Semisequicentennial Transportation Conference Proceedings
May 1996, Iowa State University, Ames, Iowa

Preliminary Data Collection and Analysis for Traffic Flow Management on a Freeway Corridor

Lonnie E. Haefner, Ming-Shiun Li, and Luis A. Porrello

Department of Civil Engineering,
Campus Box 1130,
One Brookings Drive,
Washington University,
St. Louis, Missouri 63130.

This paper summarizes the major research efforts and findings with respect to a study of traffic flow behavior of a segment of freeway corridor. The objective of this initial effort is to develop a traffic flow database, which will be useful to the development of congestion mitigation and management techniques for the study segment. A data collection procedure and routine was developed for the collection of various information relevant to traffic flow behavior. The average moving car technique was used for collecting data such as travel time, average speed, delay and stop, acceleration noise, and occurrences of shock and incidences. Traffic counters were installed in selected locations to gather volume, speed, and density information. Data were transferred into various charts and tables to illustrate the operation of the freeway corridor. The graphical presentations generated for the study include series of travel time and speed profiles, acceleration noise, volume profiles, and speed-volume, volume-density, and speed-density charts. The critical areas along the study segment of the freeway corridor were identified through careful interpretation of the charts and tables, and potential solutions were suggested for further research.

This paper is a synopsis of major research efforts and findings with respect to a study of traffic flow behavior of a segment of a freeway corridor. The long-term objective of the research is to develop congestion mitigation and management techniques for the study segment. The specific objective of this initial effort is to develop a traffic flow database for the above segment.


This section briefly presents major fundamental and emerging literature sources relevant to the study. The topics of travel time, speed and delay studies, acceleration noise analysis, and basic traffic flow theory are presented as a basis for the data collection and analysis efforts of further sections.

Travel Time - Delay

Travel time and delay data are typically collected using test-car runs along the section of freeway in question. Test-car runs may be done by several techniques, including the floating car, average car, and maximum car techniques (1,2,3). In the floating car technique, the driver is instructed to pass as many vehicles as pass his/her vehicle. In the average car technique, the driver is simply instructed to travel according to his or her best judgment of the traffic stream's speed. Last, in the maximum car technique, the driver is instructed to travel at the posted speed limit unless impeded by traffic. The average car technique was chosen for the study because it provides data which represent the most likely scenario.

Acceleration Noise

Acceleration noise can be considered as the disturbance of the vehicle's speed from that of a uniform speed and can be identified as a measurement of the smoothness of traffic flow. Acceleration noise is dependent upon the three basic elements of the traffic stream, namely, the driver, the road, and the traffic condition. The importance and background of acceleration noise has been the topic of numerous works (4,5,6).

Speed-Volume-Density Relationships

The relationship between volume (q) and density (k) is called the fundamental diagram for traffic, or the q-k curve. Empirical studies show that as the density rises the flow first of all increases and reaches a maximum and then apparently falls, but there is some conflicting evidence regarding the exact shape of the curve (4,7,8). The shape and calibration of such relationship are important, because they provide the basis for the selection of measures of effectiveness and the definition of level-of-service ranges for freeway segments.

Historically, speed (u) and volume (q) have been major measurements in level-of-service analysis. The 1994 Highway Capacity Manual (HCM) (9) shows that speeds remain very close to free-flow speeds until volumes increase to 1300 pcphpl or greater, and speeds at capacity are only 5 to 10 mph lower than the free-flow speeds. Because speed is nearly constant over a wide range of flow rates, speed may not be an adequate measure of performance for level of service determination (10,11). In the 1994 HCM, the parameter used to define levels of service for the basic freeway sections is density. Density increases throughout the range of volumes from zero to capacity, resulting in a measure of effectiveness that is sensitive to flow throughout the range of useful values. This suggests the critical importance of the study of volume-density relationships in order to understand the characteristics of traffic flow and to further model and control the freeway traffic stream.


Description of Study Area

The study area is comprised of the eastbound and westbound sections of Corridor I-64-40 between Kingshighway Boulevard on the east and McKnight Road on the west. This segment (Figure 1) includes the interchanges at Kingshighway, Hampton, Clayton-Skinker, Oakland, McCausland, Bellevue, Big Bend, Laclede, Hanley, and I-170-Brentwood and McKnight Road. The total length of the section is approximately 5.4 miles.

Travel Time and Delay Study

Preliminary runs over the section yielded six "checkpoints" which served as origin and destination points in the study. These points were selected after initial surveillance illustrated that they provided bounds for areas of congestion. The procedure for data collection was designed to account for both delay as time spent less than 5 mph and for the number of instances when a full stop was reached. The total number of travel time and delay runs amounted to 1,246 trips in 62 days. This surveillance totaled over 6,728 miles and over 300 hours of observation.

Acceleration Noise Study

The Missouri Highway and Transportation Department provided the research staff with a vehicle equipped with an accelerometer. Once a week, the staff used this vehicle and a laptop computer to monitor the acceleration fluctuations during multiple runs. This resulted in 192 trips which totaled over 1,036 miles of surveillance, and which provided the research staff with over 1,500 data points.

Traffic Volume, Speed, and Density

The traffic volumes were collected through two types of counters. The traffic counters/classifiers (or density counters) collected data such as volume, speed, headway, vehicle classification, and surface temperature and condition in a 5-minute interval. They collected information for every individual lane on the freeway (or the ramp) for twenty-one hours a day. The major objective of using the density counters is to collect traffic data which can reflect the freeway operations under both steady and unsteady traffic streams. By referring to the results of travel time-delay field studies and acceleration noise analysis, five locations were selected to match the occurrences of shock waves, queues, and delay phenomena. This counting effort totaled 12 individual lanes for 32 days.

The data collected from the density counters were translated into series of u-q, q-k, and u-k curves. In addition, several parallel studies were undertaken, including the studies of traffic volumes corresponding to time of day and day of week, volume distribution by lane, percentages of heavy vehicles, and the impact of special events.

The second type of counters are the tube counters. They were used to collect volumes of the ramps with heavier traffic and greater impacts on freeway operations within the study area. Twenty-nine ramps were selected and each location was counted for 6 days in a 15-minute interval.

The collection of ramp volumes provided opportunities to identify the traffic patterns of ramps and to integrate ramp volumes with freeway volumes. The ramp and freeway volumes were integrated in every 15-minute interval for the entire study area, which formed an important database for the level-of-service study and for identification and understanding of the dynamics of the freeway operations.


The results presented herein are organized in the following manner. First, the travel time and delay study. Second, the acceleration noise profiles by hourly period, direction, and peak. Third, the volume profiles and level-of-service studies, and finally, fourth, the volume, speed, and density relationships.

Travel Time and Delay Study

The travel time and delay study data were grouped into averages for each 15-minute interval of the A.M. and P.M. peak hours. A series of charts were developed to depict relationships among the traffic stream variables: (1) Average speed per section by day of week; (2) Average cumulative travel time per section by day of week; (3) Average delay and stops by day of week; and (4) Average speed for entire study area vs. time by day of week.

Average Speed

During the morning rush in the eastbound direction, it is evident that (1) the sections of McKnight-Brentwood, Brentwood-Hanley, and Hanley-Oakland (refer to Figure 1) were the sources of the largest changes in average speed, and (2) the most crucial time

period was between 7:30 and 8:00 when the above three sections experienced the lowest average speeds. During the westbound morning rush, the average travel speed remained above 47 mph in all sections except for the periods of 7:30-7:45 and 7:45-8:00, when the average speeds for the Oakland-Hanley sections fell to approximately 35 mph. Interestingly, this 30 minute period also contained the lowest average speeds for the opposite (eastbound) direction. This apparent instance of reverse commuting, the data shows, is true for both peaks and for every day.

During the 5:15-5:30 interval for the eastbound afternoon peak, travel speeds in the Brentwood-Hanley section fell below 47 mph. After climbing back to acceptable levels in the 5:30-5:45 period; speeds in the Brentwood-Hanley section fell to a more crucial 25 mph during the 5:45-6:00 interval. For the westbound afternoon during the 3:30-3:45 and 3:45-4:00 intervals, the Hampton-

Oakland section fell below 47 mph and the Oakland-Hanley section approached 30 mph. The Hampton-Oakland section further fell to approximately 40 mph during the 4:15-4:30 time period. The next sudden drop in travel speeds occurred during the 5:30-5:45 time period when the Oakland-Hanley and Brentwood-McKnight sections experienced speeds below 30 mph. The other three sections averaged speeds which fell between 47 mph and 30 mph. Last, during the 5:45-6:00 interval, the Kingshighway-

Hampton and Hanley-Brentwood sections climbed above 47 mph, while the other three sections remained between 47 mph and 30 mph.

It can be concluded that during the afternoon peak in the westbound direction the heaviest congestion, in terms of average section travel speed, occurred between 4:45 and 5:45, when these speeds remained, for the most part, close to 30 mph. In addition, the data showed the Oakland-Hanley and Brentwood-McKnight sections experienced the lowest average speeds of the study area during this critical period.

Weekday Comparison of Average Speed

For the eastbound morning peak, it was found that on Friday the average speed was generally higher than any other day of the week. The remaining days followed similar average speed trends along a band between 40 and 55 mph. For the westbound morning peak, there wasn't any single weekday when the average speed was significantly different from other days. The trend was quite uniform along a band between 47 and 57 mph. During the afternoon peak for both eastbound and westbound directions, the Monday average speed was generally higher than other days, especially after 4:30. For the same time period, the average speed for Wednesday was generally lower than during other weekdays.

Cumulative Travel Time

Two conclusions result from the study in the eastbound morning peak: (1) The interval when the longest cumulative travel time was experienced, as expected from the average speed analysis, was 7:45-8:00; and (2) The interval when the shortest cumulative travel time was experienced was 8:45-9:00. It is important to note that while maintaining a free flow speed the study area can be traveled in approximately 5 minutes and 52 seconds. The times took to travel the 7:45-8:00 and 8:45-9:00 periods were approximately 9 minutes and 22 seconds, and 5 minutes and 52 seconds respectively. In the westbound direction, the morning peak cumulative travel time jumped abruptly during the 7:30-7:45 and 7:45-8:00 intervals. This is an expected result if we consider that the lowest values of travel speed occurred during this time period. The 7:30-7:45 period (worst case) was traversed in 7 minutes and 39 seconds.

During the eastbound afternoon peak, two periods experienced significantly longer cumulative travel times, 5:15-5:30 and 5:45-6:00. The worst condition occurred for the most part in the Brentwood-Hanley section. The longest travel time occurred during the 5:45-6:00 interval when it averaged 7 minutes and 6 seconds. The cumulative travel times in the westbound direction during the afternoon peak increased, in general, with every 15-minute interval during which runs were conducted. However this increase was more significant within the Oakland-Hanley and Brentwood-McKnight sections. Furthermore, in the worst case, the total travel time was over 11 minutes, or more than twice the time it takes to travel the study area under free flow conditions.

Delay and Stops

During the eastbound morning peak, the longest delay was experienced in the 7:45-8:00 interval during which a total of 34.2 seconds were recorded as delay time. This delay represented over 48 percent of the total delay time recorded during the entire rush period, and thus signified the importance of this time period in the overall morning peak behavior. It was found that the focus of congestion in this direction was between McKnight and Hanley. In the westbound direction during the morning peak, delay was experienced between 7:30 and 8:30 with the longest delay recorded between 7:30 and 8:00. The critical sections were Hampton-Oakland and, more significantly, Oakland-Hanley. The average singular stop experienced between Oakland and Hanley during the 7:30-7:45 interval was also significant.

In the eastbound direction during the afternoon peak, delay was not as critical as in other directions and peaks, but was present. Further, it occurred in the sections of Brentwood-Hanley and Hanley-Oakland. As expected, the highest frequency and magnitude of delay and stops occurred in the westbound direction during the afternoon peak. Delay was experienced in virtually every 15-minute interval of the entire three-hour rush. In addition, after 4:15 delay was encountered in practically every section of the study area. Finally, full stops were reached in multiple time periods and, in some cases, more than once per run.

Acceleration Noise Study

Looking at the acceleration noise charts (Figures 1 and 2) the areas of interests are represented by curves or "humps," either concave or convex. The acceleration noise study for the eastbound direction in the morning peak showed three areas of interest. They are (1) Between I-170 and Laclede; (2) Between Big Bend and Bellevue; and (3) Between Oakland and Hampton. The highest overall acceleration noise was experienced from 8:00 to 9:00 between I-170 and Hanley and it was recorded as approximately 1.83 ft/sec2.

The study for the westbound morning peak yielded the following two areas of interest, where a positive slope in the acceleration curve line occurred in both time periods: (1) between Big Bend and Laclede and (2) between Hanley and I-170. It is important to note that the 7:00-8:00 period recorded higher values than the 8:00-9:00 period in every section. The highest overall value occurred between Oakland and McCausland and amounted to approximately 1.59 ft/sec2.

Three significant conclusions surface for the eastbound afternoon rush period. First, between I-170 and Hanley acceleration noise increased dramatically. Second, between Hanley and Laclede the acceleration noise continually increased. Third, the 5:00-6:00 time interval recorded higher values than the two earlier time periods in most of the study area. The highest value was approximately 1.70 ft/sec2 and it was recorded between I-170 and Hanley. The analysis for the westbound afternoon peak yielded the following conclusions: (1) Acceleration noise values were generally highest during the 4:00-5:00 period, although the peaks during the 5:00-6:00 period were higher; (2) The highest overall value was recorded between Oakland and McCausland and amounted to approximately 1.82 ft/sec2; and (3) This high value of 1.82 ft/sec2 is slightly lower than the highest value, considering both directions and peaks, which was 1.83 ft/sec2 recorded during the eastbound morning rush.

Traffic Volume Study

Freeway Volumes

A series of charts and tables were developed to summarize the volumes and related information. The charts representing volumes and speeds corresponding to time of day during the 21-hour data collection period were plotted to identify the freeway operation, peak-hour periods, and impact of special events. In comparison with the volumes by lanes, it was found that lane 3 had the highest traffic volumes during peak hours, while lane 1 has the lowest. The overall volume from a 21-hour count showed that most vehicles traveled in lane 2, particularly during off-peak hours.

The average percentages of heavy vehicles traveling on this freeway segment was around 16 percent and the percentages of heavy vehicles during peak hours were usually higher than during off-peak hours. The percentages of heavy vehicles on each lane seemed to be consistent over time, particularly during peak hours. Lane 3, in which traffic usually moves faster, characterized with lowest percentage of heavy vehicles, ranged from 5 percent to 9 percent. Lane 2, which had the highest percentage of heavy vehicles, was consistently occupied with 20 percent to 21 percent of heavy vehicles. The heavy vehicle percentages during peak hours in lane 1 were only slightly lower than in lane 2, ranged around 16 percent to 19 percent. The heavy traffic volumes coupled with the presence of high percentages of heavy vehicles make the operation of the freeway segment more complex.

Ramp Volumes

Several ramps record significant volumes and have tremendous impacts on freeway flow operation. The ramps along the study area are numerous, and usually the distances between ramps and/or interchanges are relatively short. In addition, several weaving areas exist within the study area and create significant conflicts in traffic movements. The ramp volumes were integrated with the freeway volumes to form the capacity analysis.

Capacity Analysis

The capacity analyses showed that most of the freeway segments within the study area were saturated during peak hours. Because of the congestion condition on freeway segments, the conditions of most of the ramps have also fallen to level of service F at the merge/diverge check points, even where some ramps may have relatively low volumes. Moreover, the weaving area analyses indicate that the weaving areas, in particular the one located between Hanley and I-170 which is characterized with relatively high volumes and significantly operational conflicts, result the major shock waves and delay phenomena for the entire freeway operation. As far as the weaving areas are concerned, it was found that the weaving areas themselves might not be the major problem. However, the short distances between successive ramps and their intermingled weaving areas, in conjunction with significant volumes created major flow conflicts. More importantly, it was found that the results of the multiple weaving area analyses matched the outcomes of time-delay and acceleration noise studies quite well. This indicates the weaving areas within the study area need to be improved or redesigned in order to maintain a steady traffic flow.

Speed, Volume and Density

The relationships among speed, volume, and density were presented through a series of graphs. Eight graphs, including a speed-volume (u-q) curve, a volume-density (q-k) curve, a speed-density (u-k) curve, and a hourly q-k curve for each peak hour, were generated on a daily basis for each individual lane. These allow one to make comparisons of traffic patterns with different lanes and different days of week. The team then combined the daily data collected at the same location into a massive data set and generated the above eight graphs for each lane again. The graphs using the combined data set represented the normalized traffic data for that location. These resulting graphs are used to observe the speed-volume-density relationships for that location, and define the capacity and critical density of the freeway. Figures 3 and 4 show the speed-volume-density relationships for a three-day data collection on lane 2 of the westbound direction between Clayton-Skinker and Oakland.

It was found that the free-flow speeds were approximately 55 mph, 58 mph, and 63 mph for lane 1, lane 2, and lane 3, respectively. In addition, the capacities for lane 1, lane 2, and lane 3 were identified as approximately 1700 vph, 1900 vph, and 2100 vph, respectively. The traffic flow in lane 3 tended to move faster than others and its capacity was the highest, which also reflected the lower truck percentage. Lane 2, which characterized with higher volume and higher truck percentage, moved slightly faster than lane 1 under uninterrupted flow. The traffic in lane 1, which always has to interact with high truck percentages and ramp merging and diverging activities, showed the lowest free-flow speed and capacity.

From the q-k and u-k curves, it was found that density had strong relationships with volume and speed until it reached the range of 35 to 40 vehicles per mile per lane (veh/mi/ln). In a rather conservative way, the critical densities were identified from the q-k curves. The critical density was defined as the density corresponding to the maximum volume can be accommodated on the freeway. The results showed that the critical densities for lane 1, 2, and 3 seem to be very close to each others, regardless their observed free-flow speeds. It suggests that density may be a rather important and more reliable measure than volume and speed in the determination of freeway capacity.

The major advantage of the hourly q-k curves is to observe the dynamics and progression of the traffic stream and, more importantly, the shock wave phenomena. Figures 5 and 6 present the combined hourly q-k curves for typical morning and afternoon peaks. These figures show that the density measures during peak hours were constantly over the critical density, especially in the afternoon peak. It indicated the traffic stream within this section of the freeway was unstable. The q-k curves suggest that the best traffic condition is when the density is lower than critical density. That is, if we can maintain the density measures lower than critical density at all times, congestion will be significantly reduced, and the road can be utilized in the most effective and efficient way. It also suggests that, if the density values on the right-hand side of the critical density can be shifted to near or lower than critical density by some way(s), the shock waves, delay, and congestion phenomena can be minimized.

Potential Solutions

After reviewing the data, and behavior requirements for easing congestion in this corridor, the following solution set is listed as being potentially capable of altering the density in such a manner as to achieve congestion mitigation. The itemized possible solutions are as follows:

Ramp Metering - To develop uniform input to the traffic stream, with the objective being to achieve better density levels by virtue of regulated influx of additional flow.

Related Arterial Street Retiming - To achieve better surrounding area traffic flow circulation, including more uniform usage of freeway access and egress points, thus improving density profiles.

Changes in Weaving Operations - To mitigate traffic conflicts of access, egress and mainline interfacing movements, which develop compound density clusters, traffic humps and ultimately induce shock wave performance and systems saturation. Improved placement, design and throughput components of weaving operations in conjunction with the critical ramp locations noted in the study may minimize this flow conflict problem and improve density levels.

Operational and Geometric Alteration of Adjacent Freeway Facilities - Such as the I-170 corridor as it impacts I-64-40 segment flow and critical weaving processes.

Advance Warning Systems to Motorists, by Use of Variable Message Signing - The use of such traffic operations advance warning systems may allow notification of unique density and saturation problems and/or incident identification, and offer directional advice and control requirements for drivers which will mitigate density problems.

Incident Detection Capabilities - Closely related to the above, incident detection systems and message systems can warn drivers of unique accident, lane closure and other related incidents which alter density, and allow mitigation opportunities.

Use of Related TSM Strategies - The parceling out of specific lane use for transit and/or high occupancy carpool use and other modal split intensive TSM strategies such as carpooling and vanpooling may reduce individual auto trip making and therefore freeway usage resulting in lowered density.

Geometric Design Alterations - The unique redesign and reconstruction of the cross-section, possibly increasing the number of lanes, therefore reducing density per lane.

Alternate Routing Programs - Development, in conjunction with all of the above and the ultimate IVHS-TIC system, of a dynamic route guidance program which assesses density and saturation for a freeway segment or route path, relays it to driver and develops an alternate routing assignment considered optimal for the driver's origin-destination.

In reviewing the above as likely candidates for study, experimentation, testing, and implementation in the next research phase, it should be understood that the first six entities range from operational technology currently in existence towards functional component IVHS systems components now considered state-of-the-art and being placed in many metropolitan areas. The development of related TSM strategies are more reflective of the status for progressive change in urban transportation planning that a region must undergo. On the other hand, geometric design alterations and reconstruction are likely to be costly and have environmental and negative public policy implications. Finally, true alternate routing programs can only be placed after a thorough integration of all IVHS components, and the integration and functional operation of a total freeway management system.

In light of the above, it should be understood that the first six potentially operational components of freeway congestion management should be researched in detail, while other solutions should be considered cautiously in light of their capital costs, public policy implications and somewhat uncontrollable variables.


Major conclusions with respect to data collection procedures and outputs and behavioral characteristics and findings include:

  1. The critical area in the eastbound direction is bounded by Brentwood Boulevard and Laclede Station Road. High values for delay, stops, volume, density, and acceleration noise, coupled with low average speeds resulted in near or full saturation of this section during the morning and afternoon peaks.
  2. In addition, the section bounded by McKnight Road and Brentwood Boulevard remained in congestion throughout most of the morning peak as traffic merged and diverged within the section
  3. The critical area in the westbound direction is bounded by Oakland Avenue and Hanley Road. There was a significant breakdown in the traffic flow in this section during the morning peak, and more significantly, for a longer period of time during the afternoon peak.
  4. Major shock wave and freeway saturation occurred within the study area. Specific worse case incidences include the following:
  5. The worse case scenario for the morning and afternoon eastbound peaks occurred between 7:00 to 8:00 AM and 5:30 to 6:00 PM, respectively, while traversing the Brentwood Boulevard to Laclede Station Road section. The multiple weaving areas in the section together with the large volumes on the adjacent ramps create high acceleration noise and significant delay.
  6. In the westbound direction, traffic flow reaches its lowest throughput during the 7:30 to 8:00 AM interval and the 4:30 to 5:30 PM interval, for the morning and afternoon peaks respectively. Multiple weaving areas and high ramp loads in the Oakland Avenue to Hanley Road section create frequent shock waves and saturation.
  7. As evident from the above points, the Hanley Road interchange, combined with the neighboring I-170 interchange, creates significant traffic conflicts which result in conditions that designate this section as the most critical in the study area.
  8. A major opportunity to improve congestion exists by virtue of utilizing solutions which reposition the density level to the appropriate portion of the q-k curve. This should be the primary objective of potential future solutions studied and demonstrated.

In light of the above findings and conclusions, a set of potential solutions are worthy of consideration in further research. Such research should simulate, experiment, and demonstrate the potential for further positive alteration of the density profile, as discussed above. It should also include an evaluation of public benefits and costs of the above options, formation of unique combinations of options, and a description and specification of a public awareness program to educate the public as to the value of the installation of such systems.


Funding for this study was provided by the Missouri Highway and Transportation Department and its District 6 Metro Office in St. Louis through the Transportation and Urban Systems Engineering Program, Department of Civil Engineering, Washington University.

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