Optimization Of Departure Interval And Speed For Single Bus Line

In recent years,urban traffic congestion and pressure are getting worse and worse because of the fast increase of vehicles in China.It has become a serious problem which affects citizens’ living quality and work efficiency.The urban public transport has the advantages of larger passenger capacity,lower fuel consumption,energy conservation and environmental protection,etc.Developing the public transportation and transportation priority policy would be an effective way to alleviate traffic congestion in China.However,under the current bus scheduling system in our country,the daily bus schedules are issued by a fixed timetable with equal intervals.The inflexible scheduling strategy not only has low efficiency,but also makes problems,such as bus bunching problem,etc.It is necessary to propose some more effective bus scheduling strategies to improve the public transport service quality and passengers’ travel experience,and to attract more citizens choosing bus for travelling.In addition,with the development of Internet of Things,a lot of real-time information could be monitored and collected in time,using mass real-time information to achieve effective real-time scheduling has become a new highlighted problem of the dynamic scheduling research.Based on this background,the research of bus optimization of departure interval and speed for single line has been conducted in this thesis,and the main work includes the following aspects:First,an urban bus scheduling model for single line is established.The objective of this model is to minimize the total passenger waiting time.The decision variables are interval and inter-station speed.It means to adjust the both decision variables within the allowable ranges.A genetic algorithm is designed to solve the optimization model.In order to test the performance of model and algorithm,some simulation experiments are designed under different passenger flow distributions.Then the optimization results are presented.Second,an bus scheduling model considering traffic lights and road information is proposed.The influence caused by the intersection signal lights on the delay of bus driving is considered in the model.After deducing the passengers’ delayed time on bus,we add the delayed time into the objective function.Then we give the classification of weather conditions and traffic congestion conditions which could affect buses’ speed.According to an actual bus route in Shenyang and the measured passenger flow,several simulation experiments are designed to study the speed restriction of weather and road congestion.The results of the experiments shows that the model and algorithm could not only reduce passenger waiting time but also solve the bus bunching problem.Third,a dynamic scheduling model for single line based on multi-period is presented and formulated based on real-time information under the IOT environment.By using the collected relevant real-time information,the model and algorithm could dynamically adjust and optimize bus departure interval and speed.Decision-making library is introduced to improve the convergence speed of the algorithm.Through typical cases to study the optimization effect of model,the results shows that the model and algorithms can keep adjusting when the road conditions change anytime.