可以自组织的交通信号灯

发布日期:2019-11-23 10:24
       要改善交通流,与其说是向其施加特定行为,不如说是创造条件使得交通以最有效的方式自发地进行自我组织。这一理念并不总是能被管理者和规划者所接受,但它正逐渐成为处理交通乃至所有社会现象的最好方法——即放弃自上而下的控制,相信如给予其机会,复杂系统能够自下而上地去发掘出自身有效的行为模式。我们可以通过重新考察如何协调交通信号灯来说明这一点。通常的方法是将一连串十字路口信号灯的开关时间的周期序列进行同步。但在这个方法中,信号灯的开关序列是进行周期性的改变更好,还是无论交通条件如何都保持不变更好?答案是两者都缺少科学依据。事实上,让每个信号灯随时根据交通条件做出反应才是更好的方法。让交通信号灯自我组织的想法可能听起来会导致灾难。有人可能会问,怎么能保证一个路口的最佳安排也会适合其他路口呢?然而,如果除了所在路口的交通状况,每个信号灯还能获取相邻路口的交通信息,通过这种信息共享,整个系统就能够随时获取比严格的周期性序列变化更加有效和灵活的解决方案。

       这种想法的具体操作方式是,在每个路口前放置一个交通传感器,向每个独立的信号灯控制系统提供车辆驶入流量的信息。这样就可以计算出交通网络中各个部分的预期延迟时间以及相应的“交通压力”。然后,优先给予交通压力最大的区域绿色信号灯。在这种方式中,信号灯并不控制交通,而是反过来被交通情况所控制。一些偶然的波动,例如某些线路上暂时的空闲现象,可以被利用来缓解其他区域的拥堵。在该方法实际的运行中,出现了惊人的同步现象:例如绿色信号灯会沿着交通网络呈现“波浪”状的流动。

       对于自主信号灯进行自组织的交通网络的模拟结果显示,与目前最先进的传统控制方法相比,该方法可以将总体平均交通延迟时间减少30%-40%,交通网络中单个车辆行驶时间的可预测性也得到了较大提升。

图1 自组织交通信号灯的调控机制
       
       右图显示的四向多车道十字路口运行了自适应周期的信号灯。左图显示,随着总体交通入流密度(这里表示为利用率u)的增加,信号灯最佳序列和时间间隔也在发生变化(来源:Dirk Helbing,苏黎世联邦理工学院)。
 
       在德国德累斯顿市的繁忙市中心,有13个混杂着电车轨道和人行横道的十字路口,对于这一区域交通网络的模拟结果显示,自组织的信号灯可以显著减少包括步行在内的所有交通模式的等待时间。同样的原理也适用于其他交通控制措施,例如速度限制:允许车辆根据实时的交通流情况调整速度可减少拥堵和延时。
 
以下为英文原文:

Traffic Lights Can Organize Themselves

Philip Ball

Improving traffic flow is not so much a matter of imposing particular behaviours as of creatingthe conditions under which the traffic can spontaneously organize itself in the most efficient manner. That philosophy doesn’t always sit easily with managers and planners, but it is looking increasingly to be the best way to approach all manner of social phenomena: to relinquish top-down control in favour of a faith in the bottom-up capacity of complex systems to find their own efficient modes of behaviour, given the opportunity.

This is illustrated by a reconsideration of how to coordinate traffic lights. The normal approach is to synchronize a periodic sequence of on-off times for aseries of lights at a cluster of intersections. But there is no reason to suppose either that the best sequence is strictly periodic or that it has toremain the same regardless of the traffic conditions. It turns out to be better to allow each individual traffic light to respond adaptively to the flow conditions at any moment.

The notion of allowing traffic signals individual autonomy could sound like a recipe for disaster– why should there be any guarantee that what is ‘best’ for one intersection will also suit what is happening at the others? However, if each signal issupplied with information not only about the traffic at that particularjunction it but also about the traffic coming from neighbouring junctions, thissharing of information can enable the system as a whole to find more effective, flexible solutions at any moment than are available from an insistence on regimented periodicity.

The idea is that traffic sensors placed a little before an intersection feed information about the incoming flow to each individual light-controlling system. This makes it possible to calculate the expected delays, and corresponding ‘trafficpressures’, at different parts of the network. Priority for green signals is then given to those parts experiencing the greatest pressures. In this way, the traffic itself controls the lights, rather than vice versa. Chance fluctuations,such as temporary lulls in the traffic on some routes, can be exploited torelieve congestion elsewhere. The behaviour that emerges can in fact look surprisingly synchronized, for example in the appearance of ‘waves’ of green lights that travel through the network.

Simulations of traffic flow on a network where autonomous lights are coordinated in this way show that overall average delays can be reduced by 30–40% relative to today’s state-of-the-art conventional control methods, and that the travel times for individual vehicles through the network actually become more predictable.

A simulationstudy of a real-world urban network – 13 intersections in the busy city centre of Dresden, complicated by tram lines and pedestrian crossings – has shown that self-organized traffic lights can significantly reduce the waiting times for all the modes of transport, including pedestrians. The same principle can be applied to other traffic-control measures such as speed limits: allowing them to adapt to the prevailing flow conditions can reduce congestion and delays.
 
参考文献:(英)菲利普•鲍尔著, 韩昊英译, 赖世刚校. 社会为何如此复杂:用新科学应对二十一世纪的挑战. 北京:科学出版社,2015.
本文作者在原书的基础上,重新撰写了文字。
 
作者简介:韩昊英
目前为浙江大学城乡规划学和公共管理学的教授、博士生导师,学术背景为建筑学、城乡规划学和公共管理学,曾在清华大学、日本东京大学、韩国首尔国立大学和加拿大多伦多大学攻读学位或访学研究。韩昊英从小生活在城市,热爱城市的历史和文化,喜欢观察和体验多样的城市生活。
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