Crowd behaviour

Last week, one of my friends pointed out to me that my many recent blog articles have been only on the energy efficiency topic and are not as unpredictable and/or interesting as the earlier ones. So this time am making a conscious attempt at not writing about energy. There is lot of construction activity in Bangalore and the place where I live in. The construction is not just restricted to residences but increased number of residences puts pressure on municipal corporation to provide more water and handle sewage. The road outside where we live, has been dug to lay in water and all kinds of pipes. That means our only road that gets us out of layout is closed and as is common place – a new temporary road has been found out. That road can not handle the pressures of the traffic. I was thinking about this scenario and it gave me an idea of today’s topic. Is there a deterministic (non-random) way of assessing the crowd traffic and its impact on better understanding of crowd behaviour, improved design of the built infrastructure? Crowd is being used in a generic sense and although it is about a group of people, here it is being used in a more generic sense as you would find anywhere in India – in that it is a collection of group of people, herd of cows and goats, a group of auto rickshaws, a grop of water tankers in summer and in general a group of vehicles that move in all possible directions even though the road may be straight ! If you leave in time, what is the probability in a scientific way of reaching your destination in a fixed time? Does crowd monitoring help? Let us explore.

Although crowds are made up of independent individuals or entities (remember not to leave aside the cows and buffalos and even vehicles that are driven by individuals) , each with their own objectives, intelligence and behaviour patterns, the behaviour of crowds is widely understood to have collective characterisitics which can be described in general terms. Since the Roman times, the mob rule or mob mentality is an implication of a crowd that is something other than the sum of its individual parts and that it possesses behaviour patterns which differ from the behaviour expected individually from its participants. If there is any scientific basis for the study of crowd behaviour, it must belong to the realm of social sciences and psychology, and that the mere mortals of physical sciences and engineering have limited or no business in getting involved with such studies. But I came across an article a few years ago that was interesting. It said understanding of field theory and flow dynamics is good enough to get started on getting a solution to crowd monitoring and may offer solutions that are technology based and control the crowd behaviour using developments in image processing and image understanding.

The article I mentioned above was one of IEE publications. Do not recall which one. But the thought process left an impression. It said our knowledge of study of gases can provide us insgihts into the study of understanding crowd behaviour. After all, a gas is made up of individual molecules, moving about more-or-less independently of each other, with differing velocities and directions. The ideal-gas theory provides a reasonably accurate basis of predicting the properties and behaviour of gases over a wide range of conditions, without considering behaviour of individual molecules. This was a major breakthrough and something not possible to conceive if the notion had prevailed that equations of motion for each individual molecule had to be solved in order to predict overall behaviour of a gas in any particular direction. What it also proved was an observation in mob rule, that the overall behaviour is something other than the sum total of its parts.

Now where does this similarity end? Surely the molecules of gas are different from cows and buffaloes and individuals and vehicles. They are far more complex and have a mind of their own. The theory of gases does not attribute intelligence to molecules. The possessed crowd that moves in a particular direction in a mindless pursuit is akin to the behaviour of charged particles under the influence of electric field. When you have a temporary road that is bi-directional, you not only have a crowd moving in one direction but in both and capable of inducing collisions, like particles of opposite charges.

I have known many techniques in recent years in image processing that use those well-established techniques for monitoring and collection of data on crowd behaviour. A key factor in the solutions is the use of techniques where inferences can be drawn by rising above individual pixels or objects – a notion akin to rising above molecules and individuals that make up the spaces.

Whether all of this can lead me to predict fixed time of arrival at destination is anybody’s guess. But it does provide insights into crowd behaviour and probably an interesting application of science that can make your journey to the destination enjoyable.

The Green Rebound

What is a rebound effect? In traditional sense, it is used in medicine to describe an effect where it shows the tendency of medication, when discontinued, causes a return of symptoms being treated to be more pronounced than before. So what has ‘green’ got to do with the rebound effect? Well, couple of weeks ago, there was an article in Nature News that has rekindled interest in this topic; which has been a point of discussion for many days now, I must confess. The green rebound, as I call it, is the rebound effect as applied to energy conservation. I have been emphasizing through many articles before on the need to be energy-prudent, to be energy conscious and hence do things which conserve energy. But just what happens when you save?

The green rebound, which is application of rebound effect to energy conservation, is a term that describes the effect that the lower costs of energy services, due to increased energy efficiency, has on consumer behavior. It generally indicates either an increase in number of hours of energy use, or increase in quality of energy use thereby creating a situation where you end up using more than you save and hence portraying a kind of a paradox.

For instance, if a 18W compact fluorescent bulb replaces a 75W incandescent bulb, the energy saving should be 76%. However, it seldom is. Consumers, realizing that the lighting now costs less per hour to run, are often less concerned with switching it off; in fact, they may intentionally leave it on all night. Thus, they ‘take back’ some of the energy savings in the form of higher levels of energy service (more hours of light). This is particularly the case where the past level of energy services, such as heating or cooling, was considered inadequate.

What is not debated is whether the effect exists. You may be surprised to know it does. What is being debated is the extent of this rebound? Like all other economic models, this one too is tending to overstate the reality.

1. The actual resource savings are higher than expected – the rebound effect is negative. This is unusual, and can only occur in certain specific situations (e.g. if the government mandates the use of more resource efficient technologies that are also more costly to use).

2. The actual savings are less than expected savings – the rebound effect is between 0% and 100%. This is sometimes known as 'take-back', and is the most common result of empirical studies on individual markets.

3. The actual resource savings are negative – the rebound effect is higher than 100%. This situation is commonly known as the Jevons paradox, and is sometimes referred to as 'back-fire'.

The rebound effect is a phenomenon based on economic theory and long-term historical studies, but as with all economic observations its magnitude is a matter of considerable dispute. Its significance for energy olicy has increased over the last two decades, with the claim by energy analysts in the 1970s, and later by environmentalists in the late 1980s, that increasing energy efficiency would lead to reduced national energy consumption, and hence lower green gas emissions. Whether this claim is feasible depends crucially on the extent of the rebound effect: if it is small (less than 100%) then energy efficiency improvements will lead to lower energy consumption, if it is large (greater than 100%) then energy consumption will be higher. Note the use of the relative terms ‘lower’ and ‘higher’: what exactly they are relative to has often been left unstated and has been a cause of much confusion in energy policy debates. Sometimes it refers to current energy consumption, at other times to a reduction in the future rate of growth in energy onsumption.

The claim that increasing energy efficiency would lead to reduced national energy consumption was first challenged by Len Brookes in 1979, in his review of Leach's pioneering work, A Low Energy Strategy for the UK, when he criticized Leach's approach to estimating national energy savings because of its failure to consider macroeconomic factors. This was followed in the early 1980s by similar criticism by Daniel Khazzoom of the work of Amory Lovins. The criticism of Brookes and Khazzoom was given the name of the Khazzoom-Brookes (KB) postulate by the economist Harry Saunders in 1992. The KB postulate may be described as: those energy efficiency improvements that, on the broadest considerations, are economically justified at the microlevel lead to higher levels of energy consumption at the macrolevel than in the absence of such improvements.

This work provided a theoretical grounding for empirical studies and played an important role in framing the problem of the rebound effect. It also reinforced an emerging ideological divide between energy economists on the extent of the yet to be named effect. The two tightly held positions are:

1. Technological improvements in energy efficiency enable economic growth that was otherwise impossible without the improvement; as such, energy efficiency improvements will usually back-fire in the long term.

2. Technological improvements in energy efficiency may result in a small take-back. However, even in the long term, energy efficiency improvements usually result in large overall energy savings.

Even though many studies have been undertaken in this area, neither position has yet claimed a consensus view in the academic literature. Recent studies have demonstrated that direct rebound effects are significant (about 30% for energy), but that there is not enough information about indirect effects to know whether or how often back-fire occurs. Economists tend to the first position, but most governments, businesses, and environmental groups adhere to the second.

The Nature news mentions a report from the Breakthrough Institute, an advocacy group based in Oakland, California, that is pushing for huge government investment in clean-energy technologies, suggests that various types of rebound effect could negate much, if not all, of the emissions reductions gained through efficiency. Energy efficiency should still be pursued vigorously as a way to bolster the economy and free up money for investments in low-carbon technologies, the institute says, but rosy assumptions about emissions reductions should be treated with caution.

Should there be an alarm due to such reports that you may across? Well no. Every coin has two sides and if anyone assumes that this report makes a non-case of energy efficiency, that is far-fetched. It only means that as we start conserving, we need to be more careful in terms of usage and hence I believe monitoring of your energy resources not just once in a while, but on a continuous basis will ensure the rebound does not take place. So monitoring is like that medicine, which once withdrawn, can have rebound effect.