A critical analysis of the effect of autonomous driving vehicles on traffic breakdown in mixed traffic flow is made. Classical adaptive cruise control (ACC) and ACC based on three-phase traffic theory (TPACC) are considered. We show that within a wide range of dynamic parameters of classical ACC, the ACC-vehicles can initiate traffic breakdown and reduce highway capacity. Contrarily, in the same range of parameters of TPACC, the TPACC-vehicles do not initiate traffic breakdown. To understand physical reasons for the effect of classical ACC- and TPACC-vehicles on traffic breakdown, we introduce a model of ACC that can be considered a combination of dynamic features of classical ACC and TPACC. With the use of this model, we find how the amplitude of a local speed disturbance caused by the ACC in a vicinity of a bottleneck and the probability of traffic breakdown depend on the dynamic parameters of the ACC.
Microscopic Theory of Traffic Flow Instability Governing Traffic Breakdown at Highway Bottlenecks: Growing Wave of Increase in Speed in Synchronized Flow
Enhanced Intelligent Driver Model to Access the Impact of Driving Strategies on Traffic Capacity
随着越来越多的车辆配备了自适应巡航控制（ACC），这种车辆的交通流的集体动态的影响变得相关。通过仿真研究了ACC车辆比例变化对交通流特性的影响。为了模拟ACC车辆，我们提出了一个新的汽车跟随模型，也作为ACC在真实汽车中实现的基础。该模型基于智能驾驶员模型[Treiber等人，Physical Review E 62，1805（2000）]，并继承了其直观的行为参数：期望的速度、加速度、舒适的减速和期望的最小时间间隔。然而，它消除了智能驾驶员模型在切入情况下有时不切实际的行为，随之而来的小间隙通常是由其他车辆在密集或拥挤的交通中变道引起的。仿真了不同ACC策略对故障前最大容量和故障后动态瓶颈容量的影响。通过适当的策略，我们发现灵敏度为0.3，即，ACC车辆增加1%将导致容量增加约0.3%。当考虑实际故障时的行驶时间时，这种灵敏度会成倍增加。
We present an algorithm to identify days that exhibit the seemingly paradoxical behaviour of high traffic flow and, simultaneously, a striking absence of traffic jams. We introduce the notion of high-performance days to refer to these days. The developed algorithm consists of three steps: step 1, based on the fundamental diagram (i.e. an empirical relation between the traffic flow and traffic density), we estimate the critical speed by using robust regression as a tool for labelling congested and uncongested data points; step 2, based on this labelling of the data, the breakdown probability ca…
Metastable States in Two-Lane Traffic Flow Models With Slow-To-Start Rule
利用计算机模拟，我们表明，亚稳态仍然发生在两车道交通模型慢启动规则。然而，这些亚稳态不再存在于存在侵略性驱动器（\textit{which do not look back before changing lanes}）的系统中。实际上，电路中仅存在一个积极驱动器会触发高流量状态的击穿。在这些系统中，稳态是唯一的，其松弛动力学应取决于车道变换概率$p_{ch}$和电路中存在的激进驾驶员的数量。研究还发现，弛豫时间$τ$以幂律形式发散：$τ\propto p_{ch}^{-β}, β=1$。
In this paper we consider the problem of estimating emissions due to vehicular traffic on complex networks, and minimizing their effect by regulating traffic at junctions. For the traffic evolution, we consider a Generic Second Order Model, which encompasses the majority of two-equations (i.e. second-order) models available in the literature, and extend it to road networks with merge and diverge junctions. The dynamics on the whole network is determined by selecting a solution to the Riemann Problems at junctions, i.e. the Cauchy problems with constant initial data on each incident road. The l…
Traffic jams in urban scenarios are often caused by bottlenecks related to the street topology and road infrastructure, e.g. traffic lights and merging of lanes. Instead of addressing traffic flow optimization in a static way by extending the road capacity through constructing additional streets, upcoming smart cities will exploit the availability of modern communication technologies to dynamically change the mobility behavior of individual vehicles. The underlying overall goal is to minimize the total dwell time of the vehicles within the road network. In this paper, different bottleneck-awar…
The fundamental diagram is an assumed functional relationship between traffic flow and traffic density. In practice, this relationship is noisy and exhibits significant statistical variability. On smart motorways, this variability is increased by variable speed limits that are not captured by the fundamental diagram. To study this variability, it is appropriate to consider the joint probability distribution function (pdf) of density and flow. We perform an empirical study of the variability in the relationship between flow and density using 74 days of data from 64 sections of London's M25. The…
