To enhance the resilience of urban rail transit networks in dealing with interference events and facilitating rapid network recovery, this paper focuses on studying damaged urban rail transit networks and proposes comprehensive resilience evaluation indexes for urban rail transit networks that take into account two dimensions: network topology and passenger travel path selection. A bi-level programming model is constructed to maximize the comprehensive toughness, where the upper-level model is an integer planning model for determining the optimal recovery sequence of the affected stations under interference events that result in station closure or inoperability. The lower-level model is a passenger flow allocation model aiming to minimize travelers’ impedance. A genetic algorithm and Dijkstra’s labeling algorithm are used to solve the upper model as well as the shortest path of the lower model, respectively. Using a real-world urban rail transit network as an example, this research applies different recovery strategies, random recovery, node importance-based recovery, and comprehensive toughness-based recovery, across five common interference scenarios to analyze the recovery sequence of stations in each scenario. The modeling results show that the comprehensive toughness-based restoration strategy yields the most favorable results for the rail transportation network, followed by the node importance-based restoration strategy. In addition, the network’s toughness varies more significantly when employing different restoration strategies during target interference, as compared to the random and range interference scenarios.

The exit-lanes for a left-turn (EFL) is an unconventional method of organizing traffic for left-turns at signalized intersections. In this paper, we propose a nonlinear optimization model to minimize delay by establishing a delay-time diagram for the left-turn traffic when the left-turn traffic is non-oversaturated, considering the relationship between the pre-signal start node of the exit-lanes for a left-turn and the queuing dissipation time of left-turn vehicles. Model validation is performed with example calculations to compare and analyze each operating index and fleet type after signal timing optimization of intersection lane borrowing left-turn lanes. The results show that compared with the conventional left-turn lane, the average delay of vehicles operating with the model decreased by 15.7%, exhaust emission decreased by 11.4%, and capacity increased by 65.7%. The model can support EFL pre-signal design, where signal control is related to queue dissipation time. In practice, a well-designed pre-signal control scheme based on traffic volume can improve capacity and reduce emissions while minimizing average vehicle delays.

Reservation parking is a new type of parking that allows users to obtain a parking space for an appropriate time slot by reservation. This paper pioneers a high degree-of-freedom reservation strategy and rules for commercial districts in which users can arbitrarily select parking time slots. The nested logit is applied to build a parking revenue model by analyzing the cost, demand, and price factors sequentially according to the user’s choice behavior. The parking lot price game in the region is dissected and a nonlinear pricing model is proposed for maximizing regional returns. A model validation of a parking lot in an actual commercial area shows that compared to the traditional parking method, the parking lot revenue increased by 69.63% upon the application of this reservation strategy and pricing scheme, while the parking lot traffic increased by 22.4%. This model can provide strong support for reservation parking pricing in commercial areas. In the comparison of scenarios, the scientific validity of this model using dynamic pricing and regional game competition is verified. In the application, a reasonable price scheme can be formulated based on the parking lot traffic, cost, and surrounding parking strategies, which can result in higher parking revenue while providing users with great parking convenience.