WHY AND WHEN PEDESTRIANS WALK ON CARRIAGEWAY IN PRESENCE OF FOOTPATH? A BEHAVIORAL ANALYSIS IN MIXED TRAFFIC SCENARIO OF INDIA.

Transcription

1 WHY AND WHEN PEDESTRIANS WALK ON CARRIAGEWAY IN PRESENCE OF FOOTPATH? A BEHAVIORAL ANALYSIS IN MIXED TRAFFIC SCENARIO OF INDIA. Sobhana Patnaik, Mukti Advani, Purnima Parida.

2 There are reasons for walking on Footpath

3 There are reasons for walking on main road (Carriageway) and not on Footpath

4 Usage of carriageway by pedestrians is a common site in urban Indian roads. Present study focuses on the effect of traffic characteristics and road side amenities, on pedestrians decision of walking on the footpath or on the carriageway with a case study of an urban road located in Badarpur border, New Delhi.

5 Objective of the study Analyzing pedestrian decision making behavior with respect to vehicle traffic. Analyzing pedestrian decision making behavior with respect to presence of hawkers. Developing binary logit model for pedestrian preference. Developing model to measure pedestrian level of service.

6 Methodology

7 Study area characteristics Two lane undivided road with footpath on both sides.

8 Traffic movements are From Okhla towards Faridabad (Left hand side i.e. LH) From Faridabad towards Okhla (Right hand side i.e. RH) Accordingly the carriageway width has been divided into two halves by an imaginary line for the study.

9 Traffic Characteristics Major contributors of the vehicle volume are, cars (passing the 2/minute) and motorized two wheelers. The site experiences heavy pedestrian footfall with more pedestrians walking on the part of carriageway on left half of the study section(from Okhla towards Faridabad).

10 Descriptive Analysis Study of pedestrian preference(footpath/carria geway) With respect to vehicle space occupancy With respect to hawker space occupancy

11 Effect of vehicle space occupancy on pedestrian decision making behavior 90 Percentage pedestrian flow on footpath Percentage space occupied by vehicles

12 Effect of space occupied by hawkers on pedestrian decision making behavior Percentage pedestrian flow on footpath Percentage of pedestrian flow on footpath Percentage space occupied by hawkaers Percentage space occupied by hawkers Percentage space occupied by vehicles in morning and afternoon hours

13 Opinion of the pedestrians 63.33% of the pedestrians out of a sample size of 200, stated that, they are using the footpath to avoid heavy vehicle traffic and only 12.33% are stating that the footpath is comfortable. Pedestrians have also stated their reasons for using the carriageway.60% of pedestrians out of a sample size of 200 are stating that the footpath surface is not good.52% of them are saying that the footpath is congested and 44% of them have stated the presence of hawkers as a reason.

14 Significance Testing

15 Binary logistic regression model for pedestrians preference With p-value of 0.001,hawkers are becoming significant in pedestrians decision to walk on the footpath or on carriageway. Model is validated by Hit ratio method. The value of Hit Ratio obtained is 0.74.

16 Pedestrians walking on carriageway due to hawkers even when vehicle traffic is high! Pedestrians walking on the footpath to avoid the vehicle traffic!

17 Proposed pedestrian level of service model (PLOS) LOS score value = [(Pf * Spf)] [(Pc * Svo)] Where, Pf = Percentage of pedestrians walking on the footpath Spf =space available per pedestrian on footpath Pc =Accounts for percentage of pedestrians walking on carriageway (It is 0 if no pedestrians are walking on the carriageway and 1, if pedestrians are observed on the carriageway) Svo = score for space occupied by vehicles (on carriageway)

18 Score for vehicle space occupancy

19 Proposed LOS criteria

20 Application of the PLOS Model to the study area Scenario 1: Existing situation Scenario 2: Layout assumed, such that all pedestrians are walking on the footpath. PLOS model is used to compare the alternate layouts.

21 Comparison of both the scenarios in terms of LOS

22 Conclusions The quality of walking facility provided is not good. Hence, pedestrians are using the footpath only when motor vehicle traffic is high. Pedestrians using the carriageway in presence of hawkers, irrespective of the intensity of motor vehicle traffic, indicates that they are willing to access the facilities provided by hawkers. The developed model for measuring pedestrian level of service includes percentage of pedestrians walking on footpath, area module on footpath and pedestrians walking on carriageway.

23 Conclusions On application of the developed model to the study location, it shows that the walking facility provides a better level of service when all pedestrians are walking on the footpath. In order to improve the level of service further, due consideration should be given to increase the width of the walking facility. The quality of the walking facility should also be improved. A thought should also be given to introduce hawkers as a separator between the pedestrian traffic and motorized traffic instead of providing physical barriers like guard rails in the narrow Indian roads.

24 Future Scope of Work The authors understand that, the results obtained from this study cannot be generalized as it is focused on a single location. In order to make the study more generic, data from such similar locations can be collected to cover a larger sample size. The developed PLOS model, can further be improvised by considering more parameters and statistical methods.

25 Key References Study on Traffic and Transportation Policies and Strategies in Urban Areas in India, Ministry of urban development May Parida, P., Najamuddin, Parida, M. (2007). Development of qualitative evaluation methodology for sidewalks in Delhi, ITPI Journal 4:3(2007) Parida, M.(2014).Review report for Indian Highway Capacity Manual. Held on 2nd August 2015 at CSIR-Central Road Research Institute. Advani, M.,Nisha, G.(2013). Behavioral analysis of pedestrians for walking on footpath and on carriageway in space-sharing traffic scenario. Indian Road Congress, Indian Highways, volume 41, No 7, July 2013.

26 Thank you

27 Concepts Continued Vehicle space occupancy(in present investigation) is the percentage of carriageway space occupied by vehicles (motorized or non motorized). Usually calculated by selecting an area of carriageway of known dimensions, calculating the area of each vehicle present within that area at a particular moment and taking the percentage of total vehicle area on the area of carriageway.

28 Concepts Continued Hawker space occupancy(in present investigation) is the percentage of carriageway/footpath space occupied by hawkers. Usually calculated by selecting an area of carriageway/footpath of known dimensions, calculating the area occupied by each hawker on the carriageway/footpath present within that area at a particular moment and taking the percentage of total hawker area on the area of carriageway/footpath.

29 Research Gaps The Walkability Index proposed by Ministry of Urban Developement, India(2008), accesses how friendly an area is to walking. The Central Road Research Institute of India (Parida, 2007) has proposed a measurement tool which calculates the pedestrian LOS based on a mix of physical characteristics and user ratings. These methodologies assess the walking facilities considering the quality, environmental and social parameters from the experts perspective.

30 Why this study Lack of understanding what people need for space can be an obstacle for planners to create a better urban place. For a country like India where motorization has accelerated the urban sprawl and decline of the city centers there is a need to study pedestrian walking behavior and pedestrian movement. It is not well known how the traffic characteristics or facilities of an area influence the pedestrian walking behavior.

31 Criteria for selection the of site The criteria for the selection of the site is, its high pedestrian count and considerable motorized traffic movement. The carriageway is occupied by hawkers and pedestrians are observed walking on the carriageway along with motorized traffic.

32 Pedestrians stated reasons for walking on the carriageway

33 Pedestrians stated reasons for walking on the Footpath

34 Vehicle speed data

35 Classified traffic volume count

36 Pedestrian count

37 Pedestrian speed The free-flow speed for LF is m/min and for RF it is m/min which is higher than the normal walking speed i.e. 72m/min to 90m/min.

38 Summary of flow characteristics

39 Fundamental diagrams

40 Speed-flow relation when there are few pedestrians on a walkway (i.e., low flow levels), there is space available to choose higher walking speeds. As flow increases, speeds decline because of closer interactions among pedestrians. When a critical level of crowding occurs, movement becomes more difficult, and both flow and speed decline.

41 Flow density relationship All observation of maximum unit flow fall within a narrow range of density, and afterwards with increase in density flow declines. Flow is basically how many people are moving on per minute basis. For a narrow range of density, with increase in density, flow increases. And at this location, what is observed is speed is not getting affected by flow, but some other reasons. due to environment, emotional state etc. One eg. can be walking speed at cross walk is becoming higher compared to that of sidewalk due to environmental reasons Studies done earlier have also highlighted the effect of culture, populatoion size, traffic intensity and vegetation on pedestrian flow characteristics.

42 Logistic regression models Direct probability model Used to model binary response At this study location, Users have two options walking on footpath/ walking on carriageway The probability of choosing one, can be modelled by using binary logistic regression. A predictor variable is a variable used in regression to predict another variable. It is sometimes referred to as an independent variable if it is manipulated rather than just measured. Variables of interest in an experiment (those that are measured or observed) are called response or dependent variables