Fred L. Hall

EMPIRICAL ANALYSIS OF FREEWAY FLOW-DENSITY RELATIONSHIPS

Abstract Many researchers have reported on the occurence of gaps in freeway speed-density and flow-density data and have suggested that discontinuous functions are necessary to properly describe “observed” traffic behavior. This paper investigates the flow-occupancy (spot-density) relationship using an extensive data set collected on the Queen Elizabeth Way in Ontario. Daily time-traced plots of 5-minute average flow rates versus occupancy were analyzed. Results indicate that there is another interpretation of gaps in data, which does not imply a discontinuous function, but rather, an inverted V shape (continuous, but not continuously differentiable). Three conclusions were reached: (a) it is essential to provide details of data collection locations if one is to know whether a particular pattern in resulting data represents a “true” relationship, or just the specifics of a particular place; (b) there are clear advantages to examining daily time traces of traffic behavior, rather than relying on scatter diagrams of numerous days of accumulated data; and, (c) previously documented arguments for a discontinuous flow-occupancy relationship do not seem convincing, because knowledge of daily operations at a particular location could easily explain the occurence of gaps in the data.

ANALYSIS OF BICYCLE COMMUTER ROUTES USING GEOGRAPHIC INFORMATION SYSTEMS: IMPLICATIONS FOR BICYCLE PLANNING

A geographic information system (GIS) network data base is used to determine the characteristics of 397 routes used by commuter cyclists in Guelph, Ontario, Canada, and to compare them with the shortest-path routes between each origin and destination. The analysis of route data provides useful insight for understanding factors affecting travel behavior and in this case provides quantitative support for many existing assumptions regarding commuter cyclist behavior. Most commuters divert very little from their minimum path (0.4 km on average) and are found to use major road routes. The cyclists tend to avoid grades, grade-separated railway crossings, and high-activity areas, but not road (as opposed to pedestrian) bridges. Cyclists use traffic signals especially for crossing major roadways and turning. The high-quality direct off-road paths are used only infrequently by the commuter cyclists and the lower quality ones even less. The results of this analysis suggest that efforts to accommodate current commuter cyclists should be focused on improving cycling conditions on the road network, such as providing wider curb lanes, or actuated traffic signal detectors that recognize the presence of bicycles. If potential new commuters are similar to the minority of current commuter cyclists in this study who use mainly local roads, paths or trails, then projects that make the network of local roads and pathways more connective and direct may encourage a higher level of commuter cycling.

Catastrophe theory and patterns in 30-second freeway traffic data— Implications for incident detection

This paper analyses 30-second data on flows, occupancies, and average speeds of freeway operations near bottlenecks caused by incidents. These data are seen to be very poorly explained by the conventional traffic flow theory, but to accord quite well with a recently proposed model based on catastrophe theory. One of the key areas in which the catastrophe theory model fits the data better than conventional models is with regard to the transitions to and from congested operation upstream of incidents. The data suggest that such transitions are characterized by a fairly gentle change in occupancy, and a fairly constant flow, but a sudden, sharp, change in speed. This relatively smooth transition in occupancy, which could not be investigated with earlier data, lends additional support to the catastrophe theory model. On the strength of these results, the outline of an alternative logic, based on the catastrophe theory model of the flow-occupancy-speed pattern, is suggested for freeway incident detection.

Ottawa-Carleton commuter cyclist on- and off-road incident rates.

This analysis overcomes the known limitations of police and emergency room bicycle accident databases through use of a survey that asked cyclists to indicate their accident history as well as their regular commute route to work or school. By relating the route information of the 1604 respondents (52.5% of the distributed questionnaires) to facility attributes in a Geographic Information System, defensible estimates of travel exposure on roads, off-road paths and sidewalks were developed. The relative rates of collisions on the three different facility types were not statistically different from 1.0. The relative rates for falls and injuries suggest it is safest to cycle on-road followed by off-road paths and trails, and finally least safe on sidewalks. While there were no major injuries reported on sidewalks, the relative rate for these events on paths was greater than the rate for roads. The absolute event rates per bicycle kilometre were found to be between 10 and 41 times higher than similar rates for automobile travel. Results suggest a need to discourage sidewalk cycling, and to further investigate the safety of off-road paths/trails. The analysis also demonstrates the need for bicycle travel exposure information and the use of more than just collision databases for bicycle safety analysis.

AN INTERPRETATION OF SPEED-FLOW-CONCENTRATION RELATIONSHIPS USING CATASTROPHE THEORY

Abstract The occurence of gaps in freeway operations data, for example in flow-concentration plots, and the accompanying jumps in the behavior of some of the variables, have been observed in many data sets. Conventional representations of speed-flow-concentration relationships do not address those jumps, much less explain why the jumps occur at different values of the variables in different data sets. Catastrophe theory provides a way to understand that behavior. In particular, the cusp catastrophe replicates quite well the functions derived from data collected on the Queen Elizabeth Way in Ontario. Simple linear transformations between traffic operations variables and catastrophe theory variables are shown to provide a feasible explanation for the occurrence of these jumps. Although the theory does not lead to a single unique solution, it provides fresh insight into the operation of freeways, and suggests several avenues for further research.

Developing passenger car equivalents for heavy vehicles on freeways during queue discharge flow

This paper investigates the hypothesis that the effect of heavy vehicles on traffic is greater during congestion than during undersaturated conditions. A new approach was developed to quantify this effect by deriving passenger car equivalents (PCEs) using queue discharge flow (QDF) capacity as the equivalency criterion. This approach is based on the premise that QDF capacity observations can be expected to show minimal variation if traffic stream was uniform and consisted of passenger cars only. Two sites in Ontario, Canada were used for this research. The first is located at an entrance ramp merge area and the second at a long-term freeway reconstruction zone. Nonlinear programming was utilized to perform optimizations on a number of data sets at each site. Results strongly suggest that the research hypothesis is true and that the approach developed by this research is both plausible and feasible. The mean PCE factor at the first site was 2.36 versus 1.5 in the Highway Capacity Manual (HCM) 2000. At the second site, the mean PCE factors in the two directions of travel were 3.21 and 2.7 versus 2.0 in the HCM 2000. Results also showed that the PCE factor developed from the optimization runs behaves as a random variable that generally follows the normal distribution. Furthermore, the PCE factor was neither a function of weather conditions nor of roadside maintenance work.

Direct comparison of community response to road traffic noise and to aircraft noise

Previous efforts to synthesize information on community responses to various noise sources have been forced to rely on a variety of surveys conducted in different countries over a number of years. Comparability of both the noise measurements and the questions asked has been limited, and has of necessity relied on professional judgment. Data collected recently around Toronto International Airport provide a direct comparison of response to two sources, based on 673 interviews of persons exposed to a variety of levels of both aircraft and road traffic noise. The results of that analysis do not support the assumption that response to these two noise sources is the same. For the same value of Ldn, a greater percentage of the sample is highly annoyed by aircraft noise than by road traffic noise. Possible reasons for this contradiction of the results of a previous synthesis of noise surveys are discussed.

Freeway Quality of Service: What Really Matters to Drivers and Passengers?

Although the concept of level of service for freeways is usually defined in terms of users’ perceptions, very few studies have sought drivers’ or passengers’ views about what is important to them. Such information is particularly important for the evaluation of extended trips on freeways as opposed to trips on a single section or segment. Such information is valuable not only for improving the Highway Capacity Manual but also for establishing appropriate criteria for assessment of intelligent transportation system proposals. The results of focus group sessions are reported in which a group of commuters discussed their views about determinants of the freeway quality of service that they experienced. Total travel time is the most important determinant for them, but a number of other aspects of the trip also matter, including safety, traveler information, and maneuverability (density). The importance of travel time is a reminder that travel is a derived demand, not something that commuters do for the pleasure of the drive.

The applicability of catastrophe theory in modelling freeway traffic operations

Abstract A freeway operations model based on catastrophe theory has recently been proposed. The model has not yet been fully developed, but has been advanced to a functional form which appears very promising. To date, the number of data sets which have been used to verify the models applicability has been small. This paper analyses some new data with respect to the essential properties of catastrophe theory, and with respect to some of the decisions made in the models initial development. The catastrophe theory model continues to show promise, but requires some rethinking to ensure accurate replication of freeway operations data.

Activity interference and noise annoyance

Abstract Debate continues over differences in the dose-response functions used to predict the annoyance at different sources of transportation noise. This debate reflects the lack of an accepted model of noise annoyance in residential communities. In this paper a model is proposed which is focussed on activity interference as a central component mediating the relationship between noise exposure and annoyance. This model represents a departure from earlier models in two important respects. First, single event noise levels (e.g., maximum levels, sound exposure level) constitute the noise exposure variables in place of long-term energy equivalent measures (e.g., 24-hour Leq or Ldn). Second, the relationships within the model are expressed as probabilistic rather than deterministic equations. The model has been tested by using acoustical and social survey data collected at 57 sites in the Toronto region exposed to aircraft, road traffic or train noise. Logit analysis was used to estimate two sets of equations. The first predicts the probability of activity interference as a function of event noise level. Four types of interference are included: indoor speech, outdoor speech, difficulty getting to sleep and awakening. The second set predicts the probability of annoyance as a function of the combination of activity interferences. From the first set of equations, it was possible to estimate a function for indoor speech interference only. In this case, the maximum event level was the strongest predictor. The lack of significant results for the other types of interference is explained by the limitations of the data. The same function predicts indoor speech interference for all three sources—road, rail and aircraft noise. The results for the second set of equations show strong relationships between activity interference and the probability of annoyance. Again, the parameters of the logit equations are similar for the three sources. A trial application of the model predicts a higher probability of annoyance for aircraft than for road traffic situations with the same 24-hour Leq. This result suggests that the model may account for previously reported source differences in annoyance.