Our group focuses on traffic safety in Suzhou district and tries to find solutions for our local community. Our research involves assumptions, confirmation and the actions we should take to influence the community.
Traffic problems, as major problems all around the world, have become increasingly severe in the modern society, especially in densely populated metropolis. Due to the rising number of vehicles, which has an exponential increase every year, the number of traffic accidents in China rose drastically and reached approximately 110,000 dead and over 560,000 injured last year. These incredible data gave our group the will to find solutions to fix the traffic problems. In the big picture, our whole project will be divided into three parts: facts collecting, factors analysis and solutions finding.
In order to completely cure the traffic problems in China, our group started from investigating the global trend of traffic safety. From our searching of global information, the fact that road safety in China is way below the world average really caught our attention. Also, we realized that there is a gap in road safety between developed and developing countries. To fully understand this, we conducted further research on New York, USA to draw some experience from western world and find out the effective measures to lower the traffic accident rate in China. We figured out possible factors that might influence the gap:
- law restrictions,
- the car volume,
- the type of vehicles (namely the trucks ratio)
After this research we decided to put the focus in Suzhou to see whether the real situation is consistent with our assumptions. In order to achieve this goal, we went to 8 main roads of Suzhou to measure the traffic volume by measuring the number of cars passing through one point of the road within one minute. With the data of our observation we used statistic methods and we conclude that the traffic volume plays some role in the happening of the traffic accidents but the ratio of trucks in the total traffic cannot be one critical factor. We also distributed questionnaires to a random sample of about 215 people in streets. In our result, 174 people, which is 80.93% of the total sample, think the traffic volume will influence the accident rate, while only 105 people, which is 48.84% of the total, think the truck rate is responsible for the accident rate.
Our intent is to explore solutions for our current traffic situation in China. First, by our observation of the types of vehicles on roads, we discover that the three main types of vehicles used in China are private cars, motorcycles and bicycles. Knowing this, we then search the information of accident number for these three vehicles. It was easy to see that the unmotorized vehicles generally have a lower accident number than the motorized vehicles do, which also means that the use of unmotorized vehicles such as bicycles may drastically reduce the accident rate. Also, the results showed the traffic volume is a key factor that influences the rate of accidents. So, in order to reduce the traffic volume and the accidents ratio, our advise is to introduce the shared bicycles into Suzhou, which can reduce the accidents not only by alleviating the road pressure but also by substituting more high-accident vehicles into low-accident vehicles. Moreover, the drivers themselves are one key component of causes of accidents. We investigated on solutions of problems which are caused by drivers themselves like unfresh mind or fatigue driving. We searched the information of the number of traffic accidents during different time intervals in a day and the majority accidents clusters are in 8:00-11:00 and 18:00-19:00, which is reasonable since they are commuting hours. Therefore, another solution we thought of is that the time restrictions can be set in some high-accident roads to reduce the number of accidents. In a wish to influence more people, we further distributed leaflets about our chinese version results including statistical evidence to those people who previously received questionnaires and about 53% of them expressed surprise to the strong relationship between those factors and the probability of accident rate while 47% said that was within expectation. Also, we presented our whole result to the staffs in our community and gave them our suggestions in improving the local traffic situation.