As China’s high-speed rail and civil aviation gradually move from a competitive relationship to a cooperative relationship, air-rail integration services (ARISs) have begun to be promoted, and an increasing number of passengers are choosing the combined travel mode of high-speed rail and aviation. As two long-distance transportation modes are involved, transfer time also affects transfer service satisfaction, and the factors affecting the transfer time of ARIS need to be further clarified. In this study, a stated preference (SP) survey on the transfer reservation time of ARIS passengers was conducted, the perception accuracy of the transfer reservation time was analyzed, and the influencing factors of the transfer reservation time in each link were analyzed by using a multivariate ordered logistic regression model. The results show that the average transfer time of air-rail combined transportation passengers is 102 to 128 min; more than half of passengers’ reservation time is reasonable; and passengers’ genders, educations, occupations, incomes, travel modes, costs, and distances have different degrees of impact on the transfer reservation time. This study holds a certain guiding significance for improving the service quality of air-rail intermodal transportation and improving transfer efficiency and provides a theoretical basis for personalized and customized services for air-rail intermodal passengers.
20 November 2024 in IEEE Transactions on Intelligent Transportation Systems
Due to limited mileage and high schedule constraints, electric buses need to maximize not only energy efficiency but also mobility flexibility, especially in lanes where multiple bus lines merge. Connected-autonomous electric buses (CAEBs) indeed reduce inter-vehicle gaps to minimize the impact of bus stops on road capacity, but lead to frequent acceleration and deceleration to ensure safety. Therefore, this paper regards the CAEBs in the merged lane of bus lines as a whole platoon to study the cooperative control algorithm aiming at the tradeoff between energy saving and mobility. Model predictive control and optimal control are combined to design CAEB control inputs where saturation inputs, safe inter-vehicle spacing constraints, and external disturbances are integrated. This paper finds sufficient conditions for the unique solution of the non-convex optimization objective caused by the higher-order energy terms. In addition, this paper proves the semi-negative characterization of the symmetry matrix of higher-order energy terms to realize the asymptotic stability of CAEB platoons. Comparative simulations show that the cooperative control algorithm effectively trades off mobility and energy consumption even in emergency scenarios, and achieves a 25% reduction in energy consumption with only a 2.2% reduction in mobility.
5 April 2023 in Journal of Advanced Transportation
With the progress of regional integration in China and the growth of passenger travel demand, a single travel mode has been unable to meet passengers’ cross-regional, multimodal, and personalized travel needs. Air-rail integration service (ARIS) is gradually catching on with travellers. Compared with developed countries, ARIS remains in its infancy in China, with a low penetration rate. Against this backdrop, this study presents an SP survey of ARIS passengers at Shijiazhuang Zhengding International Airport as an example and analyses the factors affecting their transfer process using multiple ordinal logistic regression. The satisfaction analysis results help to construct a simulation model of ARIS of Shijiazhuang Zhengding International Airport by using AnyLogic to verify the optimization effect. The research results show a significant impact on the ARIS transfer process by gender, education, occupation, travel mode, travel cost, location of the shuttle bus, arrival frequency of shuttle bus, manual baggage check-in service, self-service check-in, and the performance of security check equipment. The adoption of optimization measures will reduce ARIS shuttle bus, baggage check-in, and security check-in times by 68%, 50%, and 45%, respectively.