| Air pollutants have an impact on residents’ travel health,more significantly on commuters with concentrated travel times and high travel demand.The lack of investigation and analysis of air pollutants may lead to underestimation of the burden of disease caused by air pollutants and inadequate preventive measures for susceptible populations.Particulate matter(PM),as the main pollutant in the air,is one of the main causes of human cardiovascular and respiratory diseases.Under the same air pollution exposure level(comprehensive consideration of the impact of pollutant concentration and exposure duration),commuters’ choice of travel mode and route will have different impacts on their health.Therefore,it is necessary to establish a feasible method system to improve commuter travel health through information guidance based on the analysis of the mechanism of PM on commuter health.With the help of information media such as navigation software,commuters are provided with information services such as traffic congestion status of road network,emergencies and travel guidance,thus inducing commuters to travel can effectively improve commuting efficiency,which has become an effective means for traffic managers to regulate traffic volume.However,the research on commuter decision-making mechanism under the guidance of travel health information is lacking.Therefore,this paper aims to improve the travel health of commuters,combines travel health factors with traffic guidance,and carries out relevant research on the travel decision-making behavior and guidance information service of commuters considering health factors.The main research contents include:Firstly,measured PM concentrations and ECG indicators for commuters were obtained for each mode of travel(walking,bicycle,private car,taxi,bus,subway)based on particulate matter detectors and ECG detectors for the exposed environment.Based on the data collected on PM concentrations in different traffic spaces for each mode,the relationship between PM concentrations in traffic spaces and background environment PM concentrations(PM concentrations detected by environmental monitoring stations),temperature,humidity,wind speed,passenger capacity,traffic flow,the location of environmental monitoring stations is clarified,thus enabling the acquisition of PM concentrations for each mode based on background environment PM concentrations,meteorological conditions and traffic conditions.Secondly,PM inhalation is identified as a measure of commuter travel health,and the travel health risks of commuters are assessed.A PM inhalation model that consider the individual characteristics and exercise load of commuters is developed.The PM inhalation per unit time is calculated based on the amount of heat consumed by the human body during the trip,combine the travel time and PM concentration to obtain the PM inhalation of a complete trip of commuters.Correlation analysis of multiple fractal characteristics of ECG indicators to obtain optimal indicators for detecting health risks.Human inhalation of PM has a lagging and cumulative effect.The method of combining linear mixed effects(LME)and distributed lag nonlinear model(DLNM)is constructed to obtain the relationship between PM inhalation and the cumulative changes of the optimal indicators,and verify that PM inhalation can be used to measure health risks.The ROC curve is applied to obtain health risk thresholds,classify commuting states into healthy and risky states,and build a binary logit model to obtain the specific contribution of each influencing factor to the health impact to assess the probability of health risks arising from different groups of commuters.Thirdly,a traffic guidance strategy that integrates travel time and travel health is proposed.An analysis is conducted on the characteristics of commuter travel guidance problems considering health factors,including commuter travel decision-making behavior under the influence of health factors,weight of health factors,release of health induced information,and state transition rate caused by factor changes.A circular system is constructed for commuter travel data,commuter distribution state perception,air environment state perception,and guidance scheme generation.Three guidance strategies are proposed for different air pollution environmental information,including optimal travel efficiency,optimal travel health,optimal comprehensive travel time and travel health.At the same time,based on the relationship between the release of induced information and the choice behavior of commuters,an interactive feedback mechanism is formed between the release of induced information and the travel choice behavior of commuters.The optimization goal is to maximize the utility of the travel mode/minimize the impedance of the travel path,and the rules for the release of induced information are designed.The implementation process of the guidance strategy scheme is established.Fourthly,a travel decision model that integrates commuting health and commuting time is developed to obtain the results of commuters’ finite rational travel mode and travel route selection under the influence of multiple factors.A commuter travel health value and time value function is established to obtain commuter travel health value and time value,and a travel mode choice model with multiple core variables is established by integrating travel time,travel health and travel cost to obtain the results of commuters’ choice considering health factors in different scenarios.Cumulative prospect theory is applied to simulate the commuter travel route decision process,and a travel route decision model with the addition of health factors is developed to obtain the results of commuter travel route choices under single time,single health and combined time and health.Finally,a dynamically optimized Bi-level Programming Mode is constructed and algorithms are designed to solve it based on the relationship between the overall operational effectiveness of the road network and commuters’ choices.A travel mode guidance model with the upper-level objective of maximum travel utility and the lower-level objective of maximum cumulative prospect value is developed and solved using the bat algorithm.The influence of parameters such as travel time,travel health and individual commuter characteristics on the inducement effect is also analyzed by introducing the concept of ’marginal cost’.A travel route guidance model with the upper-level objective of minimum travel impedance and the lowerlevel objective of maximum cumulative prospect value is established,a road impedance function considering health factors is constructed,and the traffic distribution results of the road network are obtained based on the Frank-Wolfe algorithm of path traffic distribution at the origin and destination points.The concept of "marginal cost" is introduced to analyze the influence of parameters such as travel time and travel health on the traffic flow of the road section,while a simulation model of commuting scenarios based on Agent technology is constructed to describe the influence of information release time,information obedience rate and OD on traffic flow growth rate on the guidance effect according to the established Agent rules.Through case studies,the proportion of travel mode structures and the distribution of road traffic flow with and without guidance information are compared,demonstrating the applicability and effectiveness of the guidance strategy proposed and guidance model established in this paper.In summary,based on the measured PM concentration data of different traffic spaces by travel mode and the real-time ECG data of commuters,the health effects of PM on commuters are explored in depth.Combine health factors with travel guidance to achieve the goal of improving commuter travel health.The results of the study are "personalized" and provide practical solutions to improve the health of commuters,as well as providing theoretical references and technical support to improve the health of commuters in the region. |
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