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Tradeoffs among free-flow speed, capacity, cost, and environmental footprint in highway design

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Abstract

This paper investigates differentiated design standards as a source of capacity additions that are more affordable and have smaller aesthetic and environmental impacts than modern expressways. We consider several tradeoffs, including narrow versus wide lanes and shoulders on an expressway of a given total width, and high-speed expressway versus lower-speed arterial. We quantify the situations in which off-peak traffic is sufficiently great to make it worthwhile to spend more on construction, or to give up some capacity, in order to provide very high off-peak speeds even if peak speeds are limited by congestion. We also consider the implications of differing accident rates. The results support expanding the range of highway designs that are considered when adding capacity to ameliorate urban road congestion.

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Notes

  1. See FHWA (2006), Ch 7. Of the $84.5 billion in investments in urban arterial and collector roads meeting defined cost-benefit criteria in this report, 53% is for freeways and expressways—of which about half is for expansion, half for rehabilitation or environmental enhancement (Exhibit 7-3).

  2. We do not attempt to account quantitatively for the truck restrictions, tighter curves, or nicer landscaping that may further enhance parkway amenities. We suspect that in some cases it would be optimal to restrict trucks altogether, but an explicit model of truck restrictions would be far more complex and is not undertaken here. Safety implications are discussed further in the section on “Safety”.

  3. Cassidy and Bertini (1999) suggest that the highest observed flow, which is larger, is not a suitable definition of capacity because it generally breaks down within a few minutes—although Cassidy and Rudjanakanoknad (2005) hold out some hope that this might eventually be overcome through sophisticated ramp metering strategies. Our speed-flow function does not include the backward-bending region, known as congested flow in the engineering literature and as hypercongested flow in the economics literature, because flow in that region leads to queuing which we incorporate separately. See Small and Verhoef (2007, Sect 3.3.1, 3.4.1) for further discussion of hypercongestion.

  4. Analyzing more daily time periods would of course increase precision, but would also make the model more location-specific. By using only two periods, we miss some congestion that is caused by queue buildups during shorter periods of higher demand, and thus may understate the advantage of higher-capacity roads. To compensate, we use a rather long 4-h one-directional peak.

  5. We ignore the difference in cost due to converting part of the paved shoulders in the “regular” design to vehicle-carrying pavements in the “narrow” design; since the largest component of new construction cost is grading and structures, this difference should be minor. We also ignore any differences in maintenance cost that may occur because vehicles on narrow lanes are more likely to veer onto the shoulder or put weight on the edge of the pavement (AASHTO 2004, p. 311).

  6. Note that for the urban streets in Fig. 3b, the total two-directional roadway width at the intersection itself is less than the sum of those of the two separate one-directional roadways, because the left turn lanes in both directions share the same lateral space. That is, the width of the two directional roadway includes only the width of one, not two, left turn lanes. For the “regular” design this is 2 × (12 + 12 + 8) + 12 = 76 = 2 × 38, whereas for the “narrow” design it is 2 × (10 + 10 + 10 + 3) + 10 = 76 = 2 × 38; hence both are described as having a 38-foot one-directional roadway.

  7. The calculations are done with each period continuous (i.e. 6–10 am peak, 10 am–10 pm offpeak). We found it makes a negligible difference if the peak is in the afternoon so the offpeak period is split into two parts. We also computed results for a two-peak scenario with each peak period equal to 2 h, representing a case where the traffic is evenly distributed during the morning and afternoon peaks. The two-peak scenario is briefly addressed at the end of this and the next sections, and both results are described in detail in Appendix B of the Online Resource.

  8. Nevertheless, we performed the same analysis using reconstruction costs of existing lanes, which are lower than the construction costs of new alignment shown in Table 3. The results are qualitatively similar: using reconstruction costs favors the narrow roads somewhat less in small cities and more in large cities. The sources used are the same as those listed in Table 3; see Appendix C of the Online Resource for more details.

  9. Lake Shore Drive includes six signalized intersections (only five going southbound) within its 15-mile length, for an average spacing of over two miles; but all the signals are within a central section about 2.4 miles in length. This highway opened in 1937 (Chicago Area Transportation Study 1998).

  10. Of course, the idea of building an entire network is an idealization, made here solely in order to account for the different capacities of different design options.

  11. According to Small and Verhoef (2007, Sect. 2.6.5), the value of time for work trips is typically estimated as 50% of the wage rate, which would be about $10.50 per hour for 2009 (BLS 2010, Table 1, reporting mean hourly wage for civilian workers). We assume these value of time studies apply to the entire vehicle, although authors are often ambiguous. Values of time are higher for work trips than for others, but occupancies are lower; we assume these two factors balance out between peak and off-peak travel so assign them both the same value of time.

  12. The delay calculation in the bottleneck queuing model at the entrance of the road is very similar to the HCM’s control delay. In the bottleneck model described in Section 2 of this paper, the uniform control delay is zero (because there is no signal) and the term containing k in Eq. (16) is negligible because of the large traffic volume. The remaining components in Eq. (16) plus the HCM initial queue delay (both converted to hours) give precisely the same result as the bottleneck model.

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Acknowledgments

We are grateful to the University of California Transportation Center for financial support, and to three anonymous referees and many colleagues for comments on earlier drafts, especially Pablo Durango-Cohen, Robin Lindsey, Robert Noland, Robert Poole, Peter Samuel, Ian Savage, and Erik Verhoef. Of course, all responsibility for facts and opinions expressed in the paper lies with the authors.

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Correspondence to Chen Feng Ng.

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Appendix: Speeds and capacities from the highway capacity manual (2000)

Appendix: Speeds and capacities from the highway capacity manual (2000)

This appendix briefly discusses the HCM’s methodology for calculating speeds and capacities for expressways, which the HCM calls “freeways” (based on HCM ch. 13, 23), and arterials (based on HCM, ch. 10, 12, 15, 16, 21). A more detailed explanation of the equations and parameter values are presented in the online version of this Appendix (see Online Resource).

Expressways/Freeways

Capacity varies by free-flow speed, and equation 23-1 in the HCM is used to estimate free-flow speed (FFS) of a basic freeway segment:

$$ \text{FFS} = \text{BFFS} \,-\, f_{LW} - \,f_{LC} - f_{N} - f_{ID} $$
(11)

A brief description of each parameter and the parameter values used in the paper are given in Table 5. As shown in Appendix N of the highway performance monitoring system (HPMS) field manual (FHWA 2002), the relationship between base capacity (BaseCap, measured in passenger-car equivalents per hour per lane) and free-flow speed is:

Table 5 Parameter values for expressways
$$ BaseCap = \left\{ {\begin{array}{*{20}c} {1,700 + 10FFS} \hfill \\ {2,400} \hfill \\ \end{array} \begin{array}{*{20}c} {{\text{ for }}\text{FFS} < 70} \hfill \\ {{\text{ for }}FFS \ge 70} \hfill \\ \end{array} } \right. $$
(12)

Equation 23-2 in the HCM is used to convert hourly volume V, which is typically in vehicles per hour, to v p , which is in passenger-car equivalents per hour per lane (pce/h/ln) and is used later on to estimate speed:

$$ \upnu_{p} = V/(PHF \times N \times f_{HV} \times f_{p} ) $$
(13)

See Table 5 for the parameter values used in this paper. Equation (3) can also be used to calculate capacity in terms of vehicles per hour for all lanes, which we call V K in this paper, by replacing V = V K and v p  = BaseCap.

We use the HCM speed-flow diagrams in Exhibit 23-3 to calculate average passenger-car speed S (min/h) as a function of the flow rate v p (pce/h/ln).

Urban arterials

The high-type unsignalized arterial analyzed in the comparison between freeways and arterials in Sect. 4 is an example of a “multilane highway” in the HCM’s terminology. The capacity and free-flow speed of this arterial are calculated using the procedures outlined in Chapters 12 and 21 of the HCM (which are very similar to the expressway calculations). However, we make the following modification to the HCM speed-flow function since the HCM function results in the high-type arterial having a higher speed at capacity than the expressway. For free-flow speeds between 55 and 60 min/h, that speed-flow function (Exhibit 21-3 of the HCM) is:

$$ S_{a} = \text{FFS} - \left[ {\left( {\frac{3}{10}\text{FFS} - 10} \right)\left( {\frac{{v_{p} - 1,400}}{28\text{FFS} - 880}} \right)^{1.31} } \right] $$
(14)

The high-type arterial’s speed at capacity (which we shall denote as \( S_{a}^{\text{cap}} \)) can be calculated from this equation by setting flow rate v p equal to capacity. Denoting the expressway’s speed at capacity as \( S_{e}^{cap} \), we then define a modified speed-flow function for the high-type arterial so that \( S_{a}^{\text{cap}} = S_{e}^{\text{cap}} \), essentially by increasing the rate at which speed falls with traffic volume. Specifically we use:

$$ \tilde{S}_{a} = \left( {\frac{{S_{a} - S_{a}^{\text{cap}} }}{{\text{FFS} - S_{a}^{\text{cap}} }}} \right)(\text{FFS} - S_{e}^{\text{cap}} ) + S_{e}^{\text{cap}} $$
(15)

where S a is given by equation (14).

For the signalized urban arterials in Sect. 3 (which the HCM calls “urban streets”; see Chapters 10, 15 and 16), we focus on high-speed principal arterials (design category 1). These arterials have speed limits of 45–55 min/h and a default free-flow speed of 50 min/h (Exhibits 10-4 and 10-5 of the HCM). Using the procedure recommended by Zegeer et al. (2008, pp. 66–73), if we assume the speed limits on the “regular” and “narrow” arterials in Sect. 3 are 55 and 45 min/h respectively, this gives us free-flow speeds of 51.5 and 46.8 min/h.

A vehicle’s travel time on an urban street (ignoring queuing due to volumes exceeding capacity, computed separately in the text) consists of running time plus “control delay” at a signalized intersection. Based on Exhibit 15-3 of the HCM, running time for an urban arterial longer than one mile is calculated as the length divided by the free-flow speed.

The formula for calculating control delay (Eq.169 in the HCM) is the sum of three components: (1) uniform control delay, which assumes uniform arrivals; (2) incremental delay, which takes into account random arrivals and oversaturated conditions (volume exceeding capacity); and (3) initial queue delay, which considers the additional time required to clear an existing initial queue left over from the previous green period.Footnote 12 Because the initial queue limits entry flow to the road’s capacity, the initial queue occurs only once at the entry to the road (prior to the first signal) since the traffic volume arriving at each intersection is never greater than the intersection’s capacity. As a result, the control delay in this paper consists only of uniform control delay and incremental delay. Using Eqs. 169, 1611 and 1612 of the HCM, the control delay at a signal is:

$$ d = \frac{{0.5C(1 - g/C)^{2} }}{{1 - \left[ {\min (1,X)(g/C)} \right]}} \cdot PF + 900T\left[ {(X - 1) + \sqrt {(X - 1)^{2} + \frac{8kIX}{cT}} } \right] $$
(16)

Table 6 provides a description of the parameters and the values used in this paper.

Table 6 Parameter values for urban arterials

The arterial’s capacity, V K, is based on the saturation flow rates of the through and shared right-turn/through lane groups, along with the fraction of time the signal is green and the proportion of traffic at each intersection that is making left turns. Saturation flow means the highest flow rate that can pass through the intersection while the light is green and is calculated based on equations 164 and 166 of the HCM. Saturation flow rates depend on the number of lanes, lane width, proportion of vehicles turning right, and other factors. For the most part, we use the default values recommended by the HCM and we assume that 7.5 % of the total traffic volume will be vehicles turning left, and similarly for vehicles turning right. Complete details are available in the online version of this Appendix (see Online Resource).

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Ng, C.F., Small, K.A. Tradeoffs among free-flow speed, capacity, cost, and environmental footprint in highway design. Transportation 39, 1259–1280 (2012). https://doi.org/10.1007/s11116-012-9395-8

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