Curb parking pricing method based on parking choice behavior

In order to improve the use efficiency of curb parking, a reasonable curb parking pricing is evaluated by considering individual parking choice behavior. The parking choice behavior is analyzed from micro-aspects, and the choice behavior utility function is established combining trip time, search time, waiting time, access time and parking fee. By the utility function, a probit-based parking choice behavior model is constructed. On the basis of these, the curb parking pricing model is deduced by considering the constrained conditions, and an incremental assignment algorithm of the model is also designed. Finally, the model is applied to the parking planning of Tongling city. It is pointed out that the average parking time of curb parking decreases 34%, and the average turnover rate increases 67% under the computed parking price system. The results show that the model can optimize the utilization of static traffic facilities.

Pedestrian choice behavior analysis and simulation of vertical walking facilities in transfer station

Considering the interlayer height, luggage, the difference between queuing pedestrians, and walking speed, the pedestrian choice model of vertical walking facilities is established based on a support vector machine. This model is verified with the pedestrian flow data of Changchun light-rail transfer station and Beijing Xizhimen transfer station. Adding the pedestrian choice model of vertical walking facilities into the pedestrian simulation model which is based on cellular automata, the pedestrian choice behavior is simulated. In the simulation, the effects of the dynamic influence factors are analyzed. To reduce the conflicts between pedestrians in opposite directions, the layout of vertical walking facilities is improved. The simulations indicate that the improved layout of vertical walking facilities can improve the efficiency of pedestrians passing.

Research on Online Education Consumer Choice Behavior Path Based on Informatization

The application of information and communications technology(ICT)in the education industry is becoming more and more extensive,and online education realized through ICT is developing in full swing.The influence of ICT on online education consumer's choice behavior is the core issue of online education industry development research.The research on the interactive path and methods of information and online education consumer choice behavior is worth exploring and revealing.This study introduces the word-of-mouth factor as a new research variable under the framework of the Rational Choice Theory model(RCT)and the structural equation method to conduct empirical research and theoretical analysis to verify the validity of the hypothesis and model.The fifthGeneration mobile communication system(5 G)analyses the factors affecting online education consumer behavior choices based on the premise of ICT.Research on the path between ICT and choice behavior provides new ideas for online education consumer choice behavior research and ICT and content and provides a new scenario.This article is a cross-disciplinary research content in theory,and its innovation opens up a new path for the management of ICT research.The research results have innovative significance and value at both the theoretical and practical levels.

Passenger Choice Behavior between Direct and Transit Flights——A Case Study on Passengers Using Hub Airports in the Northeast Asian Region

This study analyzes air passenger route choice behavior for long-haul inter-continental travel. It employs the SP （state preference） technique and logit modeling to investigate the impact of route development via neighboring countries in the region. With the Japanese government pursuing an increase in international routes at Haneda International Airport, and the Chinese government planning to construct Beijing Capital Second International Airport by 2019, the competition among airports to serve as hubs in Northeast Asia will increase significantly. Korean passengers will have a greater number of route choices when traveling to North America or Europe, utilizing not only direct flights from Incheon International Airport but also flights via Tokyo or Beijing area airports including Haneda International Airport, Narita International Airport, Beijing Capital International Airport and Beijing Capital Second International Airport. Accordingly, passengers will choose among the alternatives by considering fares and flight times. As such, it is essential for airports to offer flights with competitive prices for transit passengers to become successful competitive airports in the region. Therefore, it will become more important for market decision makers to strive toward more attractive ticket prices and better route network quality.

Swarm Intelligence Algorithm Inspired by Route Choice Behavior

Travelers＇ route choice behavior, a dynamical learning process based on their own experience, traffic information, and influence of others, is a type of cooperation optimization and a constant day-to-day evolutionary process. Travelers adjust their route choices to choose the best route, minimizing travel time and distance, or maximizing expressway use. Because route choice behavior is based on human beings, the most intelligent animals in the world, this swarm behavior is expected to in- corporate more intelligence. Unlike existing research in route choice behavior, the influence of other travelers is considered for updating route choices on account of the reality, which makes the route choice behavior from individual to swarm. Anew swarm intelligence algorithm inspired by travelers＇ route choice behavior for solving mathematical optimization problems is introduced in this paper. A comparison of the results of experiments with those of the classical global Particle Swarm Optimization （PSO） algorithm demonstrates the efficacy of the Route Choice Behavior Algorithm （RCBA）. The novel algorithm provides a new approach to solving complex problems and new avenues for the study of route choice behavior.

Analyzing Behavior Differences of Occupied and Non-Occupied Taxi Drivers Using Floating Car Data

As the travel purpose of non-occupied taxies is to find new passengers rather than to arrive at the destination, large differences exist in the route choice behavior between the occupied and non-occupied taxies.With the assistance of geographic information system(GIS) and taxi-based floating car data(FCD), this paper investigates the behavior differences between occupied and non-occupied taxi drivers with the same origin and destination. Descriptive statistical indexes from the FCD in Shenzhen, China are explored to identify the route choice characteristics of occupied and non-occupied taxies. Then, a conditional logit model is proposed to model the quantitative relationship between drivers' route choice and the related significant variables. Attributes of the variables related to non-occupied taxies' observed routes are compared with the case of occupied ones. The results indicate that, compared with their counterparts, non-occupied taxi drivers generally pay more attention to choosing arterial roads and avoiding congested segments. Additionally, they are also found less sensitive to fewer traffic lights and shorter travel time. Findings from this research can assist to improve urban road network planning and traffic management.

Diverging effects of subjective prospect values of uncertain time and money

Studies from behavioral economics show that the subjective prospect value of money has diminishing sensitivity to losses/gains,represented by an S-shape,and this has been applied in representing the subjective prospect value of time in many transportation studies such as travel behavior modeling and network equilibrium.In this study,we demonstrate that the prospect value of time has an increasing sensitivity to losses/gains and can be represented by anϨ-shape,which contrasts that of money.We further explain the rationality of this surprising finding based on psychological and behavioral theories and discuss extensive practical implications.The correlations between sensitivities to gains and losses in terms of magnitude are revealed as well to shed light on potential underlying correlated behavioral principles.Substantial loss-aversion features are observed in the empirical analysis,supporting endowment effects.Implications of the findings on decision-making and other areas that utilize time as a key indicator have been discussed.The findings may revolutionize many research areas that utilize time as a key indicator such as transportation engineering.

A dynamic simulation model of passenger flow distribution on schedule-based rail transit networks with train delays

In a schedule-based rail transit system, passenger route choices are affected by train delays, and, consequently, the relevant passenger flow distribution of the network will differ from the normal state. In this paper, a passenger＇s alternative choices, such as selecting another route, waiting, and switching to other transportation modes, and the corresponding influence mechanism are analyzed in detail. Given train time-space diagrams and the time-varying travel demands between the origin and destination （O-D）, a dynamic simulation model of passenger flow distribution on schedule-based transit networks with train delays is proposed. Animation demonstration and statistical indices, including the passenger flow volume of each train and station, can be generated from simulation results. A numerical example is given to illustrate the application of the proposed model. Nu- merical results indicate that, compared with conventional methods, the proposed model performs better for a passenger flow distribution with train delays.