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For most ultralong bus lines, low punctuality rates and vehicle bunching are two main challenges. One potential strategy to solve these two problems is to split an ultralong line into two or three shorter lines according to historical passenger flow patterns as well as other presetting objectives and constraints. Thus, in this paper, a multiobjective optimization model is first established in consideration of both passenger flow distribution and coline metro networks. Then, the optimal truncated stop is determined by estimating the model results generated by enumerating each potential bus stop derived from related metro stops. The nondominated sorting genetic algorithm II (NSGA-II) is applied to solve the model efficiently. A case study conducted on a real bus line associated with metro networks in Beijing, China, demonstrates the efficiency of the optimization strategy adoption in terms of operating cost and passenger travel time, even with a slight increase in passenger cost. Besides, the multivehicle type is also referred in the experiments to verify economic efficiency to reduce operational costs. [ABSTRACT FROM AUTHOR]

Delays at bus stops have seriously affected the efficiency of bus operation and the improvement of level of services of public transportation and greatly influenced the preferences of passengers to choose bus services. In this paper, the analysis on arriving, dwell and leaving process of buses and the method to calculate bus delays at stops are proposed according to survey data from three bus routes in Beijing. Statistical analysis is then adopted respectively to evaluate average times that buses are docking at curbside and bay-style stops. Moreover, it is noted that different load factors of passengers in buses have significantly influenced the average boarding and alighting time per person. The effectiveness and accuracy of the proposed methods is illustrated through case studies. This study is crucial and helpful for the planners and operators to evaluate the efficiency and level of service of urban public transportation. [ABSTRACT FROM AUTHOR]

Numerous studies have investigated the travel effects of online purchases. However, compared to tangible goods (e.g., books, electronics, and clothes), very limited attention has been paid to online purchases of intangible services (e.g., hairdressing, dining out, and visits to movie theatres, zoos, and local theme parks). Utilizing data obtained from 733 structured interviews in Beijing, China, this paper aims to examine the influence of buying intangible services online on trip frequency. The results indicate that – because of buying intangible services online – 52% of respondents indicated an increase in travel frequency to use these services, while only 7% indicated a decrease in the frequency. More importantly, those who indicate an increase in travel frequency are inclined to travel longer distances to use these services. Therefore, purchasing intangible services online may impose additional pressure on transportation systems. Applying a multinomial logistic regression method, we additionally reveal the influential factors of changes in travel frequency. The results show that – due to buying intangible services online – people with lower accessibility to shopping centers and bus stops are less likely to increase and even more likely to decrease the frequency of travel to use these services. • Purchasing intangible services online makes consumers travel more frequently to use these services. • The built environment plays a role in travel frequency changes caused by buying intangible services online. • Physical retailers for intangible services can benefit from online purchases. • Purchasing intangible services online seems to be a challenge for transportation systems. [ABSTRACT FROM AUTHOR]