Headway Adherence. Detection and Reduction of the Bus Bunching Effect
Josep Mension, TMB, Miquel Estrada, UPC
We propose a work on detection and reduction of the bus bunching effect, which appears when two or more buses run one after the other and causes inefficiency, decrease in transport capacity and a loss of service quality.
When transit vehicles operate at headways of 10 minutes or less, vehicle bunching can occur. This way, two or more vehicles on the same route arrive together or in close succession, followed by a long gap between them.
From a passenger outlook, the lead vehicle is usually overcrowded, having collected its own passengers and passengers arriving early for the next service, and passengers arriving during the gap in service experience a longer waiting time than expected.
From the operator point of view, the less-utilized following vehicles represent wasted capacity, and more time is needed at the end of the route for schedule recovery, which increases the route's cycle time and in all probability the operating costs.
The bunching effect can be measured in terms of headway adherence, the regularity of transit vehicle arrivals with respect to the scheduled headway, and it is calculated as the coefficient of variation of headways Cvh: the standard deviation of headways (representing the range of actual headways), divided by the average (mean) headway.
Cvh=(σ(HA - HS))/H*A
Cvh: Coefficient of variation
σ: Standard deviation
HA: Actual headway
HS: Scheduled headway
H*A: Average actual headway
The coefficient of variation of headways can be also related to the probability, P that a given transit vehicle's headway, hi will be off-headway by more than one-half the scheduled headway h.
Despite it is difficult to explain to the stakeholders, it is the best available measure for describing the bunching effect as evidenced by diverse real examples in Barcelona.
To reduce the negative effects of time-headway variations on route performance, a procedure based on real-time bus tracking data at stops is proposed. This strategy controls the cruising speed of buses and considers the extension of the green phase of traffic lights at intersections, when a bus is significantly delayed. The performance of this strategy will be compared to the current static operation technique based on the provision of unproductive slack times at holding points.
An operational model is presented in order to estimate the operational effects of each controlling strategy, taking into account the vehicle capacity constraint. Controlling strategies are assessed in terms of passenger total travel and waiting time, as well as the coefficient of variation of time-headways. Moreover, the number of vehicles needed to provide the service is estimated in comparison to the holding point strategy. The effects of controlling strategies are tested in an idealized bus route under different operational settings and in the bus route of highest demand in Barcelona by simulation.
The results show that the proposed dynamic controlling strategy reduces passenger travel time by 21-37% as well as the coefficient of variation of headway by 78-83% regarding the uncontrolled case, providing a bus performance similar to the expected when time disturbance is not presented.
Association for European Transport