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IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS By K.R. Vinodh Kumar, Dr.

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Presentation on theme: "IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS By K.R. Vinodh Kumar, Dr."— Presentation transcript:

1 IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS IMPACT ASSESSMENT OF BUILT ENVIRONMENT ON PEDESTRIAN ACCIDENTS By K.R. Vinodh Kumar, Dr. Nisha Radhakrishnan* Dr. Samson Mathew** Department of Civil Engineering National Institute of Technology Trichy, India. 1

2 2 National Institute of Technology Tiruchirappalli, INDIA

3 WHO reported that over 1.2 million people die each year on the worlds roads and 50 million suffer non-fatal injuries. It also predicted that road traffic injuries will rise to become the 5 th leading cause of death by 2030. Pedestrians, cyclists, drivers of motorized Two – wheelers and their passengers account for almost half of global road traffic deaths. 3

4 4

5 Road Trafc injuries are one of the top three causes of death for people aged between 5 and 44 years. 5

6 Pedestrians share a high percentage in road user fatalities. They are exposed to severe consequences of road accidents than other road users. Pedestrian safety is often an afterthought. Road facilities in urban areas are still an important source of harm to pedestrians. 6 Pedestrian Safety???

7 Factors associated Identification of interventions Remedial measures 7 Accident Reduction

8 Active EducationEnforcement Passive Largely involve modifications to the Built Environment (BE) 8 Education and enforcement cannot be the only measures taken to reach a sustainable road safety. Local Environment and road infrastructure play a substantial role in the co-occurrence of road accidents.

9 Built Environment refers to the structures, and infrastructure, that are made by man. Transportation Built Environment - includes road infrastructure, pedestrian infrastructure and streetscape like crosswalk, pedestrian signals, median, refuge island etc which has its influence on the pedestrian activity. 9

10 Crosswalk lighting & signal Refuge islandRoad narrowing Reducing Accidents 10 Examples of BE

11 Curb parking Flora Obstruction Causing Accidents 11 Examples of BE

12 12 Midblock with no crosswalks, traffic calming measures Causing Accidents Examples of BE Long walking distance – Absence of Median/Refuge island

13 A total of 4,30,654 Road Accidents reported during the year 2010. These accidents caused 1,33,938 deaths. 5.5% increase in Accidental Deaths. Tamil Nadu, Andhra Pradesh and Maharashtra have accounted for 11.5%, 10.5% and 7.1% respectively of total Road Accident deaths. Source : National Crime Records Bureau 13

14 Pedestrians are more exposed to accident fatalities caused by the motor vehicles than any other means. Studies have been done relating the factors like Traffic volume, speed, etc., with the pedestrian accidents – ignoring other factors especially BE elements. Measures to identify and rectify those factors prove to be difficult or very expensive in the field by means of ITS implementation and monitoring. 14

15 To study the impact/influence of Built Environment on Pedestrian safety. To collect pedestrian accident data and to map the accident spot in Tiruchirappalli city base map. To identify location of high density pedestrian crashes using spatial analysis technique. To conduct Built Environment Audit along the identified hotspots. To analyse the influence of the each Built Environment elements on Pedestrian accident occurrences by Logistic Regression modelling. 15 Objectives

16 Source: Tiruchirappalli city corporation 16 Study Area INDIA TAMILNADU

17 Accident Data collection Identification of Modifiable BE elements Filtering Pedestrian Accidents & Data analysis Preparation of BE Audit Data Sheet Conducting BE Audit Geo-coding all the accident spots 176/2/2014 Methodology Spatial Analysis of Accident spots Land use classification of Hotspots Developing a statistical model Suggestions for improvements

18 Source : Traffic Control Room, Trichy 18 Mode Wise Distribution of Fatalities in Trichy City (2009 - 2011)

19 19 Source : Traffic Control Room, Trichy Mode Wise Percentage of Pedestrian Accidents (2009 – 2011)

20 Accident Spots Besides identifying locations of pedestrian crashes, detecting the high-density zones, which refers to the number of pedestrian crashes per unit of road segment, is critical for an intervention program. Although pedestrian safety in a motorized urban environment is important throughout a city, public health interventions prioritized at these high density zones are paramount to make accident reduction efforts more effective Creation of Density map is essential to identify critical zones. 20 Accident Spot location

21 Density surfaces show where point or line features are concentrated. Cell Values of Population Density For Example 21 Density analysis and density Map

22 Determine if points (events) are exhibiting specific pattern over study area or are they randomly distributed. Estimate the intensity (density) of how the point pattern distributed over the study area. Intensity = Mean number of events per unit area at points defined as the limit. Search radius of 150m was adopted for the analysis. 22 Kernel Density

23 Kernel Density Map Airport Ariyamangalam Puthur 4 road Gandhi market Toyota showroo m TV koil 23

24 This tool measures spatial autocorrelation (feature similarity) based on both feature locations and feature values simultaneously. It evaluates whether the pattern expressed is clustered, dispersed, or random. The tool calculates the Moran's I Index value and a Z score evaluating the significance of the index value. 24 Spatial Autocorrelation

25 Moran's Index value near +1.0 indicates clustering while an index value near -1.0 indicates dispersion. - 1.0+ 1.00 25 Morans I Index

26 26 Morans I Index & Z Score

27 List of Identified Hot Spots 1.Ariyamangalam - SIT Bus stop 2.Ariyamangalam - Rice mill Bus stop 3.Ariyamangalam - Rail Nagar Bus stop 4.Airport - J K Nagar intersection 5.Airport – Wireless Rd 6.Pudhukottai Rd – Ponmalaipati Rd intersection 7.TVS Tollgate intersection 8.Rockins – Mc Donalds Road intersection 9.Rockins – Melapudur Rd intersection 10.Rockins – HPO Rd intersection 27 11. Lawson – Bharathidasan road intersection 12. Reynolds – Lawson road intersection 13. Puthur 4 road intersection 14. Gandhi market – Big bazaar street intersection 15. Chatram Bus stand intersection 16. Chennai bypass – Kallanai road intersection 17. Chennai bypass – Kodayampettai intersection 18. T V Koil intersection 19. Chennai trunk road – Kollidam intersection List of Identified Hot Spots

28 28

29 1.Curb Parking 2.Crosswalk 3. Lighting 4.Bus Stops 5.Pedestrian Signals 6.Flora Obstruction 7.Speed Humps 8.Road Width 9.Sidewalk 10.Median 11.Refuge Island 12.Instruction Signs 13.Advance Stop lines 14.Pedestrian Barriers 15.Branding Signs 16.Alcohol Serving Establishments 17.Educational Institutions 18.Industrial areas 19.Commercial areas 20.Residential areas 29 List of Built Environment Elements Considered

30 Built Environment??? 30

31 31 Built Environment???

32 32 Format of Environment Audit Sheet

33 33 Findings of Environment Audit Survey

34 34 30m Linear Buffer Pedestrian Accidents Hotspot Linear Buffering

35 35 Land Use Classification

36 36 Land Use Classification 10m Buffer

37 37 Land Use Classification 20m Buffer

38 38 Land Use Classification 30m Buffer

39 39 Change in Residential area

40 40 Change in Commercial area

41 Used to analyze relationships between a dichotomous dependent variable and metric or dichotomous independent variables. Combines the independent variables to estimate the probability that a particular event will occur or not. Finds the impact of each independent variable on dependent variable. 41 Logistic Regression in SPSS 20

42 Indicator 1.Curb Parking 2.Crosswalk 3. Lighting 4.Bus Stops 5.Pedestrian Signals 6.Flora Obstruction 7.Speed Humps 8.Road Type 9.Sidewalk 10.Median 11.Refuge Island 12.Instruction Signs 13.Advance Stop lines 14.Pedestrian Barriers and Fences 15.Branding Signs 16.Alcohol Serving Establishments Continuous 1.Educational areas 2.Public areas 3.Commercial areas 4.Residential areas 42 Independent Variables

43 43 Logistic Regression in SPSS

44 44 ScoredfSig. VariablesCURB PARKING(1).0101.919 CROSSWALK(1)21.4301.002 LIGHT(1)15.1301.000 BUS STOP(1)19.9521.003 PEDESTRIAN SIGNAL(1)23.6731.000 LONGBLOCKS(1)1.5131.219 ROAD TYPE(1)4.8211.004 SIDEWALK(1)30.0451.001 MEDIAN(1)12.0331.002 REFUGE ISLAND(1).9521.329 INSTRUCTION SIGN(1).1591.690 ADVANCE STOPLINE(1)8.1431.003 PEDESTRIAN BARRIERS(1)31.8571.001 BRNDING SIGN(1)2.0101.919 ALCOHOL SHOP(1)44.5401.000 RESIDENTIAL AREA17.1401.004 COMMERCIAL AREA24.0001.003 EDUCATIONAL AREA1.3411.559 PUBLIC AREA3.1291.719 Variables are removed due to insignificance Significance of Variables

45 45 BS.EWalddfSig.Exp(B) Step 1Variables CROSSWALK(1)0.2340.03253.4731.0000.0001.264 LIGHT(1)0.1130.02324.1381.0000.0011.120 BUS STOP(1)-1.0250.5603.3501.0000.0300.359 PEDESTRIAN SIGNAL(1)1.2360.16357.4991.0000.0153.442 ROAD TYPE(1)0.0890.0801.2381.0000.0221.093 SIDEWALK(1)2.4530.35049.1201.0000.00011.623 MEDIAN(1)0.8970.3217.7991.0000.0032.452 ADVANCE STOP LINE(1)0.2340.1432.6781.0000.0141.264 PEDESTRIAN BARRIERS(1)2.6210.28584.5751.0000.02813.749 ALCOHOL SHOP(1)-1.8310.18696.9061.0000.0180.160 RESIDENTIAL AREA-0.0210.00427.5631.0000.0000.979 COMMERCIAL AREA-0.0370.00638.0281.0000.0040.964 Constant1.3420.38712.0251.0000.0213.827 Variables in the Equation a Block 1 - Final Model

46 46 VariablesIncreases*Decreases* Pedestrian Barriers13 times Sidewalk11 times Pedestrian Signal3 times Alcohol shop84% Bus Stop65% Residential Areas2.1% Commercial Areas3.6% * Chances of not having Pedestrian Hotspots Important Findings

47 47 Accuracy of the test Step-2 Log likelihood Cox & Snell R Square Nagelkerke R Square 069.9410.5010.485 155.4480.7090.822 Model Summary -2Log likelihood is a measure of error associated with the model in predicting the dependent variable and its value should be as low as possible. Cox & Snell R square and Negelkerke R square are the two pseudo R squares used to measure the fitness of model in Logistic Regression.

48 Classification Table Observed Predicted ACCID Percentage Correct 01 Step 1 ACCIDENTS < 3 ACCIDENTS > 3 08372.2 131684.2 Overall Percentage85.0 48 Model Validation

49 Total No. of Accidents occured in Puthur – 5 Y=1.342+0.234*(CRSSWLK)+0.113*(LIGHT)+1.025*(BST OP)+1.236*(PEDSIG)+0.089*(ROADW)+2.453*(SIDEW)+ 0.897*(MED)+0.234*(ASTOPL)+2.621*(BANDF)- 1.831*(ALCSHP)-0.021*(RESI)-0.037*(COMM). Y=1.342+0.234*(1)+0.113*(1)+1.025*(1)+1.236*(1)+0.0 89*(1)+2.453*(1)+0.897*(1)+0.234*(1)+2.621*(1)- 1.831*(1)-0.021*(0)-0.037*(3780). Y= -0.5481 P(X)=1/(1+e(P-Y)) = 0.98 (Prob. having of less than 3 accident occurrence) 49 For Puthur 4 Road

50 Integrated Geospatial-Statistical analysis employed to analyse the pedestrian fatalities with respect to Built Environment elements along Tiruchirappalli road network. The analysis proved to be effective in providing the following information 86% of pedestrian fatalities were observed in intersections and rest of them in mid blocks. Examination of Built Environment elements in the hotspot showed that they had lack of pedestrian infrastructure. The residential area increases as we move away from the road. The commercial area decreases as we move away from the road. The commercial area is having higher impact on pedestrian activity than any other. 50 Conclusions

51 Pedestrian Barriers, sidewalk and pedestrian signals are having higher impact on the accident reduction. Alcohol Shops and bus stops are increasing the chances of accidents to greater extent. Absence of speed calming measures has been observed to have a negative influence on pedestrian safety The study helps in identifying the effective Built Environment in reducing the accident occurrence provides information to Improve the hotspots in terms of modifying the Built Environment which would seem to be effective and easy in implementation. 51 Conclusions ( Contd….)

52 Constructing Barriers can prove to be more effective in avoiding uncontrolled pedestrian crossings. Paving the Sidewalk will reduce the pedestrian vehicle interaction. It avoids the pedestrian to walk on the road. Avoiding the Bus stops near the intersections. It should be located at least 150 m away from the intersection so that the intersection traffic will not much affect the pedestrian movement. Avoiding Alcohol serving establishments around the intersection. 52 Suggestions for Improvement

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