The two-train separation problem on level track

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Energy-efficient train timetables The two-train separation problem on level track Amie Albrecht Phil Howlett Peter Pudney Xuan Vu Peng Zhou Scheduling and Control Group School of Information Technology and Mathematical Sciences, UniSA www.tinyurl.com/iaror-aa ARC Linkage Grant LP110100136

reduce energy costs by up to 20% improve on-time arrivals by 10% reduce braking by up to 30%

Power Hold Coast Brake http://scg.ml.unisa.edu.au/dcb.svg

Optimal control of a single train Equation of motion: dv dt = p q r(v) + g(x) v dx Elapsed distance: dt = v Journey cost: J = T 0 p dt Controls: Tractive power: 0 p(x) P Braking force: 0 q(x) Q Problem: Find controls p, q and an associated speed profile v(x) with v(0) = v(x ) = 0 and t(x) T that minimises energy.

Optimal control of a single train Equation of motion: dv dt = p q r(v) + g(x) v dx Elapsed distance: dt = v Journey cost: J = T 0 p dt Controls: Tractive power: 0 p(x) P Braking force: 0 q(x) Q Problem: Find controls p, q and an associated speed profile v(x) with v(0) = v(x ) = 0 and t(x) T that minimises energy.

Optimal control of a single train Equation of motion: dv dt = p q r(v) + g(x) v dx Elapsed distance: dt = v Journey cost: J = T 0 p dt Controls: Tractive power: 0 p(x) P Braking force: 0 q(x) Q

Optimal control of a single train Equation of motion: dv dt = p q r(v) + g(x) v dx Elapsed distance: dt = v Journey cost: J = T 0 p dt Controls: Tractive power: 0 p(x) P Braking force: 0 q(x) Q Problem: Find controls p, q and an associated speed profile v(x) with v(0) = v(x ) = 0 and t(x) T that minimises energy.

40 35 30 25 v 20 15 10 5 0 2000 0 2000 4000 6000 8000 10000 12000 x

What we know about single train control On level track the optimal strategy is power-speedhold-coast-brake.

What we know about single train control 30 V v 20 U 10 0 0 10000 20000 30000 px(0,v) pt(0,v) pj(0,v) x hx(a, b, V ) ht(a, b, V ) hj(a, b, V ) cx(v,u) ct(v,u) cj(v,u) bx(u, 0) bt(u, 0) bj(u, 0)

What we know about single train control 30 V v 20 U 10 0 0 10000 20000 30000 px(0,v) pt(0,v) pj(0,v) x hx(a, b, V ) ht(a, b, V ) hj(a, b, V ) cx(v,u) ct(v,u) cj(v,u) bx(u, 0) bt(u, 0) bj(u, 0)

What we know about single train control 30 V v 20 U 10 0 0 10000 20000 30000 px(0,v) pt(0,v) pj(0,v) x hx(a, b, V ) ht(a, b, V ) hj(a, b, V ) cx(v,u) ct(v,u) cj(v,u) bx(u, 0) bt(u, 0) bj(u, 0)

What we know about single train control 30 V v 20 U 10 0 0 10000 20000 30000 px(0,v) pt(0,v) pj(0,v) x hx(a, b, V ) ht(a, b, V ) hj(a, b, V ) cx(v,u) ct(v,u) cj(v,u) bx(u, 0) bt(u, 0) bj(u, 0)

What we know about single train control 30 V v 20 U 10 0 0 10000 20000 30000 px(0,v) pt(0,v) pj(0,v) x hx(a, b, V ) ht(a, b, V ) hj(a, b, V ) cx(v,u) ct(v,u) cj(v,u) bx(u, 0) bt(u, 0) bj(u, 0)

What we know about single train control On level track the optimal strategy is power-speedhold-coast-brake. As the hold speed increases the journey time decreases. There is a unique hold speed for each given journey time.

What we know about single train control On level track the optimal strategy is power-speedhold-coast-brake. As the hold speed increases the journey time decreases. There is a unique hold speed for each given journey time. We can also find the optimal strategy for: Piecewise-constant and continuously varying gradients Steep gradients Speed limits

What happens with multiple trains?

What happens with multiple trains? If there are no disruptions we can drive efficiently to the timetable.

What happens with multiple trains? If there are no disruptions we can drive efficiently to the timetable. That rarely happens! In practice, trains are often slowed or stopped at signals for safe separation. Instead, trains should be regulated so that they are less likely to encounter restrictive signals.

What happens with multiple trains? If there are no disruptions we can drive efficiently to the timetable. That rarely happens! In practice, trains are often slowed or stopped at signals for safe separation. Instead, trains should be regulated so that they are less likely to encounter restrictive signals. So, we want to determine optimal driving strategies for a fleet of trains.

The two-train separation problem Problem: Find driving strategies for two trains travelling on the same track in the same direction subject to given journey times so that an adequate separation is maintained and so that the total energy consumption is minimised.

The two-train separation problem Problem: Find driving strategies for two trains travelling on the same track in the same direction subject to given journey times so that an adequate separation is maintained and so that the total energy consumption is minimised. In general, the overall strategy may be better if neither train follows the single-train optimal profile.

Maintaining safe separation Do not allow two trains on the same track section at the same time.

Maintaining safe separation Do not allow two trains on the same track section at the same time. Specify intermediate signal times. A signal time is: the latest exit time for the leading train the earliest entry for the following train

Outline of a solution procedure 1. Find optimal journeys with prescribed intermediate signal times 2. Find optimal intermediate times

1a. An optimal journey for the leading train If the optimal unrestricted journey does not leave a particular section before the required time then it must go faster on the first part of the journey.

1a. An optimal journey for the leading train If the optimal unrestricted journey does not leave a particular section before the required time then it must go faster on the first part of the journey. A strategy of optimal type may use different hold speeds for different sections, but as the journey progresses the hold speeds will decrease. power-hold-coast }{{} first section coast-hold-coast }{{} for (n 2) sections coast-hold-coast-brake }{{} last section

1b. An optimal journey for the following train If the optimal unrestricted journey enters a particular section before the required time then it must go slower on the first part of the journey. A strategy of optimal type may use different hold speeds for different sections, but as the journey progresses the hold speeds will increase. power-hold-power }{{} for (n 1) sections power-hold-coast-brake }{{} last section

1. Optimal journeys with prescribed intermediate signal times 30 U 1 U 2 20 U 3 10 U 4 0 x 0 x 1 x 2 x 3 x 4 30 U 2,U 3 20 U 1 U 4 10 0 x 0 x 1 x 2 x 3 x 4

2. Finding optimal intermediate times Calculate times taken to traverse sections (using p t, h t, c t, b t) Some requirements: s i=0 f i s 1 g i + T i=0 n f i T l i=0 n g i T f i=0 s = 1,..., n

2. Finding optimal intermediate times Form a Lagrangian function: J = J l + J f + constraints Compute the partial derivatives of J : f i V j g i Y j Arrive at a necessary condition for optimality This condition means we can check if prescribed times are optimal.

Future work Implement an automated search for the hold speeds Devise an efficient algorithm to optimise the prescribed intermediate times Solve the three-train problem (and then many trains) Tackle non-level track Integrate with scheduling systems (use timing windows rather than timing points)