This paper explores car drivers’ cruising behaviour and location choice for curb parking in areas with insufficient parking space based on a survey of car drivers in Beijing, China. Preliminary analysis of the data show that car drivers’ cruising behaviour is closely related to their parking duration and parking location. A multinomial probit (MNP) model is used to analyse cruising behaviour and the results show that the closer to the destination car drivers are, the more likely they choose to park on the curb. The adjacent locations are the basis of car drivers’ sequential parking decisions at different locations. The research results provide a better understanding of cruising behaviour for parking and recommendations for reducing cruising for parking. The provision of parking information can help regulate the parking demand distribution.

The rapid increase in the number of cars has caused many problems, such as “cruising for parking” and “illegal parking”. In this study, we conducted several on-street parking surveys in Beijing’s business districts. A parking location choice model and decision rules for the cruising process are established. A multi-agent based on-street parking simulation was constructed to explore the effects of time-varying parking prices on parking demand. It is concluded that demand-driven dynamic parking pricing can effectively regulate the distribution of parking demand and ensure the utilization of parking facilities within the desirable range in business districts. A lower desirable range and higher price change for the price adjustment can cause larger fluctuations in parking demand, fewer time intervals within the desirable range, and more price adjustment times. A higher desirable range and higher price change can result in longer cruising and driving times, and lower driving speeds. Considering the effectiveness and operating costs of the pricing schemes, it is recommended that the suitable range for parking occupancy rate is 60%–80% and the price change is 2 Yuan/h. The price adjustment threshold can be set based on the scale of the regional road network. The proposed dynamic parking pricing strategy can balance the distribution of the parking demand and reduce parking and traffic problems. The research conclusions can also provide a reference for the formulation of dynamic parking pricing strategies.

Introducing private capital into the public transport system for its sustainable development has been increasing around the world. However, previous research ignores emissions and energy consumption impacts, which are important for private capital investment policy-making. To address this problem, the system dynamic (SD) approach was used to quantitatively analyze the cumulative effects of different private capital investment models in public transport from the environmental perspective. The SD model validity was verified in the case study of Jinan public traffic. Simulation results show that the fuel consumption and emission reductions are obvious when the private capital considering passenger value invests in public transport compared with the no private capital investment and traditional investment models. There are obvious cumulative reductions for fuel consumption, CO₂, CO, SO₂, and PM10 emissions for 100 months compared with no private capital investment. This research verifies the superiority of the passenger value investment model in public transport from the environmental point of view, and supplies a theoretical tool for administrators to evaluate the private capital investment effects systematically.

In order to understand the mode shift behavior of car travelers and relieve traffic congestion, a Stated Preference survey has been conducted in the city of Ji'nan in China to analyze bus choice behavior and the heterogeneity of car travelers. Several discrete choice models, including multinomial logit, mixed logit and latent class model (LCM) are developed based on these survey data. A comparative analysis indicates that the LCM has the highest precision and is more suitable to analyze the heterogeneity of car travelers. The LCM divides car travelers into three classes. Different classes have different sets of influencing factors in the model. Policy recommendations are also proposed for those classes to promote bus shift from car travelers based on the model results. Finally, sensitivity analysis on parking fees and fuel cost is carried out on the LCMs under different bus service levels. Car travelers have different sensitivities to the influencing factors. The conclusions indicate that the LCM can reflect the heterogeneity and preferences of car travelers and can be used to understand how to shift the behavior of car travelers and make more effective traffic policy.

As a multimodal travel behavior, park and ride includes several trip modes such as car, walking, bus, or railway. And people’s choice of park and ride is influenced by many factors. This paper, based on the park and ride behavior survey in Beijing, will analyze the relationship between the perception of the influencing factors and the behavior intent for park and ride by using structural equation modeling. The conclusions suggest that the park and ride choice for travelers is a passive behavior which means giving up driving the car is mainly caused by the serious traffic congestion. Furthermore, improving the service level of the park and ride facilities and the comfort for riding bus or railway will increase the utilization of park and ride facilities. The perceptions of the influencing factors have both direct and indirect effects on the travel intent for park and ride by the interaction among the influencing factors.