Factors affecting headway regularity on bus routes

The common phenomenon of uneven headway in bus service is explored based on the automatic vehicle location （AVL） data of Route 2 in Yichun City of Jiangxi province from 6：00 to 9：00 in the morning. The headway regularity of two stages 6： 00--7：00 and 7： 00--9：00 is comparatively analyzed, and it is found that both the traffic conditions and the passenger demand affect headway regularity. A bus arrival model, which assumes that the dwell time of a bus is linear in headway, is built to probe the effect of scheduled headway, and the model is simulated by Matlab. The simulation results reveal that the departure intervals and fluctuations affect headway regularity. Longer intervals and less fluctuation mean higher regularity of headway. And, the fluctuation has a more obvious influence on headway regularity than the interval. Controlling the fluctuations of scheduled headway can effectively raise the regularity of headway and improve the level of public transport service.

An On-Line Scheduler over Hard Real-Time Communication System

By thorough research on the prominent periodic and aperiodic scheduling algorithms,anon-line hard real-time scheduler is presented,which is applicable to the scheduling of packets over a link.This scheduler,based on both Rate Monotonic,pinwheel scheduling algorithm Sr and Polling Serverscheduling algorithms,can rapidly judge the schedulability and then automatically generate a bus tablefor the scheduling algorithm to schedule the packets as the periodic packets.The implementation of thescheduler is simple and easy to use,and it is effective for the utilization of bus link.The orderly executionof the bus table can not only guarantee the performance of the hard real time but also avoid the blockageand interruption of the message transmission.So the scheduler perfectly meets the demand of hard real-time communication system on the field bus domain.

Optimal Combinations and Variable Departure Intervals for Micro Bus System

It is becoming increasingly difficult for Chinese citizens to access traditional public transport because of overcrowded community structures. Therefore, novel ideas are required to improve the transport system. In this respect, this study considers the design of a public transport scheduling model for a micro system. The model aims to minimize passenger waiting time and maximize number of passengers one bus carries, by simultaneously optimizing departure intervals and use of traditional and rapid buses. The model is superior to traditional models, as it analyzes the phenomena of vehicle overtaking, vehicle capacity limit, and passenger determination uncertainty. In addition, the model is a sophisticated nonlinear multi-objective optimization problem and contains more than one type of decision variable, therefore two composite algorithms, HPSO and GAPSO, are proposed, which are improvements of the Genetic Algorithm （GA） and Particle Swarm Optimization （PSO）. These two algorithms are compared to the classical GA with respect to stability and effect, and the results show them to be strong in both respects. In addition, the simultaneous optimization method has evident advantages compared to single-method optimizations.

Bus Scheduling Using a Skip-Stop Strategy Based on Stop Relevance

This research aims to propose an efficient and economic operation mode for bus scheduling optimization by combining with the skip-stop buses and all-stop buses.The skip-stop tactics in bus operation provide service of high efficiency,good punctuality and high speed for long distance commuters,which attracts wide scholarly attention.This paper establishes a model to quantitatively evaluate the relevance between stops,and then develops a new optimization method of skip-stop tactics using the data sets of IC card and bus GPS trajectory.A collaborating scheduling optimization model considering the support and confidence among the stops is proposed to precisely suit passengers’demands and improve bus service.The optimization objective is to reduce the passengers’total travel time,the number of vehicles in use,and operation energy for both the user’s and the operator’s benefits.This methodology is developed for a single-directional route using a multi-decision choice model with genetic algorithm applied to attain efficient solutions.A case study of Qingdao,which is assessed in this new model,shows a reduction of 18.31%in total passenger travel time and 17.65%in the operational inputs as compared with solutions that do not consider the skip-stop tactics.