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Total cost minimizing transit route structures considering trips towards CBD and periphery

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Abstract

The total cost minimizing approach to design transit systems is extended here beyond the usual dimensions of fleet (frequency) and vehicle size in order to examine the most appropriate spatial setting of transit lines as well. Motivated by the case of large cities in Latin America, characterized by high volumes of relatively long urban trips, we analyze the best ways to provide public transport services in a simplified urban setting represented by an extended cross-shaped network, where short trips (periphery–center) and long trips (periphery–periphery) coexist, generating economies of density. Three families of strategic lines structures are compared: mostly direct, feeder–trunk and hub and spoke. For each structure fleet and vehicle sizes are optimized, considering total (users’ and operators’) costs. The best structure is found parametrically in total passenger volume, the proportion of long trips and the value of the transfer penalty. The advantages of each dominating structure are explained in terms of factors like idle capacity, waiting or in-vehicle times and number of transfers.

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Notes

  1. In Santiago, 81% of the inter-zonal trips are from periphery to periphery (Sectra 2012).

  2. The analysis of network economies of density does not require the inclusion of flows originating at the junctions; this would need the introduction of a third demand parameter.

  3. Thus, sensitivity to prices and level of service does not play a role in this stage; total demand under the cost function approach becomes a parameter in our model.

  4. This is the usual version of the total cost of the transit system, where externalities as pollution or accidents are not included. For a general model in a single transit line see Jara-Diaz and Gschwender (2003a).

  5. We assume that there are no schedules (known by the users), as this is the most usual situation in Latin-American cities. But even if published schedules exist, they do not necessarily coincide with the ideal travelling time of the user, transferring part of the waiting cost to additional stay at the origin or at the destination of the trip (scheduled delay).

  6. Raveau et al. (2014) find that the transfers penalty depends on very case–specific aspects—e.g. if the passenger has to ascend or descend, if there are escalators available, the probability of getting a seat or not being able to board the first vehicle.

  7. As noted earlier, DIR-8 is the only structure that requires a choice by some users: where to transfer. We chose the transfer point that minimizes the individual user cost. This has an impact on the cost of other actors, which explains why DIR-8 is not an intermediate optimal structure between DIR-4 and DIR-16.

  8. We studied this phenomenon in a previous paper, showing that FT gets relatively better as the proportion of trips originating at the junction increases, because FT avoids the idle capacity generated in the other structures (Gschwender et al. 2016). See also footnote 2.

  9. In the most unrealistic case of a negligible P t , HS would dominate in most of the space.

  10. As explained in the introduction, de-emphasizing users’ cost because of financial reasons caused a lower than optimal fleet of larger than optimal buses (Jara-Diaz and Gschwender 2009).

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Acknowledgements

This research was partially funded by Fondecyt, Chile, Grant 1160410, and the Institute for Complex Engineering Systems, grants ICM: P-05-004-F and CONICYT: FB0816. We are grateful to Juan Carlos Muñoz and to the anonymous referees for useful and constructive comments.

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Correspondence to Sergio Jara-Díaz.

Appendix: cost functions and optimal frequencies for the remaining structures

Appendix: cost functions and optimal frequencies for the remaining structures

$$\begin{aligned} VRC_{FT - D}^{*} & = 2(2 + \alpha )C_{0} tY + \sqrt {2T_{A} YC_{0} \left( {4C^{{\prime }} tY + 8\varepsilon P_{w} + P_{v} tY} \right)} + \sqrt {2nT_{A} YC_{0} \left[ {4C^{{\prime }} tY + \frac{{8\left( {1 + \alpha } \right)}}{2}\varepsilon P_{w} + P_{v} tY} \right]} \\ & \quad + \sqrt {2\alpha T_{A} YC_{0} \left( {4\alpha C^{{\prime }} tY + 8\varepsilon P_{w} + \alpha P_{v} tY} \right)} + YT_{A} \left[ {C^{{\prime }} \left( {1 + n + \alpha } \right) + \frac{{P_{v} }}{4}\left( {1 + \alpha } \right)\left( {2 + n} \right)} \right] + P_{t} \eta Y \\ \end{aligned}$$
(24)
$$f_{F}^{*} = \sqrt {\frac{Y}{{32T_{A} C_{0} }}\left( {4C^{{\prime }} tY + 8\varepsilon P_{w} + P_{v} tY} \right)}$$
(25)
$$f_{T}^{*} = \sqrt {\frac{Y}{{32nT_{A} C_{0} }}\left[ {4C^{{\prime }} tY + 4\left( {1 + \alpha } \right)\varepsilon P_{w} + P_{v} tY} \right]}$$
(26)
$$f_{D}^{*} = \sqrt {\frac{\alpha Y}{{32T_{A} C_{0} }}\left( {4\alpha C^{{\prime }} tY + 8\varepsilon P_{w} + \alpha P_{v} tY} \right)}$$
(27)
$$\begin{aligned} VRC_{HS}^{*} & = 2(1 + \alpha )C_{0} tY + \sqrt {\left( {2 + n} \right)T_{A} YC_{0} \left( {4C^{{\prime }} tY + 8P_{w} \varepsilon + P_{v} tY} \right)} \\ & \quad + \sqrt {\alpha \left( {2 + n} \right)T_{A} YC_{0} \left( {4\alpha C^{{\prime }} tY + 8P_{w} \varepsilon + \alpha P_{v} tY} \right)} \,\, \\ & \quad + \left( {2 + n} \right)T_{A} Y\frac{{\left( {1 + \alpha } \right)}}{2}\left( {C^{{\prime }} + \frac{{P_{v} }}{2}} \right) + P_{t} \eta Y \\ \end{aligned}$$
(28)
$$f_{in}^{*} = \sqrt {\frac{Y}{{16\left( {2 + n} \right)T_{A} C_{0} }}\left( {4C^{{\prime }} tY + 8\varepsilon P_{w} + P_{v} tY} \right)}$$
(29)
$$f_{out}^{*} = \sqrt {\frac{\alpha Y}{{16\left( {2 + n} \right)T_{A} C_{0} }}\left( {4\alpha C^{{\prime }} tY + 8\varepsilon P_{w} + \alpha P_{v} tY} \right)}$$
(30)
$$\begin{aligned} VRC_{DIR - 4}^{*} & = \frac{{\left( {4 + 3\alpha } \right)}}{2}tYC_{0} + \left( {2 + n} \right)T_{A} Y\left[ {\frac{{P_{v} \left( {1 + \alpha } \right)}}{4} + C^{{\prime }} } \right] \\ &\quad + 2\sqrt {\left( {2 + n} \right)T_{A} YC_{0} \left[ {\left( {4 + 3\alpha } \right)\left( {\frac{{C^{{\prime }} tY}}{2} + P_{w} \varepsilon } \right) + \frac{{\left( {16 + 12\alpha + 9\alpha^{2} } \right)}}{32}P_{v} tY} \right]} + P_{t} \eta Y \\ \end{aligned}$$
(31)
$$f_{DIR - 4}^{*} = \sqrt {\frac{Y}{{16\left( {2 + n} \right)T_{A} C_{0} }}\left[ {\left( {4 + 3\alpha } \right)\left( {\frac{{C^{{\prime }} tY}}{2} + \varepsilon P_{w} } \right) + \frac{{\left( {16 + 21\alpha^{2} } \right)}}{32}P_{v} tY} \right]}$$
(32)
$$\begin{aligned} VRC_{DIR - 8}^{*} & = \left( {2 + \alpha } \right)C_{0} tY + \left( {2 + n} \right)T_{A} Y\left[ {C^{{\prime }} + P_{v} \frac{{\left( {1 + \alpha } \right)}}{4}} \right] \\ & + \sqrt {4\left( {2 + n} \right)T_{A} YC_{0} \left[ {C^{{\prime }} tY\left( {2 + \alpha } \right) + 2\left( {2 + 3\alpha } \right)P_{w} \varepsilon + \frac{{\left( {4 + 5\alpha^{2} } \right)P_{v} tY}}{8}} \right]} + P_{t} \eta Y \\ \end{aligned}$$
(33)
$$f_{DIR - 8}^{*} = \sqrt {\frac{Y}{{64\left( {2 + n} \right)T_{A} C_{0} }}\left[ {\left( {2 + \alpha } \right)C^{{\prime }} tY + 2\left( {2 + 3\alpha } \right)\varepsilon P_{w} + \frac{{\left( {4 + 5\alpha^{2} } \right)}}{8}P_{v} tY} \right]}$$
(34)
$$\begin{aligned} VRC_{DIR - 16}^{*} & = 2C_{0} tY + \sqrt {16\left( {2 + n} \right)T_{A} YC_{0} \left[ {\frac{{C^{{\prime }} tY}}{2} + \left( {1 + 3\alpha } \right)P_{w} \varepsilon + \frac{{P_{v} tY}}{8}} \right]} \\ &\quad + \left( {2 + n} \right)T_{A} Y\left[ {C^{{\prime }} + P_{v} \frac{{\left( {1 + \alpha } \right)}}{4}} \right] + P_{t} \eta Y \\ \end{aligned}$$
(35)
$$f_{DIR - 16}^{*} = \sqrt {\frac{Y}{{512\left( {2 + n} \right)T_{A} C_{0} }}\left[ {4C^{{\prime }} tY + 8\left( {1 + 3\alpha } \right)\varepsilon P_{w} + P_{v} tY} \right]}$$
(36)

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Jara-Díaz, S., Gschwender, A. & Bravo, C. Total cost minimizing transit route structures considering trips towards CBD and periphery. Transportation 45, 1701–1720 (2018). https://doi.org/10.1007/s11116-017-9777-z

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