Research On Modelling And Simulating Carsharing Travel

The sharing economy,mobile Internet and smart phones are accelerating the change in urban mobility.A new type of car travel service,carsharing,is developing rapidly in China.Carsharing service is priced in minutes or hours,and provides users with economical,convenient and high-quality car travel services through self-service vehicle booking,pick-up and return,and payment.However,in recent years,the development of carsharing in China has encountered serious setbacks.A large number of carsharing operators have closed down or transformed,and the policy support for carsharing has also been reduced.The reason is that,(1)the carsharing operators are still unclear about the motives and behavioral mechanisms of users in choosing carsharing during their travels,and(2)the government is still unclear about the longterm benefits of carsharing in improving the transport structure and reducing vehicle ownership.This has led to a vicious cycle of "poor operational performance-low social benefits".Therefore,based on the analysis of carsharing users and travel characteristics,this thesis focuses on modelling and simulating short-term carsharing travel behavior,and modelling the impacts of carsharing on long-term car owning behavior,with a view to providing quantitative analysis methods for improving carsharing operational performance and evaluating its social benefits.The main results include:(1)The small sample data of carsharing user survey and the large sample data of operational orders are nested and correlated,combined with the built environment data and the quantitative calculation of the map service application program interface,to comprehensively portray the user and travel characteristics of the new travel mode,carsharing.The research obtains the basic socio-economic attributes of carsharing users,and focuses on the profile analysis of users who use carsharing for commuting.The characteristics of carsharing travel and usage scenarios are given,and the substitution ways of carsharing to other modes such as metro and bus are analyzed,and an evaluation method of coordination between carsharing and other modes is established based on analyzing the substitution effects.(2)Based on the framework of UTAUT(Unified Theory of Acceptance and Use of Technology),a method for selecting factors influencing the carsharing travel mode choice behavior is established.On the basis of the traditional utility function based on travel time and travel cost,variables such as travel process complexity,travel comfort and importance of people who travel with you are introduced to expand the utility function.A hybrid choice model incorporating a discrete choice model and a structural equation model is developed to estimate the influence of individual socio-economic attributes,travel scenario attributes,travel mode attributes and individual attitude latent variables on the carsharing mode choice behavior.The differences in the effects of the hybrid choice model considering carsharing travel characteristics and individual attitudes are compared with traditional discrete choice models based on travel time and travel cost.It reveals the importance of carsharing travel characteristics variables and latent variables in modelling carsharing mode choice behavior,and also validates the rationality of UTAUT-based variable selection method.(3)Based on the multi-agent open-source simulation platform MATSim(MultiAgent Transport Simulation),the utility function in the simulation platform is modified using the results of carsharing short-term travel behavior model,adding important factors such as travel process complexity and travel comfort to achieve the unity of theoretical model and simulation.Meanwhile,considering the specific carsharing operating rules in China and the status that most of the carsharing vehicles are pure electric vehicles,a carsharing travel process module(including the simulation of electric vehicles and the adjustment and optimization of the return process and access/egress modes)is further developed to meet the localized carsharing operating requirements.The developed modules are implemented in MATSim through JAVA language.The developed carsharing module not only has the advantage of advanced activity-based,individual-level,dynamic optimization and interactive influence of agents,but also can calculate the extended carsharing travel utilities and simulate the localized electric carsharing travel process.It provides strong support for the subsequent evaluation of the supply and demand relationship of carsharing.(4)Based on mobile phone data,network data and public transit schedule data,a mega-city carsharing simulation environment is successfully built by taking Shanghai as an example.The simulation environment is validated by comparing it with the actual travel mode split,road traffic volume and carsharing operation data.Combined with the developed carsharing utility module and localized travel process module,the impact of different carsharing rates,electric vehicle range expansion,charging rate increase and battery swap on the carsharing demand are simulated.(5)The idea of disentangling the long-term superimposed impact of carsharing on car owning behavior is proposed,including stock and incremental impacts,current impact and future potential.Using a combination of retrospective questionnaire design and prospective hypothesis research,a survey design method for the impact of carsharing on car owning behavior is established.Combined with the Shanghai case study,the long-term impact of carsharing on selling vehicles,giving up purchase,and delaying purchase in China is analyzed.A car owning behavior model is developed and key factors are identified.A correlation analysis between the short-term carsharing travel mode choice behavior and long-term car owning behavior is conducted.Based on international comparisons,the differences in the extent of influence and factors of carsharing on long-term car owning behavior in different cities and transport development levels are revealed.