Highway Capacity Manual Methodologies for Corridors Involving Freeways and Surface Streets (2020) / Chapter Skim
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245 A P P E N D I X C Freeway Off-Ramp – Queue Spillback Analysis 1. Introduction The HCM (Chapter 14)
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246 • Ramp node 3.3: the last node in the off-ramp represents the discharge capacity of the arterial intersection approach. The volume that flows through this node is equivalent to the amount of vehicles that are able to enter the intersection; Figure C-1 – Expanded link-node structure to evaluate the off-ramp segment The geometry of an off-ramp is seldom a homogenous road segment, and additional lanes are frequently added closer to the arterial intersection approach.
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247 The type of ramp terminal is an important input into the analysis. Signalized intersections operate in cyclical patterns, and therefore those have fluctuating queue lengths.
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248 Figure C-3 –Off-ramp spillback regimes 4. Glossary of variable definitions This glossary defines internal variables used in the methodology for off-ramp queue spillback evaluation.
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249 • OFRUV(i,t,p) : number of off-ramp unserved vehicles for segment i during time period p in time period t.
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250 • RF(i,t,p,k) : flow (pc/ts)
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251 Source: adapted from HCM 6th Edition Exhibit 25-3 Figure C-4 – Freeway facilities oversaturated segment evaluation procedure, adapted for off-ramp queue spillback evaluation
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252 Source: adapted from HCM 6th Edition Exhibit 25-3 Figure C-5 – Freeway facilities oversaturated segment evaluation procedure, adapted for off-ramp queue spillback evaluation - continued
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253 Source: adapted from HCM 6th Edition Exhibit 25-3 Figure C-6 – Freeway facilities oversaturated segment evaluation procedure, adapted for off-ramp queue spillback evaluation - continued
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254 Source: adapted from HCM 6th Edition Exhibit 25-3 Figure C-7 – Freeway facilities oversaturated segment evaluation procedure, adapted for off-ramp queue spillback evaluation - continued
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255 Step 1 - Calculate background density for unblocked lanes on each segment in the case of queue spillback The first step in the Oversaturated Segment Evaluation procedure computes a background density (KB) , for each segment at the start of each time period, defined as the expected density when there is no queueing on the segment.
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256 𝑐 = 2,400 𝑝𝑐/ℎ/𝑙𝑛 (Capacity per lane) or 𝑆𝐶 = 9,600 𝑝𝑐/ℎ (Segment capacity)
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257 The analyst should select one of these two regimes based on prevailing driver behavior at the site and in the vicinity of the site. Shoulder length The available shoulder length must be input by the analyst for queue spillback analysis, and is stored under the parameter SL(i)
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258 Step 2A - Model off-ramp geometry The three-level node structure for the off-ramp shown in Figure C-1 must be modeled to reflect the geometric characteristics of the site, as illustrated in Figure C-2. This is accomplished by setting a "branch" structure, where a node can connect to multiple links downstream.
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259 Figure C-12 – Node structure for Example 2 Example 3 – A two-lane ramp connects with a signalized intersection ramp terminal (Figure C-13)
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260 the off-ramp with a single lane change. Therefore, drivers are more likely to wait until they are closer to the exit to change lanes, blocking the adjacent through lane.
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261 Figure C-15 – Measurement of queue influence area length based on queue lengths For the timestamp tbd when congestion begins in at least one lane, the back of queue length is also known from video observations. The distance between the detector and the back of queue Q(tbd)
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262 This process was performed for all data obtained. It was observed that different locations operate at significantly different speeds prior to congestion, therefore the Queue Influence Area measurements were normalized to estimate the reaction headway, defined as the travel time between detector location (where breakdown occurred)
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263 When Regimes 3 or 4 occur and lane blockage is present in the mainline, the estimated QIA is added to the queue length to determine the extent of spillback effects. If an upstream node is located within the combined length of the queue and QIA, capacity adjustment factors must be applied to account for the spillback effects.
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264 𝑣 = ramp demand flow rate (pc/h) 𝑆 = ramp free-flow speed (mi/h)
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265 one oversaturated movement may extend upstream and block the throughput of all movements at the offramp. ISTG is estimated as: 𝐼𝑆𝑇𝐺(𝑖,𝑝, 𝑘)
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266 Signalized 31-149 TWSC 20-68 AWSC 21-33 Roundabout 22-20 At signalized intersections, due to their cyclic nature, queues form and discharge at different times for different movements. Therefore, a reference point within the cycle must be selected as a starting point in the methodology.
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267 Figure C-22 – Sample signalized intersection approach from an off-ramp Input Parameters The required parameters to evaluate the capacity of a ramp terminal capacity are generally the same required for standard signalized intersection analyses, as listed in Exhibit 19-11. Arrival type: Chapter 19 of the HCM (Exhibit 19-14)
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268 methodology. Therefore, an adjustment is necessary to calculate the capacities of each movement in 15second intervals.
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269 Merge segments (freeway-to-freeway connectors) When two freeway facilities are connected through a ramp junction, the merge segment at the downstream facility becomes the ramp terminal.
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270 Step 9A - Perform spillback analysis This is a new step in the Freeway Facilities Analysis method (Figure C-4)
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273 Next, the mainline queue length, SBLQ, is compared to the available spillback queue storage for the prevalent spillback regime for the given time step, as follows: If OFRLQ = 0 → Regime 0 If 0 < OFRLQ ≤ LD → Regime 1 If SBLQ > LD : If SL(i,p)
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274 Figure C-25 – Procedure for evaluating the impact of queue spillback on upstream nodes and determination of the queue length within upstream segments When queue spillback occurs in a downstream off-ramp, the length of the mainline queue measured from the start of the deceleration lane is known from the previous step. If a given segment has any queues blocking one or more lanes, three possible scenarios may occur at the node (Figure C-26)
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275 Figure C-26 – Illustration of different impacts of an off-ramp queue at node i: (a) lane blockage, (b)
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277 𝑝 = 𝑝 , + 1𝑁 − 𝑝 ,𝑅 × (𝑑 − 1,500) 6500 (Equation C- 32)
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278 The Oversaturated Segment Evaluation procedure computes the Mainline Input (MI) for each node, in every time step.
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279 Figure C-30 – Impact of a queue spillback on the discharge capacity of an upstream on-ramp If one or more lanes are blocked due to a downstream off-ramp bottleneck, the throughput in Lane 1 will be equal to the maximum exit throughput in the congested off-ramp if the site operates in Regime 3, or 50% of the maximum exit throughput in the off-ramp, if it operates in Regime 4. It is assumed that the on-ramp and the flow arriving from the upstream on Lane 1 contribute equally to the downstream Lane 1 flow, and thus the on-ramp maximum output, in this case, is assumed to be half of the downstream throughput in Lane 1.
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281 Step 22 - Calculate mainline flow The Oversaturated Segment Evaluation procedure computes the Mainline Flow through a subject node as the minimum of several variables, as presented in HCM Equation 25-16. If the node experiences spillback, the calculation of Mainline Flow must consider the flow through both the blocked and the unblocked portions of the node.
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282 Similarly, the aggregated off-ramp ramp is aggregated at a 15-min time period: 𝑂𝐹𝑅𝐹(𝑖,𝑝)
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283 Case Study: Evaluating Queue Spillback on a Freeway-to-Freeway connector This case study illustrates the application of the off-ramp spillback methodology to evaluate a network comprised of two freeway facilities (I-75 SB to SR-826 SB, Miami, Florida) , as shown in Figure C-32.
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284 Figure C-33 – Individual freeway facilities: (a)
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285 • Deceleration lane length: 700 ft; • Number of ramp lanes: 2; and • Familiar facility users. Performance measures - individual facilities The performance measures for both freeway facilities, if analyzed independently, are presented in Table C-7 and Table C-8.
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286 Table C-9. Estimation of queue length and storage ratio at the SR-826 on-ramp Time period Total number of queued vehicles Number of queued vehicles in each lane Average vehicle spacing (ft)
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287 The unblocked background density KBUB is calculated next. For time period 2, an expected demand of 4165.8 pc/h for the mainline is used in the calculations.
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288 𝑅𝑁𝑉(3,0,2,1) = 37.4 × 35885280 × 2 = 50.8 𝑝𝑐 Step 2G - Determine the capacity of the downstream terminal The capacity of the merge is obtained by analyzing the downstream freeway facility using the oversaturated segment evaluation procedure and aggregating the parameter ONRO for an hourly flow rate.
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289 Figure C-36 – Ramp capacity and ramp inputs – time period 2 Since spillback does not occur, no additional calculations for the mainline are required. Step 30 - Calculate segment performance measures Since spillback does not occur during this time period, the performance measures for the mainline do not need to be recalculated.
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290 Figure C-37 – Ramp capacities and ramp inputs – time period 3 After the onset of queue spillback, the number of unserved vehicles at the exit is computed every time step through the parameter OFRUV(i,t,p)
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291 The parameter OFRLQ represents the length of the queue if all unserved vehicles were queued in a single line. Given the segment geometry (Figure C-39)
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