Headway fluctuation and bus bunching are commonly observed in transit operations, while holding control is a proven strategy to reduce bus bunching and improve service reliability. A transit operator would benefit from an accurate forecast of bus propagation in order to effectively control the system. To this end, we propose an 'ad-hoc' bus propagation model taking into account vehicle overtaking and distributed passenger boarding (DPB) behaviour. The latter represents the dynamic passenger queue swapping among buses when bunching at bus stops occurs and where bus capacity constraints are explicitly considered. The enhanced bus propagation model is used to build the simulation environment where different holding control strategies are tested. A quasi first-depart-first-hold (FDFH) rule is applied to the design of headway-and schedule-based holding control allowing for overtaking, with the objective to minimise the deviation from the targeted headway. The effects of control strategies are tested in an idealized bus route under different operational setting and in a real bus route in Guangzhou. We show that when the combined overtaking and queue-swapping behaviour are considered, the control strategies can achieve better headway regularity, less waiting time and less on-board travel time than their respective versions without overtaking and DPB. The benefit is even greater when travel time variability is higher and headway is smaller, suggesting that the control strategies are preferably deployed in high-frequency service.

This is a repository copy of Stochastic bus schedule coordination considering demand assignment and rerouting of passengers.

We propose a robust schedule coordination scheme which combines timetable planning with a semiflexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of costs functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation.

We propose a robust optimization model for limited-stop bus service with vehicle overtaking and demand dynamics. Time-dependent stochastic travel time is also considered. The objective is to minimize the total cost (user cost and operation cost) at the planning phase given a target reliability imperative. We further propose a simulation-based optimization framework incorporating response surface methodology to solve the problem efficiently. A real-world application result shows that vehicle overtaking and demand dynamics have significant impacts on the performance of limited-stop service and that the stop patterns are quite distinct when overtaking and demand dynamics are considered.

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On China urban arterials traffic presents a mixed flow feature because the percentage of bus flow is relatively high. This affects the applicability of traditional platoon dispersion models which generally only suitable for homogeneous traffic flow. Based on field observations, this paper proposes a mixed platoon dispersion model (MPDM) to macroscopically simulate the mixed platoon dispersion process along the road segment between two successive signalized intersections from the density view. In order to capture the heterogeneity in mixed platoon speeds, the truncated mixed Gaussian distribution (TMGD) is adopted here to fit the speed data collected in the field, and expectation maximization (EM) algorithm is employed to estimate the distribution parameters. Later, the piecewise platoon density function is developed to examine the platoon dispersion characteristics. By applying this density function, the formulation of the expected number of vehicles in the front of the platoon that have passed and the expected number of vehicles at the rear of the platoon that have not passed a downstream intersection, as well as the downstream arriving flow function are derived.Furthermore, numerical calculation for signal coordination verifies the effectiveness of the proposed MPDM.

A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM) was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM) algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model.

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