Journal of Advanced Transportation, Vol. 31, No. 3, pp. 325342 Acceleration Noise and Level of Service of Urban Roads A Case Study Y. Sudheer Babu S.B. Pattnaik Capacity measurement of roads under mixed traffic conditions as prevailing in India is ambiguous as it varies with time, composition of traffic and roadway encroachments. High incidence of slow moving vehicles and tricycles adds to the problem. Volume capacity ratio appears to be an inadequate measure of defming level of service under mixed traffic situations. An attempt is made in this paper to explore the possibility of presenting unconventional parameters like standard deviation of speed, coefficient of variation of speed and acceleration noise as possible measures of level of service. Tentative ranges of acceleration noise are proposed in association with flow and speed to explain level of service of urban roads catering to mixed traffic. The results are based on a study conducted in Madras, a major metropolitan city of India. Introduction Level of service is a qualitative measure of the effect of a number of factors. Different parameters are used to explain the level of service depending on the context. Usually, volume capacity ratio (VK) and peak hour factor (PHF) are used along with traffic speed to define the level of service of a roadway facility. However, capacity measurement, especially in India, is quite ambiguous since it varies with time, composition of traffic, carriageway encroachments and adjoining landuses. Often the effective carriageway width varies with time, affecting the capacity greatly. The variations of Y. Sudheer Babu is an Assistant Professor in the Department of Civil Engineering, Siddhartha Engineering College, Vijayawada, India. S.B. Pattnaik is an Associate Professor in the Department of Civil Engineering, Indian Institute of Technology, Madras, India. Raccivcd August 1995; Accepted April 1997.
326 Y. Sudheer Babu, S. B. Pattnaik the influx of pedestrians also influences the capacity. The passenger car unit (PCU) factors, adopted to convert various types of vehicles into standard passenger car unit, adds to the complexities of the problem. PCU values would depend on prevailing local conditions. Hence, the volume capacity ratio (VK) appears to be an inadequate measure of defining level of service especially under mixed traffic situations. Travel time too may not always reflect true conditions on the facility and is exclusively quantitative in nature. The discomfort experienced by drivers by way of frequent accelerations and decelerations is concealed in the average travel time. Of late, the traffic parameter, acceleration noise, defined as standard deviation of acceleration experienced by a vehicle in a traffic stream, has received attention as a possible measure of traffic flow quality for two important reasons. First, it explains the basic elements of traffic, viz. driver, road and traffic interaction collectively and individually. Secondly, it is a measure of the smoothness of flow in a traffic stream, a good qualitative indicator through specified quantitative ranges. It is also significant while comparing the flow quality before and after changes in geometric configurations of a facility. Considering these facts, an attempt is made in this study to explore the possibilities of presenting acceleration noise as an aggregate measure of level of service of urban road users as no such study has yet been conducted for mixed traffic conditions prevailing in India. Literature Review The level of service has been defined to represent ranges through three critical variables viz. average speed, flow and density. The basic relationships are extensively studied by many researchers. Drake et al (1967), studied speeddensity relationships. Haynes (1965) based on his studies on Gulf Freeway (6 lane divided road with 12 ft. lane width) in Houston, Texas stated that density is directly related to congestion of traffic. Van Aerde et al (1983) while studying Twoway 2lane highways in Ontario reported that the speed volume curve consists of two distinct parts; a linear section represents normal operation conditions for most of the capacity range and a nonlinear section representing a transition to flow breakdown and queuing. Several studies conducted in India too highlighted the problem of capacity and level of service under mixed traffic conditions. Justo et al (1978) while studying various roads (16 to 30 m wide with medians and bus
Acceleration Noise and Level of Service... 327 bays) in Bangalore City emphasized on recommending improvements in level of service. The massive Road User Cost Study (RUCS) (1983), though aimed at rural roads of different parts of India with single and double lanes, was comprehensive and dealt with wide areas such as speed, flow, density, fuel consumption, accidents etc. However, the study by Ramanayya (1992) well deserves a mention in the present context. While studying interrelationships among the components of traffic stream viz. speed, flow and density under mixed traffic conditions (on roads of Bangalore City and its suburban areas), he attempts to define level of service for mixed traffic using speed ranges and percentage of slow moving vehicles in the total traffic. It is interesting to note that his simulation study has taken a strong objection to the method of measuring capacity for mixed traffic prevailing on Indian roads based on guidelines provided by the Highway Capacity Manual (1985). The popular Energy Model by Drew et al (1965) based on Gulf Freeway in Houston, Texas, gave due importance to acceleration noise. Torres (1970) investigated the relationship of acceleration noise to some of the more common traffic variables. He conducted studies on short stretches of 1 to 2 miles and four lanes in each direction of Ventura Freeway and San Diego Freeway confined to morning peak traffic. His study is suggestive of the acceleration noise as a more sensitive measure of examining driver s response. But some studies were contrary to those predicted by Drew (1968). Lee and Jason (1973) observed for platoon movements that acceleration noise is not an adequate parameter for representing internal energy of a traffic stream, if the internal energy is defined in terms of vehicular interactions. His conclusions are based on aerial photogrammetry studies. Winzer (1981) observed that the acceleration noise approaches natural noise at low and high densities and reaches maximum at medium densities. His findings are based on repeated experiments on a 13km. stretch with twoway 4lane divided highway (Autobahn BAB5, Germany). Interestingly, these studies too justify the acceptance of acceleration noise as a comprehensive parameter to evaluate the level of service of a traffic system. However, the unconventional parameter for measuring level of service offered to road users such as standard deviation of speed, coefficient of variation of speed and acceleration noise were never attempted for Indian conditions.
328 Y. Sudheer Babu, S.B. Pattnaik Field Studies Madras, the fourth largest metropolis of India, forms the backdrop for this study. The study demands extensive field surveys. The traffic behavior has to be studied during different time periods of the day to represent varying traffic interactions. Moving observer method was employed to collect simultaneously the data such as flow, speed, travel time and delays. Besides, the supporting data such as activity patterns due to adjoining landuses, encroachments onto carriageways, parking, pedestrian intensity etc., was also recorded. As locally available tachographs were not suitable for microlevel analysis of speed profile, manual recording of individual speed values at an interval of 30 seconds as observed from speedometer of the test vehicle was adopted. Test runs were conducted on different classes of roads as multilane roads and undivided narrow roads. However, the analysis of only five major traffic corridors was presented. Study area and the test run roads are shown in Figure 1. Road 1 (consists of Village Road and McNicholas Road) is a congested 2lane twoway road having an effective width of 7.5 m and caters to high volumes of slow moving traffic. Footpaths with a width of 1.52.0 m, are ineffective due to unauthorized parking of bicycles and encroachment by hawkers. Adjoining landuse is mainly residential cum business. The road length is approximately 3.3 km. Road 2 (Anna Salai) is the most important traffic corridor of Madras City, having three lanes in each direction. The width of road is about 22 m including 0.5 m median with unmountable curbs. About 1.53.0 m wide footpaths are provided on eitherside. Length of road is about 4.85 km. Curb parking is restricted. Pedestrians are confined to footpaths as hawkers are discouraged to encroach onto the roads. Surrounding landuse consists of mainly commercial and official buildings. Business and entertainment centers are also housed in this area. Road 3 (Royapetah High Road) is again a congested 2lane twoway road stretch with about 7.5 m wide carriageway and 1.52.0 m footpaths. Test Runs were made on a 3.1 km stretch. The major portion of traffic consists of slow moving vehicles, with similar conditions as prevailing on Road 1. Road 4 (Kamarajar Salai) in contrast, has 4 undivided lanes (with yellow central barrier paint marking) with an additional parking lane on beach side. Width varies between 16 to 18 m with 1.53.0 m foot
Acceleration Noise and Level of Service... 329 Anna nagar KMC Porrn Nun p am ba k ham Vadapoloni Kodombakkom To K 0 1 2u Figure 1. Key Map of Study Area Te5t run roods Test run roads selected for anolyrls other malor road
330 Y. Sudheer Babu. S.B. Pattnaik paths. The road with good surfacing and well maintained sidewalks provides good driving conditions. The road runs parallel to Marina Beach. Madras University, other educational institutions and government offices are spread on the other side of the road. Road 5 (Poonamallee High Road), about 4.8 km long passes through yet another activity area. Surrounding are mainly hospitals, corporate offices etc. The width of this 4lane divided road ranges between 14 to 17 m with about 2.0 m footpaths which are not properly maintained. Test runs were made on several days during different time periods i.e., early in the morning (2:305:OO) to represent near no traffic conditions, morning (8:3011:OO h) and evening (16:3019:OO h) for peak periods of traffic, noon (13:OO15:OO h) and night (20:3023:OO h) to consider lean traffic conditions. All the runs were made using a standard van with the same driver to exclude variations due to vehicle or driver characteristics. Conducting test runs with many drivers, though would eliminate any possible bias in the results, was not possible with limited finances received for this project. However, the driver was selected only after examining a few drivers for consistency in driving. Data Analysis The observed data required refinement before final analysis. There were some abnormalities like unexpected traffic jams, delays at signalized junctions, pedestrian crossings at midblocks, effect of raining etc. The data representing only normal traffic conditions was used for the analysis. Graphic software were used to build several relationships among the parameters. The composition of traffic on different roads was fairly consistent throughout the day (Figure 2). Basic Elements of Traffic The relationship between the density and flow (Figure 3) assumes a parabolic shape. Similarly, considering density and speed relationship (Figure 4), the observations follow second order polynomial curve and show that initially as density increases, speed falls sharply, but stabilizes in near vicinity of critical density beyond which, speed may decrease linearly. Other relationships (not included here) viz. flow vs. speed and V/C ratio vs. travel time also convey similar messages.
Acceleration Noise and Level of Service... 33 1 i9y B&T 4 \ 35 15 26 ROAD 1 ROAD 2 C 6 V CARS 6 VANS 23 25 B L T BUSES L TRUCKS 3 1 THREE WHEELERS 2 1 TWO WHEELERS 0 BICYCLES L OTHER VEHCLLI (J ROAD 3 @ 25 28 ROAD L ROAD 5 Figure 2. Percentage Traffic Composition on Roads
332 Y. Sudheer Babu, S.B. Pattnaik 2000 1750 ROAD 1 ROAO 2 ROAD3 1 ROAD4 a. ROADS 0 0 10 20 30 LO SO &O 70 80 90 100 110 DENSITY ( PCU/RM) Figure 3. Density vs. Flow 'O t ROAOl ROAD 'I ROAO 3 ROAD4 I ROAD5 lo 0 0 10 10 30 LO so 60 70 80 90 loo 110 DEN SITV ( P c u / RM ) Figure 4. Density vs. Speed
Acceleration Noise and Level of Service... 333 Unconventional Parameters Standard deviation of speed (SDNS), coefficient of variation of speed (CVS) and standard deviation of acceleration (acceleration noise) are considered to explain traffic behavior. It is common understanding that fluctuations in speed values indicate driver s behavior as well as traffic conditions which influence driving. The relationship between speed and standard aviation of speed (SDNS) for the roads under consideration (Figure 5) reveals some interesting observations. Standard deviation increases as speed decreases, probably up to a point where flow attains stability. There are standard deviation falls with speed as flow reaches unstable conditions. Coefficient of variation of speed (CVS) exhibits similar trends (Figure 6). These curves have their concavity upwards. The coefficient of variation of speed (CVS) which includes both speed and standard deviation of speed (SDNS) appears more appropriate as it absorbs fluctuations. It is equally interesting to examine the relationship of flow with coefficient of variation of speed, CVS (Figure 7). It is observed that coefficient of variation of speed (CVS) increases up to half the critical flow and then it shows the downward trend. This explains that traffic behavior is erratic until flow reaches half of its critical value and there are drivers start loosing freedom as reflected in the reversal of the trend. Thus, coefficient of variation of speed (CVS) can be regarded as an important parameter to measure speed fluctuations that drivers experience in traffic streams. Acceleration Noise This is reflective of overall behavior of the traffic stream and may be regarded as the direct result of driver s stress and discomfort. It would be interesting to study this parameter to describe mixed traffic situations as prevailing in India. The relationship of acceleration noise with flow (Figure 8) and density (Figure 9) is almost linear for the case study. It can be observed from these illustrations that acceleration noise is not so sensitive to changes in density and flow in case of narrow roads (Road 1 and 3). The slopes of these lines are smooth and gradual. In contrast, for wider roads (Road 2, 4 and 5) slopes are relatively steeper indicating higher sensitiveness of acceleration noise with respect to density and flow. The relationship of acceleration noise with mean speed of traffic stream (Fig. 10) draws similar observations.
334 Y. Sudheer Babu, S. B. Pattnaik z \ l'" 15.0 E x 12.3 Y t ROAO 1 ROAD2 ROAO.3 I ROAD4 I ROADS m 10.0 2 0 * 7.5 5.0 10 20 30 LO 50 60 SPEED ( Km/h) Figure 5. Speed vs. Standard Deviation of Speed (SDNS) 0.8 0.7 0. 6 ROAD 1 ROAO 2 ROAD 3 ROAD 4 ROAO 5 0. 5 II) > u 0.4 0.3 0.2 0.1 '0 Figure 6. Speed vs. CoEfficient of Variation of Speed (CVS)
Acceleration Noise and Level of Service.. v) > U 0.8 0.7 0.6 0.5 0.4 335 ROAO 1 ROAO 2 _ ROAD 3 I ROAOL I ROAOI 0 400 80 0 1200 1600 2000 FLOW ( PCU/H 1 Figure 7. Flow vs. Coefficient of Variation (CVS) 0.12 u) 0.10 \ ul \ L 0.08 Y r o.oa 0 2 0.04 V V 4 0.02 ROAOZ ROA03 / I ROAD4 I ROAD5 /:Ae/ /.f?' /. / / Ax/ / / v',*' 0 Figure 8. Flow vs. Acceleration Noise
336 Y. Sudheer Babu, S.B. Pattnaik 0.12 n v) 0.10 \ v) 3 0.08 w W g 0.08 ~ 0 2 0.04 R O N 1 ROAO 2 ROAD3 I a. ROADI ROADS V V a 0.02 0 1 I I 0 10 20 30 LO SO 80 70 80 90 100 110 DENSITY ( PCU/UM ) Figure 9. Density vs. Acceleration Noise 0.12 n ul 2 0.10 \ x w 0.08 ' ' ' \ "\ ROAO 1 ROAD 2 ROAO 3 I ROAO 4 + ROAO 5 W ul 0 0.06 z 0 0.04 V 4: 0.02 0 1 I 1 1 I 0 10 20 30 LO 50 80 SPEEO (Km/h) Figure 10. Speed vs. Acceleration Noise
Acceleration Noise and Level of Service... 337 One striking observation from all these relationships is that acceleration noise, being passive, is low in magnitude for narrow roads. As already discussed, these narrow roads are considered as congested stretches with higher flow rates and wayside parking of slow moving vehicles especially bicycles. The above observation is contrary to what was observed by Jones et al (1962) and as stated by Drew (1968), but tallies with the findings of Winzer (1981). The present observation may be attributed to mixed nature of traffic due to high incidence of slow moving vehicles like bicycles prevailing in Indian cities. It is also interesting to observe from these graphs that acceleration noise has mostly linear relationship with all the basic elements with the ranges of acceleration noise varying from road to road as seen from the slopes of the graphs. This can be attributed to the nature of traffic, geometric features of roads and other factors like adjoining landuses, onstreet parking etc. Tentative Ranges of Acceleration Noise For any road facility two elements of traffic are easy to measure. They are flow rate and average speed of traffic stream. Interestingly, acceleration noise responds encouragingly with these two elements confirming to the observations made by Torres (1970). Hence, it would be more appropriate for mixed traffic, to chart out the level of service of urban roads in terms of ranges of acceleration noise in combination with flow and speed of traffic stream. The characteristics of different levels of service for urban arterial roads can be summarized (Table 1) as per Kadiyali (1991). Following these guidelines, the average values of all the factors during normal traffic conditions for five major arterial roads considered for the present study are presented in Table 2. The Table also includes (last column) the level of service grading of reach road. This is arrived at based on the guidelines given in Table 1 i.e., based on speed, V/C and PHF values.
~ ~~ 338 Y. Sudheer Babu, S.B. Pattnaik Table 1. Level of Service Criteria for Urban Arterial Roads Source: Kadiyali (1991) I Level of Service I speed kmh VIC PHF Load Factor Flow Conditions A, >80 0.6 0.70 0.0 Free Flow B >40 0.7 0.80 0.1 Stable Flow; Slight Delays C >30 0.8 0.85 0.3 Stable Flow; Acceptable Delays D E >25 0.9 0.90 0.7 l Approaching Unstable Flow; Delays Unstable Flow; Intolerable Delays F Overloa ding Forced Flow; Jam Conditions V/C = Volume Capacity Ratio PHF = Peak Hour Factor It may be observed from Table 2 that acceleration noise values associated with flow and speed values of all five roads have distinct relationships with the given level of service grades. The observations also support the findings of Winzer (1981) that acceleration noise is higher at medium densities and lower at low and higher densities. Thus, this table helps to understand the possible role of acceleration noise to characterize level of service of an urban road under mixed traffic situation.
340 Y. Sudheer Babu, S. B. Pattnaik However, to eliminate ambiguity, an attempt is made to delineate tentatively the ranges of acceleration noise with the support of flow and speed of traffic stream to explain the six levels of service of urban roads (for mixed traffic conditions as prevailing in India), A through F (Table Table 3. Proposed Level of Service Ranges Note: These ranges are tentatively fixed based on study observations. First, acceleration noise increases with flow until unstable conditions are reached indicating loss of freedom to maintain consistency in speed. Thereafter acceleration noise decreases indicating forced flow conditions. Thus, together with flow and speed, acceleration noise may very well define various levels of service as offered to urban road users, more so under mixed traffic conditions. Conclusions It is observed that standard deviation of speed (SDNS) and coefficient of variation of speed (CVS) respond positively while analyzing mixed traffic behavior. However, acceleration noise is found to have better correlation through linear relationships with speed and flow. Tentative ranges of acceleration noise along with flow and speed of
Acceleration Noise and Level of Service... 34 1 traffic are proposed to explain six levels of service for urban roads for mixed traffic as prevailing in India. However, these ranges on different roads depend on the freedom available to driver and the nature of traffic encountered. Exhaustive support from a strong database is necessary before generalizing for urban areas in India. Still, this study assumes considerable importance to establish that the acceleration noise could be a comprehensive measure to explain the level of service as offered to urban road users by replacing ambiguous parameters like volumecapacity ratio (V/C) for mixed traffic situation as prevalent in Indian cities. Acknowledgement This work, to the extent of field studies, received financial assistance from Indian Institute of Technology, Madras. One of the authors (Y. Sudheer Babu) also received a scholarship for his doctoral research. The authors acknowledge the assistance received from the Institute. References Drake J., Schofer, J.L. and May, A.D., "A Statistical Analysis of Speed Density Hypothesis", Highway Research Record 154, Highway Research Board, National Research Council, pp. 53897, 1967. Drew, Donald R., "Traffic Flow Theory and Control", McGrawHill Book Co., New york, 1968. Drew, Donald R., Dudek, Conrad 1. and Keese, Charles J., "Freeway Level of Service as Described by an EnergyAcceleration Noise Model", Highway Research Record 162, highway Research Board, National Research Council, pp. 3085, 1965. Haynes, John J., "Some Considerations of Vehicular Density on Urban Freeways", Highway Research Record 99, Highway Research Board, National Research Council, pp. 5979, 1965. Highway Capacity Manual, Special Report 209, Transportation Research Board, National Research Council, 1985. Jones, Trevor R. and Potts, Renfrey B., "The Measurement of Acceleration Noise A Traffic Parameter", Operations Research, pp. 745763, Nov.Dec., 1962. Justo, C.E.G. and Reddy, K.C., Ymprovements in Level of Service for Traffic Operations A Case Study", Indian Roads Congress Journal, Vol. 39, pp. 403439, 1978.
342 Y. Sheer Babu, S. B. Pattnaik Kadiyaki, I.R., "Traffic Engineering and Transport Planning", Khanna Publishers, Delhi, 1991. Lee, Joe and Yu, Jason C., "Internal Energy of Traffic Flows", Transportation Research Record 456, Highway Research Board, National Research Council, pp. 4049, 1973. Ramanayya, T.V., "Traffic Stream Models", Proceedings of National Seminar on Advances in Transportation Systems, B9.106, Indian Institute of Technology Madras 1992. Sudheer, Babu Y., "Appraisal of The Indices of Level of Service Under Mixed Urban Traffic Conditions Madras as a Case Study", Ph.D. Thesis, Department of Civil Engineering, Indian Institute of Technology, Madras, 1992. Swaminathan, C.G. and Kadiyali, L.R., "Road User Cost Study in India", Indian Roads Congress Journal, Vol. 44, pp. 191289, 1983. Torres, J.F., "Acceleration Noise, Power Spectra and Other Statistics Derived from Instrumented Vehicle measurements Under Freeway Driving Conditions", Highway Research Record 308, Highway Research Board, National Research Council, pp. 1333, 1970. Van Aerde, Michael and Ygar, Sam, "Volume Effects on Speeds of 2 lane Highways in Ontario", Transportation Research, Vol. 17A, No. 4, pp. 301313, 1983. Winzer, Thomas, "Measurement of Acceleration Noise and Discussion of The Energy Model Developed by Drew", Transportation Research, Vol. 15A, No. 6, pp. 437443, 1981.