The rapid development of urban rail transit system leads to the rising land rent and housing rent along the rail transit line. In order to respond to housing demand for low-income households, the public rental housing policy came into being. Public rental housing, with the advantage of lower rent than commercial housing, has become the primary choice for low-income households. However, the preset location of public rental housing is usually in the suburbs, separating the workplace and residence, which increases in travel cost. Consequently, it is particularly necessary to study the effect of public rental housing on the utilities of heterogeneous households from the perspective of transportation, and an equilibrium model of housing choice for heterogeneous households under public rental housing policy has been suggested in this paper. The result shows that the change in average operating speed of the rail may lead to the difference in urban residential formation and the increased speed of the rail may not be able to eliminate the location disadvantage of public rental housing. Furthermore, we find that ultra-limit public rental housing with the remote location is detrimental for low-income households. The model explicitly considers the interaction among the government, property developers, and heterogeneous households in the housing market, and can be utilized as an instruction for the future sustainable development of public rental housing.

The continuous increase in the number of private cars has caused an imbalance in the travel of cars and buses. This phenomenon has become a bottleneck restricting urban transportation economy and sustainable development. This paper examines the effectiveness of policy options in motivating travelers to choose buses instead of cars. Using of reference dependence describes mode choice behaviors with two attributes under different public transit policies in uncertain conditions. At the same time, we also consider using the bus fare concession strategy to guide the traveler to reasonably choose the bus travel, and establish a bi-level programming model to optimize the bus fare proportions. Among them, the lower-level planning considers the two attributes impact of traffic policy on travelers' decision to bus travel. Using the upperlevel planning, the optimal fare preferential proportion for different policy decisions is decided considering the lowest total system cost. The study highlights that the transit subsidy policy can be employed to guide travelers to choose bus travel preferentially. Model effectiveness is verified using numerical examples. The model is indispensable for the implementation of future traffic demand management strategies.

Abstract.Cruising for parking is a main contributor to traffic jam while the related researches are few. Assume travelers are well-informed, this paper first analyses user equilibrium (UE) in no parking fee scheme with different scarcity of parking spaces. We get a conclusion that information fails to solve traffic problems effectively in absent of control. Followed by the principle of cape and trade, the paper proposes parking reservation scheme which combining guidance (information) with tolling (control). Example shows that system cost reduces significantly after the implementation of the parking reservation scheme.

The operating system is a complex system that includes supply and demand. Changes in external information have an impact on the operation of the system, especially on both supply and demand. This paper analyzes the supply and demand and establishes the nonlinear programming problem of system operation under the social optimal goal. With the increase of external information intervention, there will be more suitable travel fares for the demand side. However, the supply side’s related operating indicators (for example, frequency, bus fleet, and vehicle capacity, etc.) have shown a trend of first increasing and then decreasing due to existing resource constraints. It can be seen that under the same information interference, there are differences in the law of change between the supply and demand sides. Besides, an example is used to verify the effectiveness of the model. Through the model and calculation examples, we can know that the supplier and the demander can meet their own needs under the social optimal goal. This provides certain theoretical support for future research information on system operation.