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Michael Nieuwesteeg Causes of crashes affecting pedestrians.

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Presentation on theme: "Michael Nieuwesteeg Causes of crashes affecting pedestrians."— Presentation transcript:

1 Michael Nieuwesteeg Causes of crashes affecting pedestrians

2 Presentation outline 1.Background – pedestrian trauma 2.Interviewing injured pedestrians 3.What causes pedestrian crashes 4.Tackling pedestrian injuries 5.New TAC programs for pedestrian and cycling safety

3 Pedestrians # (%) Deaths per year48 (16%) Hospital >14 days claims180 (20%) Hospital claims530 (12%) TAC costs$65m (10%) Pedestrian trauma

4 Pedestrians comprise 11.3% of all serious casualties Pedestrians in 40, 50 and 60 speed zones make up 8.8% of all serious casualties 60 zones intersections are particularly problematic Almost even split between intersection and mid-block Pedestrian trauma


6 TAC commissioned exploratory survey research with its clients (persons compensated for road transport injury) who were injured as pedestrians in: 16-39 or 60+ age groups 40, 50 or 60km/h zones The research sought to identify: typical crash circumstances risk factors in pedestrian crashes issues that warrant further exploration TAC research with injured pedestrians

7 TAC research findings Crash types by age of injured pedestrian Crash type % of crashes Pedestrians aged 16-39Pedestrians aged 60+ Number of crashes (n) % of crashes Number of crashes (n) % of crashes Pedestrian crossing road75%7871%7179% Crossing intersection40%3835%4146% Crossing mid-block31%3734%2427% Crossing roundabout5%33%67% Pedestrian not crossing road26%3229%1921% Car off-road / out of control7%109%44% Standing/Walking on road4%76%11% Private/Friendly4%4 4 Car-park3%3 3 Driveway cross-over footpath3%3 22% Struck while boarding/alighting3%3 22% Fall while boarding/alighting2%11%22% Other1%1 1

8 TAC research findings Intersection crashes  58% involved vehicle turning right, usually exiting, ped usually on far side of road (completing crossing)  Driver usually at fault  In many of these crashes where the driver was at fault there were elements present that made visibility difficult (low light, dark clothing, rain)  Limited understanding of impact of traffic lights. Red-light running appears to be uncommon

9 TAC research findings Mid-block crashes  70% involved pedestrian being hit on near side  20% involved reversing vehicles  In 64% of cases an intersection was within 50 metres  In a third of cases the vehicle had just pulled out of a parking spot or turned into road  22% involved pedestrians who were crossing at a signalised pedestrian crossing or zebra crossing

10 TAC research findings Other factors  A quarter of younger group had consumed alcohol pre-crash  Pedestrians usually injured while on routine trips in familiar locations  Distraction, which was an issue for the younger group, often co-occurred with impairing factors and mid-block crashes  Difficult light or weather conditions seem to contribute more to the intersection than mid-block crashes, probably by adding another level of difficulty to an already complex driving task

11 TAC research findings Age differences  Younger group significantly more likely to be at fault, to have consumed alcohol, to be distracted, stressed, tired  Younger group more likely to be injured in poor light conditions  Older pedestrians less likely to cross mid-block

12 TAC research findings IssueYoungerOlderIntersectionMid-block Roundabout and other crashes Pedestrian at fault 34%12%16%43%18% Familiar with location 90%89%91%93%83% Heavy or congested traffic 23%10%11%19%26% Poor light conditions 46%26%43%22%44% Raining 8%11%14%8%5% Tired/fatigued 15%3%6%9%15% Stressed/anxious 14%2%9%10%7% Distracted 23%2%9%24%10% Impaired by alcohol 25%3%10%15%22% Impaired by drugs 0%NA0% Impaired mobility NA8%5%3%2%

13 A system view Limits of human performance - functionality - biomechanically in collisions Limits of vehicle performance - crash avoidance - crashworthiness Physical design of roads and roadsides Vital role of speed

14 Modified Behavioural Sequence Model Function/event sequence Search Detection Evaluation Decision Human action Vehicle/system action Response Predisposing factors Driver factors Ped/cyclist factors Vehicle factors Environment factors Post-crash factors Safe System

15 When the system fails…


17 Safe System travel speeds Smart roads (ped detection) Vehicle technology (ISA, AEB) Road design, e.g., low speed environment, raised crosswalks Responsible road use When the system works…

18 When the system works

19 TAC supporting safety infrastructure  LGA grants  $100m pedestrian and cycling safety fund

20 ˃Round 1 – August 2014 97 applications, 27 funded 14 Metro Melbourne 13 Regional Victoria (2 in large cities) 11 focus on pedestrians 10 focus on cyclists and pedestrians 6 focus on cyclists Many include speed reduction to 40 km/h ˃Round 2 closes mid August 2015 LGA grants

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