Travel survey and behavior modeling still take obviously important roles in a series of transportation planning, including problem identification, problem structuring, travel demand analysis, project/policy formulation, and project/policy evaluation. Classical large-scale travel surveys (e.g. paper-based questionnaire), which have been applied in many cities in the world, have faced challenging problems such as increased survey costs, decline in quality or reliability of the results, and less continuity. The scope of transportation planning at present has become more diverse and it would cover a variety of subjects including demand management, environment, health, gender, and evacuation. Moreover, there have been dramatic expansions in travel data collection with the rapid spread of information communication technology. These issues have motivated me to set up this special issue.
This special issue has welcomed papers that are related to all aspects of innovation in travel survey methods and corresponding travel behavior modeling that show innovations in approach, outcomes, and state-of-practice. Five papers have been selected for this special issue.
The activity-based model (ABM) has been employed to forecast travel demand forecasting. However, this approach has significant shortcomings: the controversy over its alternative specific constant (ASC)'s temporal stability. To enhance such stability, various studies have tested different methods to update ASC. In this study, we propose another method of such an update that applies big data to the ABM-based simulation. This is to assimilate activity simulation to mobile spatial statistics (MSS), an estimated population data recorded by the of mobile phone connection. Because MSS can be estimated longitudinally, we can see the temporal variation of the ASC. In the empirical test, we reduced at least by 25% the distance between the number of people staying in the zone by the ABM simulation and the number of people staying in the zone of MSS.
Recent developments in the field of sensor technology have been transforming the ways in which the traffic surveys are undertaken. This study aims to determine the behavior of a person walking to and from their school using data acquired by an acceleration sensor/gyroscope incorporated into the JINS MEME eyeglass-type device. The two main results of the study were as follows: 1) We devised a method for determining the walking behavior using eye- glass-type device equipped with sensors., 2) We developed a walking behavior discrimination model with a high discrimination ability, exhibiting an overall accuracy of 0.994 and an average accuracy of 0.914 for the validation data.
I conducted functional magnetic resonance imaging (fMRI) experiments to examine the relationship between moral consciousness and travel behavior by monitoring the activation of the participant's brain areas in a situation where questions in relation to moral consciousness were indicated. I successfully extracted the brain areas in relation to “sympathy” or “memory,” which were more activated during a social dilemma than a general situation, such as baseline questions when legal bicycle parkers with higher moral consciousness answered them. According to the individual analysis, I found that the dorsolateral prefrontal cortex activation was more common for legal than illegal parkers. I also conducted an analysis on the response time difference between legal and illegal parkers. The response time for a legal parker is longer than that for an illegal parker with 5% statistical significance, which is assumed to reflect the activation of more brain areas before answering questions.
This study aims to investigate important factors affecting intention for ceasing driving in the local city in Japan. 321 elder driver data collected in Toyota City are used for empirical analysis. One trivariate ordered probit model is used to measure anxiety about driving, the intention for continuing driving and that for surrendering driving licenses in one framework. The Gibbs Sampler algorithm is applied to estimate the unknown parameters. The major findings indicate: 1) elder drivers more than 74 years old are willing to return their driving licenses compared to elder drivers between 69 and 74 years old; 2) elder drivers liking to drive are unwilling to cease driving compared to other drivers; 3) there is a synergetic effect between anxiety about driving with intention for surrendering driving licenses; and 4) there is a complementary effect between intention for continuing driving and that for returning driving licenses as we expected.
In this paper, the critical factors affecting a successful cooperative travel survey system for urban public transit are analyzed by means of a case study of Tokyo, Japan. To this end, both public and private entities participate in developing an integrated travel database. This study reviews the Metropolitan Transport Census, which is a large-scale travel survey in three metropolitan areas of Japan, mainly covering travel supply and demand of urban railway services. This survey has a cooperative framework in which the government, private/public railway companies, and transportation academics/experts jointly design the survey, collect data, and process and analyze the data. The survey database also contributes to the development of a series of policy management processes, including the development of long-term urban railway development masterplans with dynamic interactions between the government and the railway companies. The advantages and disadvantages of participating in the integrated survey for both the government and the private/public railway companies are also examined. The results reveal that a potential reason for the success of the survey system is the win-win situation in which the vision of public transit planning presented by the government is in line with the business strategies of the private railway companies. This alignment of goals is highly reliant on a mechanism of interactive communication among the stakeholders. This is achieved through a cooperative policy management process in which both the government and the railway companies are directly or indirectly governed by third parties, including taxpayers, investors, and customers.
Design and operation strategies for bus lanes during peak hours are examined. The operation of a bus under different lane management and bus stop distance settings is investigated to improve bus travel speed. A simulation model is developed to represent heterogeneous traffic flow for a corridor in Phnom Penh, Cambodia. A traffic simulator, VISSIM, is used, and the parameters are calibrated on the travel times of multiple vehicle types by structural equation modeling. The results suggest that a bus lane exclusively used by buses and motorbikes improves the travel time of buses, cars and motorbikes by 33%, 8% and 6%, respectively.
In 2017, two smartphone-based travel surveys were conducted in two cities in Afghanistan. The surveys were conducted simultaneously in the capital city of Kabul and the non-capital city of Khost. This study investigated the reasons for non-response to the smartphone-based travel survey in association with individual attributes. Additionally, the reason for non-response to the Kabul and Khost surveys were compared. The comparison results revealed that the small reward for participation was the main reason for the non-response of males, while the reason for the non-response of females was mainly related to their privacy concerns, as well as their dependency with regard to decision making. The results also indicated that the non-response rate in the city of Khost was higher than that in the capital city of Kabul.