| In recent years,the rapid development of new technologies such as artificial intelligence,big data,and 5G has provided travelers with all-round travel information in real time and quickly.It has been proven that the Advanced Traffic Information System(ATIS)can help travelers formulate reasonable and efficient activity-trip plans,and it has also increased dramatically for travelers' demand for travel information.Most of the existing related researches focus on the impact of a single information on a single decision,as well as the research on information usage behavior based on traditional discrete selection model.However,in the real activity-trip process,the traveler's choice and use of travel information is characterized by selecting multiple travel information at the same time.In addition,when the traveler decides the "multiple discrete" choice of information,it usually determines the continuous dimension of the information,that is,the frequency of use of the travel information,which has been marked as "Multiple Discrete Continuous"(MDC)selection.Therefore,it is necessary to fully consider the individual heterogeneity of the traveler,and quantitatively analyze the number of travelers' choice of travel information,as well as the frequency of use of information in travel,in this way,can deeply study the traveler's behavior of use of activity-trip information.Based on the traditional ATIS,this paper combines the emerging intelligent travel modes,adopts the technology of SP and RP fusion and D-efficient efficiency test design method,determines the influencing factors of travel information selection behavior and seven different travel chains,and generates travel Questionnaire on the use of activity-travel information.Then,use the pre-survey and formal survey to obtain valid sample data.In the end,this paper uses R language to program and construct the Multiple Discrete-Continuous Extreme Value(MDCEV)model,which takes the individual socio-economic attributes of Chengdu residents,the number of travel information selected,and the frequency of information use as input,which takes the traveler's multiple discrete selection probability for information and the probability of continuous use of information as the output,this more fully explains the behavior of the travelers on the use of activity-trip information in the model results.The results show that individual heterogeneity attributes such as personal socioeconomic attributes,information use characteristics,travel-related attributes,etc.have a significant impact on the number of information choices and frequency of use.As for the choice of travel information: in a simple travel chain,relative to the location information of the destination,the traveler needs more real-time traffic information,and the demand for life service information near the destination is lower.In a medium-complex travel chain,relative to destination location information,travelers need bus/metro route information and parking spot information near the destination.Drivers will also increase the demand for parking spotinformation near the destination.In addition,in the seven travel scenarios,the calibration result of "No Need" is significant and the parameter sign is negative,indicating that travelers have a high demand for travel information in travel chains of any complexity.For the number of information needs,in the simple travel chain,most travelers need 2-4information,in the medium complex travel chain,most travelers need information 3-5 In the complex travel chain,the demand for information can be as high as 7.It shows that the more complicated the travel situation,the higher the traveler's demand and dependence on information,and the travel information needs to be used to ensure their efficient travel.In terms of information usage frequency,in simple travel chains,travelers use information within 1 time,and in medium-complex travel chains and complex travel chains,they do not use information more than 2 times. |
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