Study on Accessibility of Feeder Lines with Different Geometric Shapes

The performance of the urban rail transit system depends largely on the operation efficiency of its feeder system. An improved way is proposed in this paper to calculate the accessibility index which is used for evaluation of feeder lines, and both passengers’ waiting time and the competition between different access modes are considered. Different from previous research, this paper focuses on whether and how the geometric shape differences affect the performance of fixed-route feeder lines. The impacts of line shape on accessibility are analysed by derived formulas for calculating accessibility under ideal conditions. The finding emerging from this study is that the accessibility of feeder lines differs obviously due to their shapes, given the same conditions of total line length, stop spacing, and vehicle fleet size. The service area of feeder lines with branches or a loop is closer to the rail station compared with that of linear lines, thus leading to fewer passengers served but shorter average travel time under specific routing plans. For further exploring the universality of the above finding, route alignment optimization models to maximize accessibility are built for different shaped lines. The optimal solutions of different shapes are obtained and compared in the cases of random generation to analyse the impacts of shapes on accessibility under different line length conditions.

OPTIMIZING FARES AND TRANSFER DISCOUNTS FOR A BUS-SUBWAY CORRIDOR

This paper aims to optimize fares and transfer discounts for public transit service along a bus-subway corridor with the consideration of effects of uncertainty in travel times and difference in stop spacing between bus and subway services on passenger behavior. The former factor is captured by the reserved time in travel cost and the latter one produces some passenger Origin–Destination (O–D) pairs along the corridor that can not be served by one mode only. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower-level capturing traveler choice behavior is a variable-demand Stochastic User Equilibrium (SUE) assignment model. A Genetic Algorithm (GA) is applied to solve the bi-level program while the Method of Successive Averages (MSA) is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the model and solution method. Numerical results indicate that the implementation of transfer discounts may be of great benefit to the social welfare and that the uncertainty in travel time and the difference in stop spacing play an important role in determining optimal fares and transfer discounts for the service along a bus-subway corridor.

Threshold Determination for Sharing Bus Rapid Transit–Exclusive Lanes with Conventional Buses

Sharing bus rapid transit (BRT) exclusive lanes with conventional buses is being considered to solve the problem of low utilization rate of BRT-exclusive lanes. However, the quantitative conditions and threshold that determine when to share need to be study. This paper took the common section of BRT and conventional bus lines as its research object. Practical investigation was conducted to analyze shared characteristics from multiple perspectives and explore influencing factors and mechanisms for sharing implementation. Based on the survey results, analytical models were established to quantify the influencing factors from three perspectives of road section, intersection, and bus stop. We selected departure volume of conventional buses as a threshold index and then summarized the constraints and the calculation process of sharing threshold. Finally, numerical examples of different scenarios were used to verify the feasibility and effectiveness of the method. The operation efficiency of the road section on exclusive lanes was the constraint on the lower limit of the shared threshold, while the upper limit was constrained by queuing probability or bus operation time under different intersections and stop spacing, which can provide reference for the shared setting of exclusive bus lanes.

A Bi-Level Programming Model for Optimal Bus Stop Spacing of a Bus Rapid Transit System

The purpose of this study is to create a bi-level programming model for the optimal bus stop spacing of a bus rapid transit (BRT) system, to ensure simultaneous coordination and consider the interests of bus companies and passengers. The top-level model attempts to optimize and determine optimal bus stop spacing to minimize the equivalent costs, including wait, in-vehicle, walk, and operator costs, while the bottom-level model reveals the relation between the locations of stops and spatial service coverage to attract an increasing number of passengers. A case study of Chengdu, by making use of a genetic algorithm, is presented to highlight the validity and practicability of the proposed model and analyze the sensitivity of the coverage coefficient, headway, and speed with different spacing between bus stops.