Study On Optimization Settings Of Multiple Bus Stop

As a basic element of city conventional public traffic system, bus stop is one important component of the public transportation, providing a place where buses set down and pick up passengers. The optimization design of the bus stop produces an effect not only on the efficiency and service quality of the public transportation, but also on road traffic and the quantity of the city environment. This paper studied on bus stop setting from the number of berths and parking capacity for routes of bus stop, for solving the problem that some bus stops congest seriously in rush hour.Firstly, it investigated on buses’arrival and the dwell time at the bus stop. With the data of investigation, the distribution type of the test data was determined by fitting test. The results showed that buses’arrival followed Poisson distribution and their dwell time at the bus stop subjected to Erlang distribution. Meanwhile, effective factors of them and the relationship between traffic capacity of the bus stop and these effective factors were analyzed. It also carried out the comparison among three typical traffic capacity calculation models.Secondly, it determined the calculation method of the number of berths and routes of bus stop. Taking two bus stops for example separately, one with one berth and another with two berths, this paper analyzed these different bus stops and concluded the calculation formula of the maximum of routes of a bus stop based on Queue theory. On condition that the number of buses at bus stop queuing system was less than that of effective berth, and the probability of buses queuing was within an acceptable range, it got the optimal number of berth with the method of trying calculating, which provided references for bus stop optimization.Finally, combining with the survey data of the target bus stop, this paper calculated the optimal numbers of berth and routes of bus stop with the methods proposed above. And, judged the existing numbers of berth and routes of bus stop were reasonable or not, and optimized this bus stop by increasing the number of berth and changing the form of the platform. Then, comparing the traffic capacity and the probability of buses queuing before the optimization with that after the optimization, put forward a optimal proposal to optimize this hus stop.