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Ms. Himani Jain, Project Scientist, Indian Institute of Technology, Delhi, India

BICYCLISTS: BEHAVIOUR AND SAFETY Case of Pune, India. Ms. Himani Jain, Project Scientist, Indian Institute of Technology, Delhi, India. Supervised by – Dr. Geetam Tiwari TRIPP, Faculty Professor, Civil Engg. Dept., IIT Delhi. Contents. INTRODUCTION BICYCLISTS PERCEPTIONS

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Ms. Himani Jain, Project Scientist, Indian Institute of Technology, Delhi, India

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  1. BICYCLISTS: BEHAVIOUR AND SAFETY Case of Pune, India Ms. Himani Jain, Project Scientist, Indian Institute of Technology, Delhi, India Supervised by – Dr. Geetam Tiwari TRIPP, Faculty Professor, Civil Engg. Dept., IIT Delhi

  2. Contents INTRODUCTION BICYCLISTS PERCEPTIONS ROUTE CHOICE MODE CHOICE POLICY CONCLUSIONS

  3. Indian context • Medium and large Indian city- different then American cities or cities of Europe. • Medium densities, low car ownership, low and middle income of Indian cities have high possibility of bicycle usage. • Mixed land use, poly-nucleated / multi-CBD and high proportions of informal housings and employment sectors present ideal short commuting trips

  4. 2000’s 1980’s 1990’s Context – India medium (3-5 m) and large cities (5-8 m) Travel pattern conducive to biking Vehicular ATL (excluding walk) 4.2 – 6.9km Bicycles ATL - 3.1 – 4.5 km Short Trips < 6km (including walk) 56 - 72% Source: Tiwari and Jain, 2008 Modal share for bicycle is going down Bicycle ownership is high 35 -65% bicycle involved in fatal crashes 8-14% No dedicated facilities for bicycles Source: ORG, 1998

  5. Captive and potential groups • Low income households (slums/ JJ colonies, LIG Colonies, urban villages) • 10 - 50% households in cities • Household income 80-150 Euros/month • Motorized public transport (bus)- not an affordable option CAPTIVE RIDER GROUP • High density (planned and unplanned) • Short trips due to mixed land use • School and college students • High ownership of bicycle, low car ownership and low-middle incomes POTENTIAL RIDER GROUP

  6. The cycle user • There are about 314% higher odds associated with bicycle usage when higher order modes are un-available and shortest route can be used. • 608% higher odds for a male who is a worker and travelling 12-14 commuting trips per week for being a cyclist • There are 22% higher odds for using a cycle if access to grocery stores, social and recreational place or tuition is more than ~15 minutes by walk. • There are about 64% lower odds for using a bicycle when there are more adults and or children who need to share the trip. • There are about 77% lower odds associated with bicycle use when education/income and age are higher for an individual.

  7. The cyclist The physical infrastructure USAGE: The cycle modal share Interventions The street surroundings/ environment The framework • The interaction between the three • Any intervention made in the transport system like bicycle friendly infrastructure and or worsening alternate modes, will have direct and indirect impacts

  8. An appropriate measure of routes/ streets require people's perception evaluation (safety, comfort and social security); differentiating among captive riders and potential users.

  9. Cyclists vs. Potential users (Jain et al 2010a)

  10. Predominant Barriers

  11. Ranking analysis

  12. Street environment and land use play an important role in cyclists route choice. (Type of built environment, density, land use intensity/mix, presence of informal sector etc.)

  13. Results (street Environment)

  14. Conclusions (based on Odds)

  15. Policy interventions – CAPTIVES SHORT TERM – • Pavement quality and street side parking require immediate attention. • Deterrents - Buses in the curb side lane and high speed of MV. • Land use mix (up to 20%),old city and informal sector predominant areas are preferred as current bike routes.Bicycle tracks are most conducive to bicycling. • The roads which are wide with footpaths are more used by cyclists.

  16. Policy effects – POTENTIAL USERS • LONG TERM – • Proper planning of informal sector and pedestrians is must to attract choice users. • Adequate Lighting and pavement quality on streets for enhanced security perception • Bicycle network incorporating NMV friendly intersections • The bus service presence, number of bus stops per kilometres and average speed of the buses - negatively correlated with the bicyclists

  17. Safe routes / infrastructure lead to substantial modal shifts to bicycle.

  18. Modal Shifts

  19. Results • Safety has comparable and highest weight age by both groups • Potential users attach very high positive value to comfort as compared to captives • Captives attach high value to cost and travel time • Lower odds of shifting when the bicycle travel time is higher. – • Dedicated tracks, priority at intersections, parking closer to destination etc are important incentives to prioritize bicycle • Odds are higher for remaining with own vehicle, evenwhen the travel costs are little higher.- • higher penalty costs (through fuel / parking etc)

  20. Willingness to pay

  21. CONCLUSIONS

  22. Bicycle Compatibility Policies • Street environment/operations aspects for designing bicycle compatible infrastructure in near future. • At the local and the neighborhood level, planning policies can be used to influence the density and layout of development. • Ultimately the use of bicycle has to be by choice. • The insights for choice users can be useful in planning and designing strategies to attract the large potential of short trips. • The possibility of theft and the social security issues also contribute to the overall low levels of cycling.

  23. Acknowledgements • Partly funded by - • Volvo Research Education Foundations (VREF) • Cycling Academic Network (CAN) scholarship • MoUD, Govt. of India (CoE Urban Transport grant to IITD) Ministry of Urban Development Govt. of India • Supported by - • Civil Engg. Dept. and Transportation Research and Injury Prevention Program (TRIPP), IIT Delhi, India • Faculty of Geo-information Science and Earth Observation (ITC); University of Twente (UT), NL

  24. THANKS ! CEZ 8168, 2007, IIT Delhi, India himani.iit@gmail.com

  25. SURVEY Zoning Zoning – Residential • within 1km distance • within 3km distance • within 5 km distance • Informal (slums) Certain mix of • Commercial • Industrial • Public - Semi Public • Recreational/ Vacant /Agric • Urban villages • IT Parks/Defense Census wards and the PMC land use map as base. Further breaking up made 417 zones (approximately 0.25 sq km to 0.44 sq km except for large slums, greens, cantonment areas and industrial sites) Zone number 36 is considered as the city center (Laxmi road) and radius is approx 7 Km. Zones falling under river, cantonment etc. are not considered

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