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Reducing traffic externalities by multiple-cordon pricing

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Abstract

The second-best congestion pricing schemes including common optimum, one cordon, and multiple cordons schemes are compared with the first-best optimum pricing scheme. A cross-subsidy effect exists in these second-best pricing models. However, the scheme with more cordons will diminish the cross-subsidy and approach an efficient and equitable outcome. The relative efficiency of a cordon pricing scheme for the case of Taipei metropolis is very high. One single cordon yields excellent performance of 93% relative efficiency. There might be some factors causing the good results: the uncongested traffic condition, the linear unit distance cost in traffic flow forming a nonlinear cost function, and the trip demands with continuous space and the same destination (the central business district) in the network.

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Notes

  1. These studies include Keeler and Small (1977), Dewees (1979), Gomez-Ibanez and Fauth (1980), Anderson and Mohring (1997), Nguyen (1999), May and Milne (2000), De Borger and Proost (2001), Li (2002), Niskanen and Nash (2004), Santos (2004), and Eliasson and Matsson (2006).

  2. Rietveld and Verhoef (1998) discussed the social feasibility of road pricing policies.

  3. Note that the linear cost function is for every unit distance (a very small distance) of a trip. Because each point (user) on the line (road) between the city boundary and CBD generates travel demand to the same destination (the CBD), the traffic flow at x is formulated by cumulating every trip from x to B (boundary), and the cost function of a trip originating at x is thus the sum of the cost of every unit of distance from 0 to x. The traffic flow is nonlinear and increasing in the distance approaching the CBD with an increasing rate. Therefore, though the cost of driving every unit distance is linear in traffic flow, the cost function of any trip is nonlinear in distance of the trip. This setting for a continuous spatial trip pattern is suited for a developed transportation corridor which generates the trips with many different origins and one destination (the CBD).

  4. The convexity and uniqueness are satisfied and the solution can be obtained by solving the following differential equation with boundary conditions.

  5. This implies that the average speed is about 26 km/hr, which is obtained by searching Google Maps in this corridor for the peak hours. This value needs to be multiplied by the value of time to convert into the monetary value.

  6. It is assumed that the number of trips per person is linearly negatively proportionate to the distance to the CBD.

  7. The trips between Danshui district and Beitou district are collected by the average daily traffic flow at Jin-Long Bridge on Provincial Highway No. 2 and at Gan-Zhen-Lin on Provincial Highway No. 2A. Those between Beitou district and the CBD are based on the traffic flow at Cheng-De Road and Xi-An Street. These data are from Taipei City Traffic Engineering Office (2012) and Directorate General of Highway, Taiwan (2012).

  8. The number of trips from Danshui district to Beitou district is around 90% of that from Danshui district to the CBD. The data are from the Department of Budget, Accounting, and Statistics, Taipei City Government (2010).

  9. The maximum speed on the roads in Danshui district is 70 km/h and that in Beitou district is around 50 ~ 60 km/h. 60 km/h is thus assumed to be the free flow speed.

  10. This ratio may not reflect exactly the acceptance by road users. In reality, most people may resist any pricing scheme compared to no toll. However, if people pay less than the external costs they generate, it may decrease resistance against the pricing regime. In this model, the assumption of the residents being uniformly distributed on the transportation corridor makes this index easily calculated.

  11. The fairness index may be treated as one for equity impact based on horizontal dimension user groups (Maruyama and Sumalee 2007).

  12. The unit of social net benefit and level of toll is minutes instead of a monetary unit. It can be multiplied by the value of time to yield the monetary unit.

  13. The value for the analysis is under normalization. For the Taipei metropolis, the number of residents is 4,642,879 in 2012 (assuming half of residents in New Taipei city commute to the CBD in Taipei). Nearly 60% of commuting trips are by private vehicles. The normalization multiplier is thus equal to 4,642,879 (60%)/26.3 = 105,921. Time value is NT$ 4.85 per minute. The social surplus is thus NT$ 47,891,870 with no toll.

  14. In this case, even one-cordon pricing provides good performance. Are the linear demand function and linear unit cost function responsible for this result? If the demand function follows the law of demand (an increase in price will decrease the quantity of demand), the performance with cordon pricing will not change too much. In addition, though the cost of driving every unit distance is linear in traffic flow, the cost function of any trip is nonlinear in distance of the trip (see footnote 3). Thus, the different function form of demand and cost will not make a large change in the outcome. The continuous spatial distribution of a single transportation corridor may be largely responsible for this result.

  15. The AR may be underestimated for the tolling schemes of more cordons. For a reasonable guess, AR will approach only 50% as the tolling is for infinite cordons. However, the toll level is very close to the external cost even though half of the users are charged a little bit higher than the external costs.

  16. Note that the normalization multiplier 105,291 needs to be multiplied by the number of trips for one resident on these figures to obtain the total trips for the corridor.

  17. The traffic flow Q(x) in the figure has to multiply the normalization multiplier 105,291 (see footnote 12). Specifically, Q(5) = 2.5 means 263,228 vehicles/day passing the point 5 km from the CBD and commuting to the CBD.

  18. We found the relative efficiency from their net benefit. This high relative efficiency is obtained even though they set an upper bound constraint for the toll level of an initial-cordon scenario.

  19. Shanghai metropolis had population of 34,000,000 residents, while Osaka metropolis had 19,342,000 in 2010.

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Acknowledgements

The authors wish to thank the Editor and the anonymous referees for very helpful comments in the paper revision.

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Correspondence to Jyh-Fa Tsai.

Appendices

Appendix 1

The following boundary conditions are used for determining the values of the six unknowns above:

  1. (1)

    The condition with the CBD (x = 0)

    When the location is the CBD, the following relations hold:

    $$p\left( {q_{1}^{**} \left( 0 \right)} \right) = C_{1} \left( 0 \right) = 0,$$
    (15a)
    $$p^{{\prime }} \frac{{dq_{1}^{**} \left( 0 \right)}}{dx} - t\left( {Q_{1} \left( 0 \right)} \right) = 0.$$
    (15b)
  2. (2)

    The condition with the first cordon location (\(x = x_{m1}\))

    When the location is the first cordon location, combining (11a) and (11b) with the trip cost condition,\(C_{1} \left( {x_{m1} } \right) = C_{2} (x_{m1} )\), yields:

    $$p\left( {q_{1}^{**} \left( {x_{m1} } \right)} \right) = p\left( {q_{2}^{**} \left( {x_{m1} } \right)} \right) - \tau_{1} .$$
    (16)
  3. (3)

    The condition with the second cordon location (x =  \(x_{m2}\))

    When the location is the second cordon location, combining (11b) and (11c) with the trip cost condition, \(C_{2} \left( {x_{m2} } \right) = C_{3} (x_{m2} )\), yields:

    $$p\left( {q_{2}^{**} \left( {x_{m2} } \right)} \right) = p\left( {q_{3}^{**} \left( {x_{m2} } \right)} \right) - \tau_{2} .$$
    (17)
  4. (4)

    The condition with city boundary (x = B)

    When the location is at the city boundary, the condition that marginal benefit equals the trip cost and the derivative for this condition must hold:

    $$p\left( {q_{3}^{**} (B)} \right) = C_{3} \left( B \right) + \tau_{1} + \tau_{2} ,$$
    (18a)
    $$p^{\prime } \frac{{dq_{3}^{**} (B)}}{dx} - t\left( {Q_{3} \left( B \right)} \right) = 0.$$
    (18b)

From the above conditions, (15a18b), the six unknown constants are determined as follows:

$${\uplambda }_{1} = \frac{{ - 2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{ - {{\upalpha B}}}} + {\uptau }_{1} \left( {{\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{\text{m1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}}_{\text{m1}} } \right)}} } \right) + {\uptau }_{2} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{\text{m2}} } \right)}} - {\text{e}}^{{ - {{\upalpha (B}} - {\text{x}}_{\text{m2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}},$$
$${\uplambda }_{2} = \frac{{2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{{{\upalpha B}}}} - {\uptau }_{1} \left( {{\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right) - {\uptau }_{2} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }({\text{B}} - {\text{x}}_{{{\text{m}}2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}},$$
$${\uplambda }_{3} = \frac{{ - 2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{ - {{\upalpha B}}}} - {\uptau }_{1} ({\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}}_{\text{m1}} } \right)}} + {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} + {\text{x}}_{\text{m1}} } \right)}} ) + {\uptau }_{2} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{\text{m2}} } \right)}} - {\text{e}}^{{ - {\upalpha }({\text{B}} - {\text{x}}_{\text{m2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}},$$
$${\uplambda }_{4} = \frac{{2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{ - {{\upalpha B}}}} - {\uptau }_{1} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} ) - {\uptau }_{2} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }({\text{B}} - {\text{x}}_{{{\text{m}}2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}},$$
$${\uplambda }_{5} = \frac{{ - 2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{ - {{\upalpha B}}}} - {\uptau }_{1} ({\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} ) - {\uptau }_{2} ({\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }({\text{B}} + {\text{x}}_{{{\text{m}}2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}},$$
$${\uplambda }_{6} = \frac{{2{\text{f}}/{\upalpha } + 2{\text{ae}}^{{ - {{\upalpha B}}}} - {\uptau }_{1} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} ) - {\uptau }_{2} ({\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{{\upalpha }({\text{B}} + {\text{x}}_{{{\text{m}}2}} )}} )}}{{2{\text{b}}({\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} )}}.$$

Appendix 2

$$\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }} = \frac{{ - {\uptau }_{1} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;0 \le {\text{x}} \le {\text{x}}_{\text{m1}} ,$$
(19a)
$$\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }} = \frac{{ - {\uptau }_{1} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0,\quad for\;{\text{x}}_{{{\text{m}}1}} \le {\text{x}} \le {\text{x}}_{{{\text{m}}2}} ,$$
(19b)
$$\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }} = \frac{{ - {\uptau }_{1} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0,\quad for\;{\text{x}}_{{{\text{m}}2}} \le {\text{x}} \le {\text{B}},$$
(19c)
$$\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}2}} }} = \frac{{ - {\uptau }_{2} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;0 \le {\text{x}} \le {\text{x}}_{{{\text{m}}1}} ,$$
(20a)
$$\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}2}} }} = \frac{{ - {\uptau }_{2} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;{\text{x}}_{{{\text{m}}1}} \le {\text{x}} \le {\text{x}}_{{{\text{m}}2}} ,$$
(20b)
$$\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{\text{m2}} }} = \frac{{ - {\uptau }_{ 2} {\upalpha }\left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{\text{m2}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{\text{m2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{\text{m2}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{\text{m2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0,\quad for\;x_{\text{m2}} \le {\text{x}} \le {\text{B}}$$
(20c)
$$\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }} = \frac{{\left( {{\text{e}}^{{ - {\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} - {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} > 0,\quad for\;0 \le {\text{x}} \le {\text{x}}_{{{\text{m}}1}} ,$$
(21a)
$$\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }} = \frac{{ - \left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;{\text{x}}_{{{\text{m}}1}} \le {\text{x}} \le {\text{x}}_{{{\text{m}}2}} ,$$
(21b)
$$\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }} = \frac{{ - \left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}1}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}1}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;{\text{x}}_{{{\text{m}}2}} \le {\text{x}} \le {\text{B,}}$$
(21c)
$$\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }} = \frac{{\left( {{\text{e}}^{{ - {\upalpha }\left( {{\text{B}} + {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{B}} + {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} > 0,\quad for\;0 \le {\text{x}} \le {\text{x}}_{{{\text{m}}1}} ,$$
(22a)
$$\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }} = \frac{{\left( {{\text{e}}^{{ - {\upalpha }\left( {{\text{B}} + {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{ - {\upalpha }\left( {{\text{B}} - {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( {{\text{B}} + {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} - {\text{e}}^{{{\upalpha }\left( {{\text{B}} - {\text{x}} - {\text{x}}_{{{\text{m}}2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} > 0,\quad for\;{\text{x}}_{{{\text{m}}1}} \le {\text{x}} \le {\text{x}}_{{{\text{m}}2}} ,$$
(22b)
$$\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }} = \frac{{ - \left( {{\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{ - {\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} + {\text{x}}_{{{\text{m}}2}} } \right)}} + {\text{e}}^{{{\upalpha }\left( { - {\text{x}} + {\text{B}} - {\text{x}}_{{{\text{m}}2}} } \right)}} } \right)}}{{2{\text{b}}\left( {{\text{e}}^{{{{\upalpha B}}}} + {\text{e}}^{{ - {{\upalpha B}}}} } \right)}} < 0, \quad for\;{\text{x}}_{{{\text{m}}2}} \le {\text{x}} \le {\text{B}} .$$
(22c)

Appendix 3

Substituting trip in (13a13c) into (14), the first-order conditions are:

$$\mathop \int \limits_{0}^{{{\text{q}}_{1}^{**} ({\text{x}}_{{{\text{m}}1}} )}} {\text{p}}\left( {\text{q}} \right){\text{dq}} - {\text{C}}_{1} \left( {{\text{x}}_{{{\text{m}}1}} } \right){\text{q}}_{1}^{**} \left( {{\text{x}}_{{{\text{m}}1}} } \right) - \left[ {\mathop \int \limits_{0}^{{{\text{q}}_{2}^{**} ({\text{x}}_{{{\text{m}}1}} )}} {\text{p}}\left( {\text{q}} \right){\text{dq}} - {\text{C}}_{2} \left( {{\text{x}}_{{{\text{m}}1}} } \right){\text{q}}_{2}^{**} \left( {{\text{x}}_{{{\text{m}}1}} } \right)} \right] + \mathop \int \limits_{0}^{{{\text{x}}_{{{\text{m}}1}} }} \left[ {{\text{p}}\left( {{\text{q}}_{1}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{1} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}1}} }}^{{{\text{x}}_{{{\text{m}}2}} }} \left[ {{\text{p}}\left( {{\text{q}}_{2}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{2} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}2}} }}^{\text{B}} [{\text{p}}\left( {{\text{q}}_{3}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{3} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)]\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}1}} }}{\text{dx}} = 0,$$
(23a)
$$\mathop \int \limits_{0}^{{{\text{q}}_{2}^{**} ({\text{x}}_{{{\text{m}}2}} )}} {\text{p}}\left( {\text{q}} \right){\text{dq}} - {\text{C}}_{2} \left( {{\text{x}}_{{{\text{m}}2}} } \right){\text{q}}_{2}^{**} \left( {{\text{x}}_{{{\text{m}}2}} } \right) - \left[ {\mathop \int \limits_{0}^{{{\text{q}}_{3}^{**} ({\text{x}}_{{{\text{m}}2}} )}} {\text{p}}\left( {\text{q}} \right){\text{dq}} - {\text{C}}_{3} \left( {{\text{x}}_{{{\text{m}}2}} } \right){\text{q}}_{3}^{**} \left( {{\text{x}}_{{{\text{m}}2}} } \right)} \right] + \mathop \int \limits_{0}^{{{\text{x}}_{{{\text{m}}1}} }} \left[ {{\text{p}}\left( {{\text{q}}_{1}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{1} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}2}} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}1}} }}^{{{\text{x}}_{{{\text{m}}2}} }} \left[ {{\text{p}}\left( {{\text{q}}_{2}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{2} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}2}} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}2}} }}^{\text{B}} \left[ {{\text{p}}\left( {{\text{q}}_{3}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{3} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\text{x}}_{{{\text{m}}2}} }}{\text{dx}} = 0,$$
(23b)
$$\mathop \int \limits_{0}^{{{\text{x}}_{{{\text{m}}1}} }} \left[ {{\text{p}}\left( {{\text{q}}_{1}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{1} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}1}} }}^{{{\text{x}}_{{{\text{m}}2}} }} \left[ {{\text{p}}\left( {{\text{q}}_{2}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{2} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}2}} }}^{\text{B}} \left[ {{\text{p}}\left( {{\text{q}}_{3}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{3} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{1} }}{\text{dx}} = 0,$$
(23c)
$$\mathop \int \limits_{0}^{{{\text{x}}_{{{\text{m}}1}} }} \left[ {{\text{p}}\left( {{\text{q}}_{1}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{1} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{1}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}1}} }}^{{{\text{x}}_{{{\text{m}}2}} }} \left[ {{\text{p}}\left( {{\text{q}}_{2}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{2} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{2}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }}{\text{dx}} + \mathop \int \limits_{{{\text{x}}_{{{\text{m}}2}} }}^{\text{B}} \left[ {{\text{p}}\left( {{\text{q}}_{3}^{**} \left( {\text{x}} \right)} \right) - {\text{C}}_{3} \left( {\text{x}} \right) - {\text{E}}\left( {\text{x}} \right)} \right]\frac{{\partial {\text{q}}_{3}^{**} \left( {\text{x}} \right)}}{{\partial {\uptau }_{2} }}{\text{dx}} = 0,$$
(23d)
$$E(x) = \left\{ \begin{gathered} \int\limits_{0}^{x} {t^{\prime } \left( {Q_{1} \left( y \right)} \right)Q_{1} \left( y \right)dy,\quad 0 \le x \le x_{{m1}} } \hfill \\ \int\limits_{0}^{{x_{{m1}} }} {t^{\prime } \left( {Q_{1} \left( y \right)} \right)Q_{1} \left( y \right)dy} + \int\limits_{{x_{{m1}} }}^{x} {t^{\prime } \left( {Q_{2} \left( y \right)} \right)Q_{2} \left( y \right)dy,\quad x_{{m1}} \le x \le x_{{m2}} } \hfill \\ \int\limits_{0}^{{x_{{m1}} }} {t^{\prime } \left( {Q_{1} \left( y \right)} \right)Q_{1} \left( y \right)dy} + \int\limits_{{x_{{m1}} }}^{{x_{{m2}} }} {t^{\prime } \left( {Q_{2} \left( y \right)} \right)Q_{2} \left( y \right)dy} + \int\limits_{{x_{{m2}} }}^{B} {t^{\prime } \left( {Q_{3} \left( y \right)} \right)Q_{3} \left( y \right)dy,\quad x_{{m2}} \le x \le B.} \hfill \\ \end{gathered} \right.$$
(24)

E(x) represents the externality incurred from an additional trip from x on all drivers using the road between 0 and x. The first two parts of (23a) represent the direct effect on total surplus caused by the outward move of the first cordon location. The other three parts of (23a) represent the indirect effect on total surplus via the change in trips on the three sections of the road by an outward move for the first cordon location. Similarly, (23b) represents the direct effect and indirect total surplus caused by an outward move for the second cordon location. In addition, (23c) and (23d) represent the indirect effect on total surplus via the change in the trips on the three sections of the road by a unit increase of toll at the first cordon location and at the second cordon location, respectively.

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Tsai, JF., Lu, SY. Reducing traffic externalities by multiple-cordon pricing. Transportation 45, 597–622 (2018). https://doi.org/10.1007/s11116-016-9742-2

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