Distribution Physiognomies Of Urban Public Bike Rental Interval


Public bike rental duration follows a specific model and order of distribution characteristics. The individual journey data for all weekdays is required for this. This helps in understanding the distribution curves for the rental duration of public bikes by the bike rental companies in the city. In most cases when different cities are considered this distribution trend is found to be more or less similar in the weekdays barring a few very minute differences.

The basic parameters used to determine the average of such rental durations include the maximum rental frequency; corresponding duration and the rental duration equivalent to 75% degree. On this basis, the theoretical model of the relation between rental duration and frequency is calculated using the radioactive decay law of physics.

The Process Followed

All data received on public bike rental frequency and its duration is used for testing the model. This resulted in a more accurate and rectified theoretical model. The results of such testing indicated towards the relationship between rental frequency and duration and proved that it obeyed the radioactive decay law.

In addition to that, the studies provided enough support to the theoretical model and also to the bike rental service providers planning to start a bike sharing system. It also helped in the allocation, dispatch and operation of the public bikes.

Comparison Between Private And Public Bikes

When public bikes are compared with the private bikes, there are a few noticeable factors discovered:

  • Public bikes are well received by people as they know that there is nothing to fear about theft of their bikes.
  • Another factor is that people do not have to worry about parking space and look for it as there are designated parking spaces for such bike by the company itself.
  • In addition to that, people using public bikes do not have to worry about repairing these bikes themselves saving them money and the time spent on repairing or searching for a repairing shop.
  • Apart from that governments have also taken to this idea of bike sharing system and strongly advocate central park bike rental to ease congestion on urban traffic.

Over the years, the bike rental system has developed and evolved rapidly with more and more cities all over the world adopting this system. There are several such rental stations not only within the metropolis and large cities, but several medium-sized cities have also taken up to this mode of transport. This newly constructed system operates stably and has resulted in an overall benefit to the commuters as well as to the bike rental companies.

Factors To Consider

Just like any business bike rental is also not devoid of issues if you do not take care of the contributing factors in its initial stages. These factors include station placement, bike allocation, stand allocation and lack of pertinent basic theory.

All these factors can be quickly dealt with and resolved with the rental duration studies which are ideally the time spent by the user on a specific bike from the departure to the destination station. The model also reveals the spatial and temporal cycling distance between the two points. Through this theoretical modeling along with the actual data testing the company can come to various facts that include:

  • Distribution characteristics and rental duration
  • Frequencies of diverse rental length
  • Preference of the riders with respect to the cycling time and distance
  • The general purpose and desire for cycling.

It also helps the central park bike rental company to predict the demand for public bikes, plan the stations, and allocate precise stands at these stations. It also holds theoretical and practical significance in the entire business practice, operation and management of bikes.

Studied From Diverse Perspectives

Different perspectives and angles are followed for the studies on the distribution physiognomies of bike rental period and each time has produced notable results. For example, when the rental duration of transfer between subways is concerned, it is found to be discrete and short as compared with those bikes for other types of stations.
The rider’s card and questionnaires are used to study such differences in distribution features of rental duration. Other operation data used are the average distance traveled and average travel time.

Travel distance is the major factor that influences the choice of people for a public bike for commuting. Based on these factors the companies have developed a general methodology to categorize bike environments. This is done according to the perceived level of comfort and safety of the riders. The second-by-second speed and acceleration data are also collected using Global Positioning Systems or GPS on the bikes. All this information helps in setting useful features to characterize bike environment and impact.

Use Of Physical Models

Use of physical models in traffic systems such as the principle of a maximum of entropy and gravity model is extensive. However, these models and principle are less frequently used for physical modeling of bike sharing systems.

The physical models provide the basic features of bike occupancy at the rental stations. Therefore, there is a need for modeling and analyzing the public bike environment in a comparatively closed system.

Until recent times modeling the bike sharing system was primarily mathematical. The radioactive decay law was used later for such physical modeling. The demand prediction model for such bikes is now done on a multinomial logit model such as the discrete choice model that is based on extensive survey and fieldwork.

The Socio-Demographic Factors

All facts and findings of the physical model point towards the socio-demographic factors. These factors influence the shift from public bike to private bike and vice versa. The other factors that affect such a shift are level of education, a resident of the city and being more progressive ideologically.

In view of the recent influx in the bike distribution and its rise in demand, the characteristics, bike rental duration, physical model based and actual data acquisition play a significant role. The results obtained provide a theoretical basis for the planning and operation of a bike sharing system.


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