The Highway Capacity Manual: A Conceptual and Research History

Rural highway capacity, level of service, and other planning criteria are based on outdated information from the United States where the operating environment and traffic conditions are often quite different from those in Canada. Much of the information on rural two-lane highway overtaking and capacity in the 1965 Highway Capacity Manual (HCM) can be traced to data collected as long ago as 1938. Rural two-lane highway capacity and overtaking concepts in use today have remained essentially unchanged since they first appeared in the 1950 Highway Capacity Manual.This paper presents the findings of an investigation into speed–volume relations, platooning, and overtaking on the primary two-lane rural highway system in Alberta, British Columbia, and the National Parks.The principal findings are: (i) there is little relation between speed and volume over the range of volume observed — up to 1700 vehicles per hour, (ii) the average speed at 1000 vph was found to be 20–25 km/h higher than that predicted in the HCM, (iii) the backward bending portion of the speed–volume curve was not observed, (iv) speed distributions at flow rates of 1200 vph showed a marked increase in speed over that in the HCM, and (v) speed distributions of free-moving vehicles indicate a higher proportion of vehicles travelling at uniform speed.The implication of the findings is that the level of service on two-lane rural highways is much higher than that given in the HCM. This, however, is not the case on most of the primary two-lane highway system in western Canada. Despite low volumes, in the 2500–5000 average daily traffic range, drivers perceive a low level of service. This is attributed to a high proportion of long distance (over 300 km), high-speed trips, in rolling terrain with restricted sight distances, through sparsely developed territory with few intermediate stops. Thus motorists spend most of their journey travelling in high-speed platoons resulting in a high driver workload and a propensity to take risks when overtaking.The paper concludes with a recommendation that a nation-wide effort be mounted to collect speed–volume, headway, platooning, and passing data over the full range of highway operating conditions on a year-round basis. A second recommendation is that provincial highway departments in Canada investigate the concept of platooning and opportunity to overtake for evaluating their two-lane highways. More attention should be given to the education and testing of drivers in the skills of overtaking on rural highways. Also proposed is an evaluation of currently accepted, safe passing sight distances, which may be inadequate for the current operating conditions and traffic mix. Alternatives to four lanes, such as alternating passing lanes with early warning signs (to inform the driver of overtaking opportunities a specified distance ahead in order to reduce driver frustration and prevent dangerous passes), need evaluation as well. The paper concludes with a comment on the possible impact of lower speed limits and vehicle control devices, such as the cruise control, on platooning, overtaking, and level-of-service measurement.

With nearly nine million lane-miles of public roadway and an economy driven by the automobile, interruptions to normal traffic operations for construction and maintenance are inevitable in the U.S.A., but the substantial safety and mobility impacts associated with queueing at freeway lane closures are mitigable. The current freeway work zone capacity methodology in the 6th edition of the Highway Capacity Manual is a vast improvement over historical guidance but still approaches the issue differently than research suggests agencies and practitioners should. Namely, a capacity defined by the mean queue discharge rate is deterministic and fails to account for the stochastic nature of traffic flow and breakdown. These core issues were addressed in this research by developing a methodology for obtaining probabilistic estimates of rural freeway work zone capacity from simulated data in PTV Vissim. Results for a two-to-one lane closure were presented as a series of breakdown probability distributions to demonstrate the viability of this methodology. The data indicated that the impact of trucks on freeway capacity is exacerbated in the presence of lane closures and led to the development of work zone capacity-based passenger car equivalents. Such a procedure may be extended to freeway facilities exhibiting different geometric, traffic, and environmental characteristics and utilized by agencies to make data-driven, risk tolerance-based planning, design, and operations decisions at freeway work zones.

Effect of traffic composition on capacity of multilane highways

The present study illustrates the effectiveness of utilizing VISSIM software in evaluating the capacity of urban multi-lane highways under varied traffic conditions. Traffic flow and speed data from a section of Ratna Rajmarga's four-lane divided highway were used to establish a speed-flow relationship. This relationship was utilized to ascertain the field capacity. Subsequently, this data was inputted into VISSIM to generate a simulated speed-flow curve, which was then compared with the actual field curve. Results revealed that the original VISSIM model tends to overestimate both speed and capacity of the highway using default parameters. Previous research has highlighted standstill distance (CC0) and headway time (CC1) as significant influencing parameters in establishing the relationship between speed and volume. Therefore, in this study, these parameters were calibrated for an urban four-lane divided road. Initial assessments of CC0 and CC1 were carried out under homogeneous traffic conditions, focusing solely on one of the five vehicle types present for all vehicles. These findings were amalgamated to determine these parameters for a more representative mixed traffic scenario. Upon recalibrating the field data using the adjusted CC0 and CC1 values, the simulation-generated curve approached closer to the reliable limit for comparison with the field data curve. Consequently, it was utilized to determine the capacity, which was found to be less than 1 percent in comparison with the capacity determined by field data.

Highway capacity through vissim calibrated for mixed traffic conditions

Annotation: The study presents the results of the research of the impact of traffic intensity and traffic flow composition on the capacity of highways and bridge crossings based on mathematical and numerical modeling methods. The main factors affecting the capacity of highways and bridge crossings have been identified. The methodology for determining the level of traffic and capacity of highways approved by the State Service of Highways (now the Restoration Agency) was adopted as the main calculation basis for numerical modeling. Also, for calculations, updated statistical data, given in open literary sources, were used. 11 test options with different composition of the traffic flow were considered: from 0% to 100% of the share of passenger cars in the composition of the traffic flow. The average speed of the traffic flow was determined depending on the geometric parameters of the road - the radii of the horizontal curves in the plan and the longitudinal slope of the carriageway. It is shown that the average speed of the traffic flow increases with an increase in the value of the radius of the horizontal curve and with a decrease in the value of the longitudinal slope of the carriageway of the road, which is due to the improvement of traffic safety conditions and the possibility of moving vehicles at higher speeds. Also, the results of the numerical modeling showed an increase in the average speed of the traffic flow with an improvement in the level of coverage of the road (bridge crossing). It is shown that an increase in the share of cars in the traffic flow leads to an increase in the average speed of the entire traffic flow, which is explained by their more "compact" dimensions, compared to trucks, buses and road trains. The smallest practical carrying capacity of a highway or bridge crossing corresponds to a column of cars at the speed of free movement. The highest practical throughput corresponds to the traffic intensity at the minimum interval (optimal speed). Also, with an increase in the traffic flow of trucks and large-sized vehicles, the capacity of the road decreases. This determines the relevance of research in the direction of developing load models based on the actual parameters of heavy-duty rolling stock when determining the load-carrying capacity of highways and overpasses. Key words: highway, bridge crossing, throughput, mathematical modeling.

The following sections are included:IntroductionTheoryAverage cost pricing and marginal cost pricing under fixed highway capacityOptimal highway capacity building through social marginal cost pricingCase 1: More Effective Use of Roads by Discounting TollsTraffic equilibrium modelSimulation resultsShift of equilibrium point through a toll discountEffects of toll discount in different degrees of congestionSummaryCase 2: Optimal Highway Capacity Building Through Mile-Based PricingSimulation frameworkRevenue calculation in the simulation modelExpenditure calculation in the simulation modelSimulation resultsExpanding highway capacity through mile-based pricingSummaryConclusionsAcknowledgmentsReferences

Several automobile manufacturers are offering assisted driving systems that use sensors to automatically brake automobiles to avoid collisions. Before extensively deploying these systems, we should determine how they will affect highway capacity. The goal of this paper is to compare the highway capacity when using sensors alone and when using sensors and vehicle-to-vehicle communication. To achieve this goal, the rules for using both technologies to prevent collisions are proposed, and highway capacity is estimated based on these rules. We show that both technologies can increase highway capacity. The increase in capacity is a function of the fraction of the vehicles that use a technology. If all of the vehicles use sensors alone, the increase in highway capacity is about 43%. While if all of the vehicles use both sensors and vehicle-to-vehicle communication, the increase is about 273%.

We study the morning commute problem with a heterogeneous travelling population whose early/late arrival penalty parameters are continuously distributed. Following Arnott et al.'s (1988) [Schedule delay and departure time decisions with heterogeneous commuters, Transportation Research Record, 1197, 56–67] model, where the ratio of the value of early schedule delay (VESD) over the value of late schedule delay (VLSD) is assumed to be constant across the population, we first derive the user-optimal travel profiles and the corresponding total travel time (TTT) for a one-to-one network with a single route. We show that although every commuter is better off if the bottleneck capacity is enlarged, commuters with high values of early arrival penalty (EAP) benefit more than those with low values. In addition, the homogeneity assumption overestimates the queuing delay and thus the TTT. Then we extend our analysis to a network with two routes, a freeway and an arterial road (AR) connecting a single origin–destination (O–D) pair. In this case, we find that the travellers who weigh schedule delay more will first shift to the AR, prompted by an increase in total demand. However, the critical travel demand at which travellers start to use the AR remains the same if the common EAP for homogeneous users is equal to the expected value of EAP distribution for heterogeneous users. Interestingly, there exists a critical value of EAP parameter, such that all the travellers whose EAP is less than it choose the freeway, and those whose EAP is larger than it choose the AR. Sensitivity analysis on TTT is performed with respect to freeway capacity, AR capacity and free-flow travel time on the AR. The results indicate that enlarging freeway (AR) capacity will always reduce the TTT of the whole network and the TTT of the AR (freeway), and increase the demand share of the freeway (AR). We also show that every commuter is better off if either the freeway capacity or the AR capacity is enlarged. Finally, we provide numerical examples to demonstrate the considerable differences in flow patterns and network performances between a homogeneous and a heterogeneous population.

There is a widely-held view that as demand for travel goes up, this decreases not only speed but also the capacity of the road system, a phenomenon known as hypercongestion. We revisit this idea. We propose two empirical tests motivated by previous analytical models of hypercongestion. Our first test uses instrumental variables to empirically isolate the effect of travel demand on highway capacity. Our second test uses an event study analysis to measure changes in highway capacity at the onset of queue formation. We apply these tests to three highway bottlenecks in California for which detailed data on traffic flows and vehicles speeds are available. Neither test shows evidence of a reduction in highway capacity at any site during periods of high demand. Across sites and specifications we have sufficient statistical power to rule out small reductions in highway capacity. This lack of evidence of hypercongestion has important implications for travel supply and demand models and raises questions about highway metering lights and other traffic interventions aimed at regulating demand.

Highway capacity is an essential element in highway planning and traffic management. There are a number of methods developed to estimate highway capacity. Most of them focus on identifying the maximum flow or throughput using a traffic speed-flow model. However, it has been found that these capacity estimates are not practical as they cannot be sustained for long, under normal flow conditions. This research mainly focuses on using the breakdown probability approach, in capacity estimation methods which are currently used to estimate the capacity mainly for freeways. Breakdown probability methods such as the Product Limit Method (PLM), the Sustained Flow Index (SFI), the Highway Capacity Manual (HCM) method are used to check the applicability of the breakdown probability approach in calculating highway capacity under heterogeneous conditions. These breakdown probability methods were applied for data collected from two multilane highway locations where heterogeneous flow conditions were observed. The capacity values obtained through the breakdown probability approach were compared with the capacity values obtained from the Greenberg model which is the considered conventional method. The breakdown approach resulted in capacity values which are less by an overall range of 7.4% to 30.9% for both locations.

This paper attempts to investigate the impact of the number of lanes on highway capacity. Methodologically, we provide a better understanding of the relationship between highway capacity and its number of lanes upon the statistical analysis of the survey. The empirical research is validated upon the extensive field survey of traffic flow in Beijing and Shanghai. The findings show that average capacity per lane decreases significantly as the number of lanes increases. Moreover, it indicated that the increase of lane-changing activity and its associated disturbance to traffic stream is the principal factor of the decrease of average capacity per lane on highways. The implication of the marginal decrease requires that the manuals of highway capacity should be revised for the better plan and design of road network. In addition, the factor of the decrease should be incorporated into the decision on adding lanes or constructing a new parallel road when travel demand exceeds road capacity.

Three-phase traffic theory and highway capacity

The publication of the “fourth” full edition of the Highway Capacity Manual (HCM) in the fall of 2000 represented a major step forward in state-of-the-art highway capacity and quality-of-service analyses. Even as this major step is taken, however, old issues reemerge and new ones arise as to the core concepts involved, the directions that such analyses should take in the future, and the needs of HCM users. Now that HCM has begun to address system and multimodal measures, the nature and meaning of capacity and level-of-service concepts need to be reexamined. The role of simulation must be more clearly defined, as must the limitations of more conventional highway capacity analyses. As databases improve, the question of statistical accuracy and stochastic variations in standard measures may seem more important, even though the inherent variability in traffic flow characteristics remains essentially unchanged. The need for software to implement ever more complex methodologies raises additional issues. As the Committee on Highway Capacity and Quality of Service and its members consider these and other important issues, an attempt to outline the major issues and alternatives that should be examined is made. In addition, some suggestions as to potential paths to follow are provided.

The majority of roads in most countries are two-lane highways. These lanes quickly reach their capacity and must be upgraded on a regular basis. To do so, we must first determine the capacity of the street. The primary objective of this study was to determine the effect of carriageway width, the radius of the horizontal curve, and gradients on Passenger Car Unit (PCU) values as well as on capacity of two-lane undivided Highways, and more importantly, to develop a multiple linear regression model to determine the capacity of the highway when all of these factors are present, which has not been previously reported. Green shield’s model was used to estimate the capacity of each element for all thirty-six sections using flow and speed data. Different models were built using regression analysis to estimate capacity independently, and the combined model was developed as a result. It has been noted that with proportionate increases in carriageway width and radius of the curve, there is an equivalent rise in PCU values and highway capacity, providing improved comfort and safety to road users. It was also discovered that when the value of the gradient increases cause increase in PCU values but the highway capacity decreases, thereby increasing the vehicle operating cost. Where all of these characteristics are present simultaneously in a section, the resulting multiple linear regression model was proven to be appropriate. It is believed to be valuable to practitioners as well as in the development or revision of Indian highway capacity manuals.