Road Accidents, Police Performance, and Modern Technology

Transcription

1 Road Accidents, Police Performance, and Modern Technology A Collaboration Between: The Rajasthan Police and The MIT J-Poverty Action Lab

2 Overview An old problem Road accidents killed more than 9100 people in Rajasthan in 2010, and injured more than 31,000. A modern solution Our initiative is India s first rigorous evaluation of the use of 2 modern technologies in policing: Breath analyzer devices GPS monitoring Collaboration between Rajasthan Police and Massachusetts Institute of Technology (USA). Program conducted in 183 police stations across 11 police districts: 1. Alwar 5. Bhilwara 9. Jodhpur 2. Ajmer 6. Bikaner 10. Sikar 3. Banswada 7. Bundu 11. Udaipur 4. Bharatpur 8. Jaipur Rural

3 Three Main Questions 1. Are checkpoints with breath analyzers effective in reducing road accidents and deaths? 2. Which personnel should carry out checkpoints? Normal thana staff Dedicated staff 3. Which locations should the police target for drunken driving checkpoints? Always at the best location to catch drunks Alternate locations to maintain element of surprise

4 Personnel Effectiveness We tried two different kinds of teams: 1. Thana teams: Teams from local thana carry out checkpoint (standard Rajasthan Police procedure). Monitored by normal police chain of command. 2. Lines teams: Dedicated teams from police lines travelled to thanas to carry out checkpoints. Monitored by: Normal police chain of command GPS device installed in police lines vehicle: Vehicle location visible in real time at SP s office/control room

5 GPS Tracking: J-PAL purchased 22 vehicle-based GPS devices (TrackingGenie) Device features: Provides real-time information about vehicle location Maintains a record of vehicle s travel history Displays GPS information via an online Google Maps portal accessible to District Police, J-PAL researchers

6 Checkpoint Locations All checkpoints held from 7:00pm-10:00pm 1. Fixed checkpoints Always held at same location. Location chosen by SHO as best for reducing drunken driving accidents. 2. Surprise checkpoints Location rotates randomly between 3 top locations chosen by SHO for stopping drunk drivers. Example: District Station Strategy Location 1 Location 2 Location 3 Jaipur Kalwad Road Thane Jobner Surprise College Tiraya Bauraj Tiraya Rural ke Paas Jaipur Samod Surprise Samod Bus Stand MhaurTiraya Rural Jaipur Purana Phulera Kaachroda Phatak Rural Phulera Surprise Churaya Maurija Road Kaaglya Hanuman Ji Ke Paas Bus Stand Ke Paas Etc

7 Strategy: Hard Data J-PAL and Police collected objective evidence from a variety of sources: Police accident data Daily accidents from 1/8/2010 to 31/12/2011 Monthly accident data till February, 2012 Independent checkpoint monitors Number and type of vehicles passing, stopped, and given challan for drunk driving. Attendance and timing of police at checkpoint. Court records on drunk drivers legal outcomes Date, vehicle type, alcohol level of driver. Whether driver acquitted or fined, and fine amount.

8 Strategy: Randomization 183 police thanas randomly assigned to different teams and different strategies, with 60 kept as control. Why randomize? Treatment and control groups are as similar to each other as possible. Outcomes in control group provide accurate comparison for measuring outcomes in treatment group. Program can be implemented in any police thana not just the best or the worst.

9 Context for Results: On average, from August 2010 to December 2011, police stations had: 3.7 accidents per month 1.5 deaths per month Out of these, 1.1 accidents occurred at night..54 deaths occurred at night.

10 Which vehicles should police stop at checkpoints? 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Percentage of Stopped Drivers Found Drunk By Vehicle Type Motorcycles Cars Trucks Luxury Cars Overall: 2.23%

11 What day should checkpoints be held? Percentage of Stopped Drivers Found Drunk By Day of Week % found drunk Sunday Monday Tuesday WednesdayThursday Friday Saturday Note: data from surveys held during program period. Absolute percentages may be unreliable.

12 Results Accidents & Deaths

13 Interpreting Graphs For each outcome, we have: 1. An estimate of how big the effect is 2. A confidence interval around that estimate: With 95% probability the true effect lies in the confidence interval. Example: 0% -5% Our best estimate of the effect -10% -15% -20% -25% -30% Effect lies in this range with 95% probability

14 Accident Results Overall Results Small effects during program period max 15% reduction in deaths at night Larger effects on all outcomes after the program Fixed vs. Surprise Lines vs. Thanas Frequency of checkpoints

15 Overall Results: 20% Accidents Deaths Night accidents Night deaths 10% 0% -10% -20% -30% -40% -50% -60% During Program 60 Days after

16 Accident Results Overall Results Fixed vs. Surprise Surprise maybe better than fixed sample too small to be sure. Significant effects on deaths during program and accidents after program. Big (>20%) estimated effects of surprise checkpoints on nighttime accidents and deaths. Lines vs. Thanas Frequency of checkpoints

17 Fixed vs. Surprise 20% Accidents Deaths Night accidents Night deaths 10% 0% -10% -20% -30% -40% -50% -60% Fixed locations Fixed, 60 days after Surprise locations Surprise, 60 days after

18 Accident Results Overall Results Fixed vs. Surprise Lines vs. Thanas Thanas consistently have higher estimated effects, but not significant. Frequency of checkpoints

19 Accident Results Overall Results Fixed vs. Surprise Lines vs. Thanas Frequency of checkpoints Effectiveness clearly highest at 3 checkpoints/week

20 For which vehicle types is enforcement most effective? 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Percentage of Stopped Drivers Found Drunk By Type of Vehicle and Treatment Motorcycles Cars Trucks Control Fixed Surprise

21 Results Checkpoint Implementation: Dedicated Lines Teams vs. Thana Staff

22 Lines vs. Thana Comparison: Checkpoint Attendance 100% 80% 60% 40% 20% 0% Checkpoints Completed On-time for Checkpoint Stayed at Checkpoint until 10pm Lines Thanas

23 Lines vs. Thana Comparison: Vehicle Checking 30% Percentage of Passing Vehicles Stopped by Police 25% 20% 15% 10% 5% 0% Lines Thanas

24 Lines vs. Thana Comparison: Catching Drunks 3.5 Drunk Drivers Caught Per Checkpoint Lines Thanas

25 Program Implementation: District-wise Comparison Checkpoints Attended Lines Thanas Ajmer 86.8% 65.8% Alwar 70.7% 11.4% Banswada 53.3% 42.9% Bharatpur* 37.0% 10.7% Bhilwara 96.6% 40.2% Bikaner 80.0% 80.0% Bundi 80.0% 21.3% Jaipur Rural 98.2% 89.9% Jodhpur City 61.9% 48.2% Sikar 76.6% 70.0% Udaipur 81.1% 73.0% Passing Vehicles Stopped Lines Thanas 27.8% 17.3% 15.7% 4.9% 30.1% 24.7% 13.8% 7.2% 23.0% 23.2% 14.0% 8.4% 19.7% 10.7% 38.8% 28.6% 10.9% 2.2% 34.7% 13.8% 16.9% 15.1% Drunk Drivers Per Checkpoint Lines Thanas *Affected by law and order situation

26 Teams Performance Over Time

27 Teams Performance Over Time

28 Lines vs. Thanas Lines consistently outperform thanas but This performance does not translate into significantly greater reductions in accidents and deaths. Not clear why this is the case. Further analysis may yield more insights.

29 Results Public Response to Enforcement

30 Do all drivers learn to avoid checkpoints? We compare the number of vehicles on the road: On a night when police are performing a checkpoint On a night with no checkpoint at the exact same spot Results: 7% fewer vehicle pass by during the checkpoint. Drivers learn to avoid checkpoints No significant difference between surprise vs. fixed on passing vehicles. Weak evidence that fixed checkpoints have increasingly fewer drivers pass over time.

31 Do drunk drivers learn to avoid checkpoints? It depends on the type of roadblock: Surprise roadblocks: No effect. Fixed roadblocks: Number of drunk drivers caught decreases by 3.4% with each previous roadblock. Effect not due to police burnout. Police lines teams visited some thanas once, some twice, some three times per week. We compare thanas that have had the same number of check points, done by teams with different experience. Results: experience gained from each additional checkpoint increases number of drunks caught by lines teams by 4%.

32 Results Court Data

33 Do drunk drivers go to court? We estimate the number of drunk drivers caught during the crackdown: (# drunks observed per checkpoint) X (# of checkpoints) = 3144 drunks compared with # drunks reported at courts = 2851 drunks Lines teams perform much better: Avg. drunk drivers sent to court per thana (total) Lines Thanas

34 What happens when drunken drivers go to court? 93% of drunken drivers pay some fine in court. None jailed. Average fine is rupees Huge variation in fines: 20 Fine Amount 15 Percent Fine Amount rs/-

35 What determines fines? Very weak link between severity of drunkeness and amount of fine. Slight positive relationship for BAC below 50 mg/100ml. No correlation for higher alcohol levels. Truck drivers pay more. Rs. 350 more than motorcyclists, Rs. 200 more than cars. Different districts charge very different amounts. For the average drunken motorcyclist: Highest: Jaipur Rural, Rs. 1608; Alwar, Rs Lowest: Udaipur, Rs. 302; Bikaner, Rs. 380.

36 Conclusions Surprise checkpoints more effective than fixed Drunks learn about fixed checkpoints and these become ineffective over time. Dedicated teams more effective than thana staff Combined effect of more focused team, GPS monitoring Caveats: No clear effect on accidents, deaths Difference between dedicated teams and thanas decreases with time 3 checkpoints/week most effective, and substantial postprogram effects Suggests that crackdown model may be an efficient way to allocate police forces.

37 Thank You