Dealing with Bus Bunching A control tool, a pilot plan and a

pedagogical game

Juan Carlos Muñoz, Felipe Delgado, Ricardo Giesen

Sergio Ariztía, Daniel Hernández, Felipe Ortiz and William Phillips Department of Transport Engineering and Logistics

Pontificia Universidad Católica de Chile

Santiago, Chile

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And so on so forth.

Our challenge: keep buses evenly spaced under an inherently unstable system

Now, if we want to prevent bunching from occurring … when is the

right time to intervene?

Bus bunching

Severe problem if not controlled

Most passengers wait longer than they should for crowded

buses

Reduces reliability affecting passengers and operators

Affects Cycle time and capacity

Put pressure in the authority for more buses

Contribution: Control Mechanism to Avoid Bus Bunching!

Approach

Based on real-time information (or estimations) about:

Bus position.

Bus loads.

# of Passengers waiting at each stop.

We run a rolling-horizon optimization model each time a bus

reaches a stop or every certain amount of time (e.g. 2 minutes)

The model minimizes:

Waiting for first bus + Waiting for subsequent buses + time held

Results: Simulation Animation

Simulation includes events randomness

2 hours of bus operation. 15 minutes “warm-up” period.

Encouraging simulation-based results

Excess waiting drops in over 60%

Excess Waiting for first bus drops in 80%

Waiting for second bus drops in 90%

Comfort inside buses improve significantly

Reliability for users improve significantly: waiting twice the average

interval drops from 1 out of 11 trips, to 1 out of 1250.

Cycle time drops by 4% and its variability by 35%

Common disobedience rate across drivers

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Obedience rate

HRT, Beta=0,5

Sin Control

Full disobedience of a set of drivers

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Deaf Buses from a total of 15 buses

Implementation

• The first pilot plan consisted in implemnting our holding

tool in buses of line 210 of SuBus from Transantiago

(Santiago, Chile) along its full path from 7:00 to 9:30 AM.

• We chose 24 out of 130 stops to hold buses

• One person in each of these 24 stops received text

messages (from a central computer) into their cell

phones indicating when each bus should depart from the

stop.

Plan Description

Control Points

The results were very promising even though the conditions were far

from ideal

Input Data

• Trajectories of given GPS data (on a regular day)

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Trajectories

Input Data • The trajectiories traveled by buses can be

inferred as:

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Corrected Trajectories for a typical day

Pilot Analysis

• Trajectories of our experiment

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Pilot Corrected Trajectories

Pilot Analysis

• Again… versus a regular day

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Corrected Trajectories

Main results

• Transantiago computes an indicator for regularity based on intervals exceeding twice the expected headway (and for how much).

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Piloto1 Prueba8 Prueba9 Prueba10 Prueba11 Prueba12 Prueba13 Prueba14 Prueba15 Prueba16 Prueba17

ICR Aproximado PM y TPM (UF)

Fines due to regularity on that day dropped around 50%

The demand captured by the line grew!

• Line 210 captured an extra 20% demand!

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Demand for Line 210 (pax)

Demand on All lines

(pax)

This pilot plan can improve significantly

1) GPS errors can be corrected

2) Run the Optimization more often (from 3.5 to 2 min)

3) Calibrate speeds and arrival rates

4) Check data inputs before feeding the system

And more importantly:

5) Bypass the person at the stop. Communicate to drivers

Conclusions

Developed a tool for headway control using Holding in real time reaching

time savings of over 50%

Extending it to green time extension and boarding limits savings can reach

over 60% with only minor impact on car users

Huge improvements in comfort and reliability

The tool is fast enough for real time applications. It had been tested

successfully in simulations (for the Insurgentes corridor in Mexico city)

and in the streets (line 210 in Santiago, Chile) with very promising results.

Publications and working papers

• Delgado, F., Muñoz, J.C., Giesen, R., Cipriano, A. (2009) Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits. Transportation Research Record, Vol 2090, 55-67

• Munoz, J.C. and Giesen, R. (2010). Optimization of Public Transportation Systems. Encyclopedia of Operations Research and Management Science, Vol 6, 3886-3896.

• Delgado, F., J.C. Muñoz and R. Giesen (2012) How much can holding and limiting boarding improve transit performance? Trans Res Part B, , vol.46 (9), 1202-1217

• Muñoz, J.C., C. Cortés, F. Delgado, F. Valencia, R. Giesen, D. Sáez and A. Cipriano (2013) Comparison of dynamic control strategies for transit operations. Forthcoming in Trans Res Part C.

Pedagogical game

Yesterday we submitted a proposal to an innovation grant for US$500,000 (40% committed by a bus operator).

The goal is to turn this experience into

a commercial tool.

For a detailed talk go to our www.brt.cl Webinar

Dealing with Bus Bunching A control tool, a pilot plan and a

pedagogical game

Juan Carlos Muñoz, Felipe Delgado, Ricardo Giesen

Sergio Ariztía, Daniel Hernández, Felipe Ortiz and William Phillips Department of Transport Engineering and Logistics

Pontificia Universidad Católica de Chile