电车规划及建设的城市提供借鉴与参考。     

CACC车头时距与混合交通流稳定性的解析关系

研究协同自适应巡航控制(Cooperative Adaptive Cruise Control，CACC)车头时距对不同CACC比例下混合交通流稳定性的影响关系，进而为CACC车头时距设计提供参考. 应用优化速度模型(Optimal Velocity Model，OVM)作为手动车辆的跟驰模型，PATH真车实验标定的模型作为CACC车辆的跟驰模型. 基于传递函数理论，推导混合交通流稳定性判别条件，计算关于CACC比例与平衡态速度的混合交通流稳定域. 分析混合交通流在任意速度下稳定所需满足的临界CACC比例与CACC车头时距的解析关系，提出随CACC比例增加的可变 CACC车头时距设计策略，并通过数值仿真实验验证所提可变CACC车头时距策略的正确性. 研究结果表明：在所提可变CACC车头时距策略下，CACC车头时距随CACC比例增加而逐渐降低，避免取值较大影响混合交通流通行能力的提升；当CACC比例大于35%时，混合交通流在任意速度下稳定.研究结果可为大规模CACC真车实验的实施提供理论设计参考.     

基于需求弹性的城市公交票价优化方法及实证分析

城市公交票价是公交系统健康发展的重要因素，票价制定需兼顾公交企业的市场性和公益性双重属性，在保证服务质量的同时，考虑运营成本和最大限度吸引公交需求，实现经济效益和社会效益的双赢.在本文中，根据用户均衡理论，构建了城市多方式交通出行的需求分析模型，采用灵敏度分析方法给出了城市公交价格-需求弹性的计算方法.在此基础上，充分考虑了各种方式的交通特征、公交需求弹性、公交运营成本及政府限价等因素，提出了城市公交票价优化的数学规划模型，并给出了求解算法.最后，以国内某城市居民出行调查及公交运营数据为基础，分析了不同条件下公交客运需求的变化规律及城市公交票价的优化策略.     

基于客流需求的城市轨道交通动态时刻表优化模型

为使城市轨道交通列车运行时刻表更贴合客流需求,依据不断变化的客流需求确定每列车的发车时刻和停站时间,采用多目标优化方法构建以乘客出行时间费用和列车运行时间费用最小为目标、列车发车时刻和停站时间为决策变量的城市轨道交通动态时刻表优化模型,并采用粒子群算法求解。以广州地铁13号线为例进行验证,结果表明优化后的时刻表更满足客流需求,能有效地提高乘客出行效率,具有更好的动态适应性。     

共享停车泊位数量可变下交通流逐日演化规律

为了揭示在共享停车泊位数量可变条件下的网络交通流逐日演化规律,首先构建了共享泊位交易系统,并考虑了交易市场中的共享泊位提供者可以选择2种异质性的价格预期方式,即理性预期方式和幼稚预期方式;而后对共享泊位的均衡价格、2种提供者的占比差、高峰时段公交和小汽车需求的演化规律进行了分析;其次,以2条平行路径的路网为例,对网络交通流量分配的最终演化结果进行了分析;最后,在对上述2个系统的最终演化状态给出定量判据后,以北京市实际路网为例进行了数值试验。理论分析和数值试验结果表明:①对于共享泊位交易系统,若供给曲线斜率小于需求曲线斜率,则共享泊位交易系统的唯一均衡解可实现无条件渐进稳定;否则若理性提供者的交易与预测成本之和大于幼稚提供者,则存在临界提供者选择强度,使得共享泊位交易系统在大于此临界值条件下出现分岔或混沌现象;②对于网络交通流系统,若出行成本对路径流量敏感度小,路径选择概率对出行成本敏感度小,小汽车需求量不大,则系统唯一的均衡解可能是渐进稳定的,否则系统会出现分岔或混沌状态;③当共享泊位交易系统处于渐进稳定状态时,若提供者对共享泊位的价格变动不敏感,用户对其价格变动敏感,潜在共享泊位需求量不大,理性提供者的交易与预测成本之和并非远大于幼稚提供者,提供者选择强度不大,则由于受到共享泊位交易总量的限制,高峰时段的均衡小汽车需求不大,导致网络交通流系统的最终演化状态容易趋向于渐进稳定;④当共享泊位交易系统处于混沌状态时,网络交通流系统会产生更加严重的分岔与混沌现象。