International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 5, May 2017, pp. 1135 1146, Article ID: IJCIET_08_05_120 Available online at http://www.ia aeme.com/ijciet/issues.asp?jtype=ijciet&vtyp pe=8&itype=5 ISSN Print: 0976-6308 and ISSN Online: 0976-6316 IAEME Publication Scopus Indexed ASSESSMENT OF EFFECTIVENESS OF VERTICAL DEFLECTION TYPE TRAFFIC CALMING MEASURES AND DEVELOPMENT OF SPEED PREDICTION MODELS IN URBAN PERSPECTIVE Siddhartha Rokade Assistant Professor, Department of Civil Engineering, M.A.N.I.T., Bhopal, India. Rakesh Kumar Assistant Professor, Department of Civil Engineering, M.A.N.I.T., Bhopal, India. Varsha Rokade Assistant Professor, Department of Civil Engineering, M.A.N.I.T., Bhopal, India. Shakti Dubey PG Student, Department of Civil Engineering, M.A.N.I.T., Bhopal, India. Vaibhav Vijayawargiya PG Student, Department of Civil Engineering, M.A.N.I.T., Bhopal, India. ABSTRACT Road safety and accident prevention is of prime importance in the world today and more so in the developing nations like India, it needs to be dealt at war footing. Speed is one of the main factors which affect the road safety i.e. the accident rate and accident severity. High speed is a contributing factor in almost one-third of all crashes; hence, speed control is fundamental to road safety. It has been proved that speed management is the most effective means to reduce road accidents and fatalities. Traffic calming measuress (TCM s) are an economic and effective means to reduce speed on a particular road stretch and are seen as one of the solutionss to tackle such problems effectively. Traffic calming devices such as speed bumps and humps are being used in India; however, limited studies have been conductedd regarding the evaluation of their effectiveness in traffic calming. The present study deal with the assessment of effectiveness of vertical deflection type TCM s which includes speed bump, plastic speed bump, raised crosswalk, rumble strips and sinusoidal hump. Speed profile curves weree developed for each vertical deflection type TCM. Further, in the present study, speed prediction models for urban areas were also developed. http://www.iaeme.com/ijciet/index.asp 1135 editor@iaeme.com
Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya The suitability of a particular TCM was also assessed on the basis of composition of the traffic i.e. two wheelers (2W), three wheelers (3W), four wheelers (4W) and heavy motor vehicles (HMV s). Key words: Traffic Calming, Road Safety, Speed Prediction Modelling, Speed Bump, Raised Crosswalk etc. Cite this Article: Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective. International Journal of Civil Engineering and Technology, 8(5), 2017, pp. 1135 1146. http://www.iaeme.com/ijciet/issues.asp?jtype=ijciet&vtype=8&itype=5 1. INTRODUCTION Construction of roads is one of the prime requirements for the development of any country, and so is for a developing nation like India. With one of the highest motorization growth rates in the world accompanied by a rapid expansion of the road network and urbanization over the years, India faces serious impacts as far as road safety is concerned. The analysis of road accident data 2015 reveals that about 1,374 accidents and 400 deaths take place every day on Indian roads which further translates into 57 accidents and loss of 17 lives on an average every hour in the country (MORTH, 2015). In the roads of the European Union alone, during 2009, more than 35,000 people died and more than 1,500,000 were injured. The cost of those accidents for society is huge and it is estimated on approximately 130 billion Euros (EC, 2010).The prime causes of the road mishaps include inappropriate speed, carelessness on the heavily trafficked roads, violation of traffic rules, erratic parking, drunken driving and absence of safe and appropriate road crossing facilities for pedestrians and other vulnerable road users (WHO, 2004).Driver s fault has been revealed as the single most responsible factor for road accidents, killings and injuries on all roads in the country over a long period of time which accounted for 77.1 % of total road accidents during 2015. Within the category of driver s fault, road accidents caused and persons killed due to over speeding by drivers accounted for a share of 62.2 % and 61.0 % respectively (MORTH, 2015).Speed is one of the main factors which affect the road safety i.e. the accident rate and severity. High speed is a contributing factor in almost one-third of all crashes. In residential areas where the streets have a lesser width than the other types of urban roads, lower speed limits need to be provided. Also in congested areas, accident prone areas or areas near to the hospitals and schools, lower vehicle speeds are required to reduce the probability of accidents and noise nuisance (Elvik et al., 2004). The probability of pedestrian death is estimated at less than 10% at impact speeds of 30 km/h and greater than 80% at 50 km/h, and the relationship between the increase in fatalities and increase in impact velocities is governed by a power of four. Small increase in urban speeds can increase death rates dramatically. Therefore, urban safety policies should give the highest priority to pedestrian and bicycle separation from motor vehicles, speed control on main arterial roads, and traffic calming on all other roads (Mohan et al., 2009).Also, the presence of improper speed humps significantly affects the pavement condition (Bekheet, 2014; Abdel-Wahed and Hashim, 2017). It has been proved that speed management is the most effective means to reduce road accidents. Speed can be reduced by the use of 3 E s, engineering, enforcement and education (WHO, 2004).Two principles are widely used to control vehicular speeds at a particular road stretch: visual measures and physical measures. Speed limit signs, painted strips across the speed, road surface patterns, plants, etc. are common examples of providing visual measures. Past experiences of European countries indicate that only visual measures are not effective in http://www.iaeme.com/ijciet/index.asp 1136 editor@iaeme.com
Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective controlling the vehicle speeds, but when they are used with physical measures they yielded satisfactory results (Schlabbach, 1997). Traffic calming schemes have a very important role to play in enhancing road safety of urban areas (Juhász and Koren, 2016). TCM s are an economic and effective means to reduce speed on a particular road stretch and are seen as one of the solutions to tackle such problems effectively. TCM s also reduce fatalities and severity of injuries (Jateikienė et al., 2016). The most common problems on the streets regarding motor vehicles are high speed and excessive traffic volume. Also, traffic conflict between vehicles and the vulnerable road users like pedestrians is another problem at intersections. TCM s can effectively reduce the number of accidents and severity (Hydén and Svensson, 2009).Therefore, there is a need to study and analyse the traffic calming devices and measures thoroughly. Traffic calming devices such as speed bumps and humps are being used in India, however, limited studies have been conducted regarding the evaluation of their effectiveness in traffic calming. In Indian cities traffic mainly comprises of two wheelers (motorized), three wheelers, and non-motorized vehicles in large proportions than passenger cars. The traffic calming devices which give satisfactory results for one class of vehicles may prove inappropriate for another class of vehicles (Tiwari, 2004). This paper focuses on the evaluation of the effectiveness of vertical deflection type TCM such as speed bump, plastic speed bump, raised crosswalk, rumble strips, and sinusoidal hump and development of speed prediction models for urban areas. In the present study, the evaluation is based on the intensity of speed reduction of various vehicle classes i.e. 2W (motorized), 3W, 4W (passenger cars) and HMV s (buses and trucks). The study focuses on motorized traffic only and the assessment concerning non-motorized transport is not considered in the present study. These TCM s under consideration are located at different links in Bhopal city of India. The research was carried out at different road links possessing traffic composition and characteristics of similar nature. The speed prediction models were developed for all the TCM s under consideration for 85 th percentile and average mean speed of the vehicles. 2. LITERATURE REVIEW Traffic calming is a Combination of mainly physical measures that reduce the negative effects of motor vehicle use, alter driver behaviour, and improve conditions for nonmotorized street users. (Lookwood, 1997). The primary purpose of traffic calming is to reduce undesirably high traffic speeds to acceptable levels, and furthermore, to improve safety for pedestrians and motorists. The urban road speed management is essentially required to lower the speed up to limiting speeds because of the mixed traffic conditions in urban areas in India. (Chaturvedi, 2006).Vertical deflection type TCM s include speed tables, speed humps and bumps, speed cushions, rumble strips and raised pedestrian crosswalks. Vertical deflection type TCM s are proving to be the most effective measures in term of speed reduction, on the other side horizontal deflection chicanes, traffic circles and roundabouts are less effective (Tiwari, 2004). The effectiveness of TCM s has been commonly assessed by means of speed reduction (Moreno and García, 2013). Speed bumps slow the speed of vehicles to 25 to 30 Mph(McDonald and McDonald, 2010). The magnitude of discomfort to the driver depends on the speed of the vehicle on the traffic calming devices. Effectiveness of the traffic calming devices also depends on the type of vehicles. Vehicles having large and tight suspension like mini vans or luxury cars, find less trouble and discomfort over the bumps or other traffic calming measure (Pau and Angius, 2001).Speed tables are similar to speed humps but having the flat top constructed with bricks or other textured materials. Due to the long flat width they provide a smooth ride for larger vehicles http://www.iaeme.com/ijciet/index.asp 1137 editor@iaeme.com
Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya and thus they are used where only a small reduction in speed is required and proportion of larger vehicles are more (Ahmed and Bagchi, 2013). Pau and Angius (2001) investigated the effectiveness of speed bumps in Italy, as Italy introduced the extensive use of speed bumps in urban areas to reduce the speed and thus to mitigate the high number of fatalities on roads. Their findings showed that at almost one third observation sites, the 85 th percentile speed crossed the posted limit. Results also showed that only slight reduction in speed in the range of 10% to 18% was observed on the traffic calmed streets and their influence region were also found from 30m to 60m.Daniel et al. (2012) investigated the impacts of vertical speed control devices, in particular case of speed humps having height of 100mm and 75mm and speed tables having a height of 75mm, on the vehicle speed and noise emission. They developed a speed model to estimate approach speed to the speed hump or tables, and speed between to TCM s using linear regression analysis. Their speed model suggests that to ensure the 85 th percentile speed of 35-40km/h and 40-45km/h, series of speed humps of spacing 50-80m and 80-130m are required, while in the case of speed tables, to ensure the 85 th percentile speed in the range of 40-45km/h, spacing required is 55-105m. Also, their finding shows that speed humps are more effective to reduce speed compared to speed tables. Ratanavaraha and Watthanaklang (2013) examined the effectiveness of temporary traffic calming devices to reduce speed in school zones in Thailand. They examined three types of temporary traffic calming devices. The type 1 traffic calming device has an arrangement of traffic cones to provide vertical alignment in the centre. Type 2 has the arrangement of traffic cones in the centre line of road and two road sides to act as street narrowing while type 3 has the arrangement similar to type 2 but with the use of warning lights to inform the drivers about the alignment before entering the zones. A nova analysis was applied to examine the effect of traffic calming devices on the speed. They found that type 1 arrangement is ineffective, whereas type 2 and type 3 arrangement moderate the speed effectively with the similar efficiency. Johansson et al. (2011) determined the effect of distance between speed cushions and pedestrian crossings on the safety and mobility of pedestrians and cyclists. Studies show that when the distance between speed cushion and pedestrian crossing was longer, the speed was comparatively lower at the pedestrian crossing than in the case of shorter spacing. They gave its explanation that drivers were more cautious, tentative and more aware of approaching to the pedestrian crossing. Pardon and Average (2013), investigated road accident problems and assessed the role of TCM s to reduce these accidents in Masvingo city. They pointed that 85% of accidents were attributed due to driver s fault and 15% due to pedestrian errors. To reduce these problems, vertical deflection type TCM s were used. They found a 70% reduction in accident rates in the city after implementation of redesigned measures. Rahman et al. (2005) had made a comparative study of design guidelines of TCM s, decision making process, their installation policy, and the evaluation process of the some popular TCM s in Japan. They made a before and after study of traffic, speed, accidents, traffic flow, environmental aspects and residents acceptability to evaluate the effects of TCM s. However, their study justified the efficiency of TCM s to reduce the vehicular speed, traffic flow, noise pollution, police enforcement, and rate of accidents and thus increase the safety of pedestrians and enhance the overall safety, the study also revealed that the installation of measures without proper design may create more problems such as increased noise pollution and vibration levels. Rahman et al.(2016)developed a point ranking system to prioritize traffic calming projects. This model explored the weight of variables during developing the point ranking system. The weights used in the point ranking system included vehicle speed, pedestrian generation, sidewalk condition and hourly vehicle volume per metre width of street. The http://www.iaeme.com/ijciet/index.asp 1138 editor@iaeme.com
Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective outcomes suggested that the severity of street largely depends on the absence of sidewalks, which had a weight of 45%, and high hourly vehicular volume of traffic per metre width of street, which had a weight of 38%. Tiwari (2004), examined the effectiveness of the TCM s on national highways and state highways and suggested that vertical deflection measures would be more effective than horizontal deflection type TCM s on Indian roads. Hydén and Svensson (2009) investigated pedestrian safety problems in the Indian city of Jaipur. The study shows that the intersections are highly unsafe for pedestrians, especially elderly pedestrians as at intersections. They proposed low cost measures such as speed humps, raised crosswalks, raised footpaths to enhance pedestrian safety and passages through medians of the same level as crosswalks. They asserted that with lower speed, traffic at intersections could be organized to enhance safety at intersections and further asserted that if average travel speed is reduced from 52 km/h to 40 km/h, the risk of pedestrians death can be reduced by 55%. Sahoo (2009) provided a method to design speed humps suitable for Bhuvaneshwar city of India. He developed two models that presented a statistical relationship between humps geometry and vehicular speed and used these models to develop a procedure to design humps for particular hump-crossing speed. It was found that the 85 th percentile speed has a stronger relationship with area to width ratio than height to width ratio. Gonzalo-Orden et al. (2016)showed the effectiveness in reducing speed of some of the TCM s and the researchers found that the TCM s that got the best improvements on lowering the speed were raised crosswalk and lane narrowing. 3. METHODOLOGY AND DATA COLLECTION The proposed methodology to evaluate the effectiveness of vertical deflection type TCM s involved the following steps. The first step was the identification of TCM s and site selection for the speed survey. Next step was the identification of the parameters to evaluate the performance of TCM s. The third step was the collection of data such as spot speed, peak hour traffic volume etc. To avoid bias and for minimizing error in the analysis, it was also important to have a rational size of the sample. After the collection of data required for research work, analysis of this data and parameters was necessary to evaluate the effectiveness of selected TCM s and their comparison. The assessment was based on data collected on selected roads of the Bhopal city in India. Spot speed data was collected at predetermined points on selected road sections where vertical deflection type TCM s was provided. Speed data was collected on weekdays during off-peak hours when the interaction between vehicles was less. The field work was carried out in daylight and good weather conditions to avoid bias in data collection. Five locations were chosen in the Bhopal city having single isolated vertical deflection type TCM. Table 1 presents the details of selected sites. In this research work, radar gun was used to measure spot speed of different vehicle classes at various TCM s. Speed profile assessment was done by measuring spot speed at 17 different points on either side of the vertical deflection type TCM s i.e. at a distance of 0m, 5m, 10m, 15m, 20m, 30m, 40m, 50m, and 100m. http://www.iaeme.com/ijciet/index.asp 1139 editor@iaeme.com
Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya Table 1 Selected Sites for Spot Speed Study Locatio n Observation Location 1. Link Road 3 2. 3. 4. Red Cross Link Road Red cross hospital Link Road 1 Main Road near DPS School Direction of Vehicular Movement Nehru Nagar to MANIT Junction Red Cross Hospital to Kalyani Girls Hostel New Market to Board Office DPS School to VNS College Classification of Street Arterial Road Distributor or Collector Road Arterial Road Arterial Road 5. Bairagarh Bhopal to Indore Arterial Road Existing TCM s Speed Bump Plastic Speed Bump Raised Cross Walk Rumble Strips Sinusoidal Speed Hump Geometry of TCM s H: 60 mm W: 450 mm H: 50 mm W: 350 mm H: 150 mm W: 5300mm H: 25 mm W: 300 mm H: 150 mm W: 3700mm 4. SPEED PROFILES FOR VERTICAL DEFLECTION TYPE TCM S Descriptive analysis on the spot speed data was performed and various parameters like free average speed, free 85 th percentile speed, average crossing speed, 85 th percentile crossing speed, maximum and minimum crossing speed of each vehicle class were calculated and are presented in Table 2. Comparison of the mean speed and 85 th percentile speed over distances at speed bump, plastic speed bump, rumble strips, sinusoidal hump, and raised crosswalk can be done easily from the speed profiles which are presented in Figure 1. For the vehicles manoeuvring the TCM s, the reduction in the speed of heavy motor vehicles and three wheelers is greater than the reduction in the speed of two wheelers and four wheelers. The slopes of the graphs represent deceleration (on the left side of 0 point) and the acceleration (on the right side of 0 point) between two data points. http://www.iaeme.com/ijciet/index.asp 1140 editor@iaeme.com
Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective Location Descriptive Statistics 1 2 3 4 5 Vehicle Class Vehicle Class Vehicle Class Vehicle Class Vehicle Class Table 2 Results of Descriptive Analysis performed on Speed Data Avg. Crossi ng Speed 85th Percen tile Crossi ng Speed Max. Crossing Speed Min. Crossin g Speed Varia nce Standa rd Deviati on Stand ard Error Stand ard Error in % Skewn ess Kurto sis 2W 21.22 27 35 16 19.92 4.46 0.7 3.31 1.11 0.3 4W 22.95 27 40 17 19.33 4.4 0.69 3.02 1.62 4.74 3W 21.05 24.15 29 13 10.87 3.3 0.52 2.47 0.1 0.25 HMV 23.18 27 29 15 10.81 3.29 0.51 2.24-0.54 0.18 2W 27.22 31 45 16 34.49 5.75 0.91 3.34 0.79 1.28 4W 24.57 30.15 37 16 35.53 5.41 0.85 3.45 0.68-0.067 3W 24.05 28 29 18 9.48 3.07 0.48 2.02-0.27-0.13 HMV 20.55 25.15 29 13 20.05 4.31 0.68 3.3 0.17-1.13 2W 21.17 25.15 31 17 11.17 3.34 0.53 2.5 0.93 0.59 4W 22.65 26.15 30 16 12.8 3.57 0.56 2.54 0.31-0.51 3W 17.87 22 26 9 19.34 4.39 0.69 3.86-0.36-0.61 HMV 12 14.15 18 7 5.94 2.43 0.38 3.16 0.24-0.09 2W 19.57 23 31 16 9.48 3.079 0.48 2.45 1.7 3.84 4W 22.17 25.15 30 16 11.68 3.41 0.54 2.43 0.52 0.037 3W 17.87 22 26 9 19.34 4.39 0.69 3.86-0.31-0.63 HMV 12.82 15 19 9 5.94 2.43 0.38 2.96 0.42-0.09 2W 22.68 28 36 16 7.153 2.67 0.74 1.82 0.25-0.51 4W 23.75 27.15 36 17 11.7 3.42 0.62 2.36 0.28-0.49 3W 22.1 25.15 30 13 10.87 3.29 0.57 2.47 0.04 0.2 HMV 23.93 27 29 16 5.74 2.39 0.44 2.3 0.45 0.79 http://www.iaeme.com/ijciet/index.asp 1141 editor@iaeme.com
Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya Figure 1 Speed Profiles of 85 th Percentile Speed at Various TCM s Fluctuations in speed profiles present the variations in drivers behaviour while manoeuvring the TCM. Speed profiles also reveal that influence ranges of TCM s are small and only within 60m. Steeper slopes in speed profiles are found for raised crosswalk, sinusoidal hump and rumble strips whereas gentle slopes are found for speed bump and plastic speed bump revealing that raised crosswalk, sinusoidal hump and rumble strip achieve high-speed reduction while speed bump and plastic speed bump realize low-speed reduction. 5. EFFECTIVENESS OF TCM S Speed reduction profiles show the reduction in free speed due to the influence of TCM s. The vehicle groups are considered as a single vehicle group and the overall speed reductions at TCM s is presented in Table 3. These results are computed by subtracting 85 th percentile crossing speed over TCM s from the free 85 th percentile speed. Further,higher reduction of speed was found for raised crosswalk, rumble strip, and sinusoidal hump than for speed bump and plastic speed bump. Further, the results showed the highest reduction in speed for rumble strip and lowest for plastic speed bump. http://www.iaeme.com/ijciet/index.asp 1142 editor@iaeme.com
S. No. Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective Traffic Calming Measure (a) Table 3 Speed Reduction Due to TCM s Overall 85 th percentile free speed (b) Overall 85 th percentile crossing speed ( c) Overall speed reduction in (d= b-c) Percentage reduction in Speed (%) (e) 1 Speed Bump 45 32 13 29 Low 2 Plastic Speed Bump 35 28.82 6.17 18 Low 3 Raised Cross Walk 48 21.86 26.13 55 High 4 Rumble Strip 60 23 35 60 High 5 Sinusoidal Hump 58 25 33 56 High Degree of Effectiveness 6. SPEED PREDICTION MODELS Speed prediction models were developed to represent the speed-distance relationships for the individual TCM s. The main intention was to develop a simple and practical relationship which would explain the effect of different TCM son speed using regression analysis. In this study, the dependent variable is the spot speed at any point representing the Y intercept in linear regression and the independent variable is the distance of that point from the TCM representing X intercept. Two models were developed for each type of TCM to represent the approach speed before the TCM on the upstream side and speed after crossing the TCM on the downstream side. The values of R 2 for speed prediction models developed were found higher than 0.90 which indicates less error and variance between predicted values and observed values. The developed models for approach speed and speed after crossing the TCM s are presented in Table 4 and Table 5 respectively. S. No. Table 4 Models for Approach Speed at the Upstream Side of TCM s TCM s Equation Representing 85 th Percentile Speed in kmph (V B(85) ) Equation Representing Mean Speed in kmph (V B(Mean) ) 1. Speed Bump V B(85) = 29.84-0.32X V B(Mean) = 25.08 0.29X 2. Plastic Speed Bump V B(85) = 30.66-0.12X V B(Mean) = 26.15-0.10X 3. Raised Crosswalk V B(85) =25.75-0.43X V B(Mean) =20.56 0.43X 4. Rumble Strips V B(85) =25.00-0.51X V B(Mean) =20.23 0.46X 5. Sinusoidal Hump V B(85) =25.54-0.55X V B(Mean) =21.14 0.47X S. No. Table 5 Models after Crossing the TCM s at Downstream Side Road TCM s Equation Representing 85 th Percentile Speed in kmph (V A (85) ) Equation Representing Mean Speed in kmph (V A (Mean) ) 1. Speed Bump V A (85) = 33.13+ 0.19X V A (Mean) = 25.54 + 0.19X 2. Plastic Speed Bump V A (85) = 29.00 + 0.15X V A (Mean) = 24.06 + 0.13X 3. Raised Crosswalk V A (85) = 26.97+ 0.37X V A (Mean) = 17.26 + 0.37X 4. Rumble Strips V A (85) = 19.07+ 0.58X V A (Mean) = 15.43 + 0.50X 5. Sinusoidal Hump V A (85) = 21.13 + 0.60X V A (Mean) = 17.89 + 0.52X http://www.iaeme.com/ijciet/index.asp 1143 editor@iaeme.com
Siddhartha Rokade, Rakesh Kumar, Varsha Rokade, Shakti Dubey and Vaibhav Vijayawargiya Validation of the developed models for all the TCM s under consideration was done and the results of regression analysis for approach speed at the speed bump are presented in Table 6. Table 6 Results of the Regression Analysis for Approach Speed at Speed Bump Coefficients Model Summary (85 th Percentile Speed of Speed Bump) R- Square: 0.88, Standard Error: 1.80 ANOVA Significance f: 5.83E-05, F- Statistics: 43 Constant Coefficient Standard error t-statistic p-value A 29.84 1.27 23.38 4.01E-07 B -0.32 0.047-6.734 0.00 Model summary (Mean Speed of Speed Bump) R-Square: 0.87, Standard Error: 1.67 ANOVA Significance f: 0.00, F- Statistics: 41 Coefficients Constant Coefficient Standard error t-statistic p-value A 25.0 1.22 20.49 8.77E-07 B -0.29 0.045-6.41 0.00 Similar analysis has been done for all the developed models. F-Statistic value tests overall significance of linear regression. At 5% level of significance, the critical value is 1.85. In all cases of regression analysis of spot speed data at different TCM s, f-value is higher than the critical value. Hence, the null hypothesis is rejected in each case. Significance f also supports the hypothesis that a proposed regression model fits the data well. In all cases of regression analysis, significance f was found less than 0.05. Further, the p-value was found to be less than 0.01, which indicates a strong presumption against the null hypothesis. In regression models for each type of TCM s, the p-value was found to be less than 0.01 except in the cases of plastic speed bump but in these cases also p-valuewas found to be less than 0.05. Hence, in each case of the regression analysis null hypothesis was rejected. 7. CONCLUSIONS In order to make urban roads safer, traffic calming is one of the most fundamental methods. Vertical deflection type TCM s are one of the most commonly used means for traffic calming worldwide. The five types of vertical deflection type TCM s used in this study were analysed on the basis of their effectiveness in reducing the speed of vehicles manoeuvring over them. From the present study, it is concluded that rumble strips, raised crosswalk and sinusoidal hump are highly effective in speed reduction than speed bump and plastic speed bump. http://www.iaeme.com/ijciet/index.asp 1144 editor@iaeme.com
Assessment of Effectiveness of Vertical Deflection Type Traffic Calming Measures and Development of Speed Prediction Models in Urban Perspective Further, the speed profile curves depict that greater reduction in speed was achieved in the case of rumble strip for HMV s. The crashes of HMV s with slow moving traffic has been a predominant reason for the enhanced number of fatalities in the mixed traffic conditions prevailing in the developing nations. The raised pedestrian crosswalk was found to effectively reduce the speed of 3W, 4W, and HMV s. The highest reduction in the speed of 2W was found in the case of rumble strips. Similarly, the highest reduction in the speed of 3W, 4W, and HMV s was found for raised crosswalk, sinusoidal hump and rumble strips respectively. Hence, the selection of a particular type of vertical deflection type TCM can be done on the basis of a particular vehicle class manoeuvring over the TCM. The assessment of the influence zones of the TCM s can also be effectively done by the speed prediction models developed in the study. REFERENCES [1] Abdel-Wahed, T.A. and Hashim, I.H., 2017. Effect of speed hump characteristics on pavement condition. Journal of Traffic and Transportation Engineering (English Edition). [2] Ahmed, A & Bagchi, R 2013. Traffic calming in Indian perspective, International Journal of Chemical, Environment & Biological Science, vol. 1, no. 3, pp. 463-467. [3] Bekheet, W., 2014. Short term performance and effect of speed humps on pavement condition of Alexandria Governorate roads. Alexandria Engineering Journal, 53(4), pp.855-861. [4] Chaturvedi, P., 2006. Challenges of occupational safety and health: thrust: safety in transportation. Concept Publishing Company. [5] Daniel, B.D., Nicholson, A. and Koorey, G., 2012, September. The effects of vertical speed control devices on vehicle speed and noise emission. In ARRB Conference, 25th, 2012, Perth, Western Australia, Australia. [6] EC-European Commission, 2010. Towards a European road safety area: policy orientations on road safety 2011-2020. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, COM (2010), 389. [7] Elvik, R., Christensen, P. and Amundsen, A., 2004. Speed and road accidents. An evaluation of the Power Model. TØI report, 740, p.2004. [8] Gonzalo-Orden, H., Rojo, M., Pérez-Acebo, H. and Linares, A., 2016. TCM s and their Effect on the Variation of Speed. Transportation Research Procedia, 18, pp.349-356. [9] Hydén, C. and Svensson, Å., 2009. Traffic Calming in India: Report on the theory of Traffic Calming and empirical trials in the city of Jaipur. Bulletin/3000. [10] Jateikienė, L., Andriejauskas, T., Lingytė, I. and Jasiūnienė, V., 2016. Impact assessment of speed calming measures on road safety. Transportation Research Procedia, 14, pp.4228-4236. [11] Johansson, C., Rosander, P. and Leden, L., 2011. Distance between speed humps and pedestrian crossings: Does it matter?. Accident Analysis & Prevention, 43(5), pp.1846-1851. [12] Juhász, M. and Koren, C., 2016. Getting an insight into the effects of traffic calming measures on road safety. Transportation Research Procedia, 14, pp.3811-3820. [13] Lockwood, I.M., 1997. ITE traffic calming definition. Institute of Transportation Engineers. ITE Journal, 67(7), p.22. [14] McDonald, T. and McDonald, P., 2010. Guide to Pavement Maintenance. I Universe. [15] Ministry of Road Transport and Highways, Road Accidents in India, Ministry of Road Transport and Highways (MORTH), New Delhi, 2015. http://www.iaeme.com/ijciet/index.asp 1145 editor@iaeme.com
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