Study On The Activity-Based Travel Demand Model And The Effect Of Information

Booting national economy and application of information technology (IT) have become an important strategic move for China's modernization by the IT revolution. The individual's activity decision process are affected by the rapid development of IT. The conventional method have focus on the physical movement of people and goods, neglecting the effects of information delivery on the transmission. In the context of increasingly severe traffic congestion, researching the activity-based travel demand analysis approach and method for the effect of IT on individual's travel behaviour is of great significance.Information-affected travel behavior is characterized by complexity , randomicity, dynamics and reliant on attributes of individual. Micro-simulation attempts to replicate the individual behavior from a specific probability distribution, and is appropriate for our research. The purpose of the dissertation is to develop the activity-based micro-simulation model combining the trip survey data, and propose a modifying method to study the effects of information on travel demand.This dissertation established a travel demand framework with provided information, focusing on the activity-based travel behavior micro-simulation method and the modification approach for forecasting the travel demand affected by information. The activity and travel behaviour are depicted with"activity-travel"pattern and a model was established to simulate the activity characteristics with time step using the Monte Carlo method. The simulation program for activity-travel pattern includes six stages: Firstly, grouping all the individuals on age and employment status and classifying the individual activity-travel patterns as a number of representative patterns using the clustering methodology; Secondly, establishing the relationship between the identified representative patterns and individual socio-economic characteristics; Thirdly, estimating the representative patterns'choice probability distribution; Fourthly, given representative patterns specifying the conditional probability distribution of attributes for activity and travel behavior; Fifthly, simulating the individual activity and travel behavior; Sixthly, validating the simulated patterns.Considering the difference between the activity-based approach and trip-based method in research object, this dissertation expounds the trip data checking and the rules of validity judgement; With trip survey data of Sheng-Yang city in 2004, the character of initial activity-travel patterns are analized and a travel demand prediction method based on cross classification was put forward. And then, a micro-simulation flow for activity and travel behaviour was developed, studies the simulation model structure, proposes a validation method, programs to implement the simulation flow; applies the proposed model to the activity and travel analysis of Shen-Yang city; compares the simulation outcomes with actual patterns, results shows that the simulation errors is small. The proposed model has been proved to be correct and rational, and could be applied to the research of travel behavior provided information.The dissertation offered a modifying method for travel demand with provided information—incremental analysis. The approach simulates individual behaviour responses with provided information and modifies the initial patterns based upon the response in order to make it reasonable and satisfy time-space constraint condition. The modifyed approach could be used to forecast the travel demand with provided information and has significance for urban traffic demand.