Improving Toronto Road Safety - Web App & Dashboard

Can GIS Analysis Make Toronto Roads Safer?

Introduction

However, the death toll continues to mount despite well-intentioned measures to make pedestrian crossings safer. Advocates, city councils, politicians and members of the public are demanding Toronto make its streets safer for cyclists and pedestrians after the recent increasing trend of deaths in the last 5 years. Based on the 2016 Ontario road safety annual report, 44.8% of pedestrian fatalities occurred in Toronto. Members of the communities question the efficiency of the Vision Zero Road Safety Plan.

In this study, 11 years of traffic collisions data (KSI: Killed and Seriously Injured) from the Toronto Police Service was analyzed with a view to identify and quantify various factors in space and time on a road network and help location-based decision making to improve Toronto road safety.

Can GIS Analysis Make Toronto Roads Safer?

Model

* Which intersections and roadways in Toronto have the highest crash rates?

* When and where do most crashes occur?

* How does the spatial pattern of fatalities differ from the spatial pattern of traffic accidents overall?

* How does the spatial pattern of crash rates occurring during the workweek afternoon commute differ from the overall pattern of crash rates?

* Overtime, which intersections or roadways are persistent problem areas for traffic accidents?

* Where are the hot spot areas for crashes involving elderly drivers, teenage drivers, or alcohol-related accidents?

* When and where do accidents involving elderly drivers, teenage drivers, or alcohol cluster spatially?

The red street segments on the map (please check the web app) show higher traffic accident rates on Toronto streets.

Predicting Street Safety by using Convolutional Neural Networks

Road Safety

When are the most dangerous times to be driving?

Dangerous Times of Driving
Collisions by Hour

The graph shows that the number of crashes higher between 1 pm to 7 pm. It reaches the highest peak at 6 pm.

Fatal Collisions by Hour

Where do 3:00 to 6:00 PM crashes occur in Toronto?

Our 24 hours data analysis over the last 11 years on the left side map shows that several peaks emerge, but the strongest is associated with the time period between 3:00 pm and 6:00 pm (between hours 15 and 18). The red dots on the map show the locations with statistically significant clustering of high rates of collisions during peak hours (please check the web app).

Traffic Collision Fatalities in Toronto 2008–2018

Accident Trend

Road accidents are typically analyzed to address the influences of humans, vehicles, and infrastructure. Many factors contribute to road safety — including roadway design, speeds, human behaviours, technology, and policies. This increasing trend of fatalities over the last decade has emphasized the need for a comprehensive and coordinated road safety strategy that will further protect vulnerable road users and reduce the number of collisions resulting in death and serious injury. The map on the left side shows traffic accident density distribution on Toronto streets. The dark colour indicates higher RTC rates (please check the web app).

Space-time Patterns of Collisions

Emerging HotSpot Analysis

KSI Data Analysis

KSI Dashboard

Traffic Signal Vehicles and Pedestrian Volumes

The Busiest Intersections in Toronto

At some busy spots such as at the intersections of Yonge St with Gerrard St W, Dundas St W, Queen St W, Richmond St W, Adelaida St W, King St W, Wellington St W and Front St W, pedestrian traffic volumes higher than vehicle traffic signal volume based on the 8hr traffic signal vehicle and pedestrian volumes data.

Traffic Signal Vehicles and Pedestrian Volumes

Pedestrians: Major Victims of Fatal Traffic Collisions

Pedestrian Fatal Collisions

In terms of pedestrian action data analysis, there were total 1568 KSI crashes related to crossings. Among them, 271 is fatal and accounts for 45.69% of total fatalities. Improper pedestrian behaviours (55%) also play a major role in causing traffic accidents. For example, There were 117 fatal cases (35%) of crossing with no traffic control, 39 fatal cases (11.78%) of crossing without right of way and 14 fatal cases (4.2%) of running onto roadway.

Pedestrian Action

Pedestrian Fatal Collisions

Pedestrian Dashboard

117 pedestrian fatal crashes happened when there was no traffic control, 81 fatal crashes occurred when pedestrians crossed with right of way and 39 fatal crashes happened when pedestrians crossed roads without right of the way.

Aggressive and Distractive Driving

Driver Behavioral Analysis

Understanding the spatial and temporal patterns of traffic accidents will help to recommend very specific remediation strategies to help prevent future crashes. Knowing which roadways and intersections are associated with persistently high rates of crashes involving alcohol, for example, may direct the locations of DUI checkpoints. For example, there was a total of 488 alcohol-related collisions including 31 fatal crashes and 169 major injuries related between 2008 and 2018. Those accidents mostly happened on weekends between 8 pm and 3 am. In terms of alcohol-related driver behaviours, it includes 375 aggressive driving, 290 speedings, 66 redlight running crashes for the same period. It can be seen from our data analysis that the number of alcohol-related KSI is higher on weekends between 10 pm and 3 am.

Six traffic violations it identified as being the most likely to kill or injure, including:

  • Speeding.
  • Failing to yield to a pedestrian.
  • Failing to stop on a signal.
  • Improper turns.
  • Cellphone use.
  • Disobeying signs.
Pedestrians: Major Victims of Fatal Traffic Collisions

Speeding and Red Light Running

The City of Toronto is planning to install automatic speed enforcement technology as part of a pair of new Vision Zero initiatives to reduce traffic-related fatalities. In an effort to improve pedestrian safety, the city is expanding the number of intersections where pedestrians will have a head start to cross the street. So far, the city has implemented the program at 12 intersections which gives pedestrians a five-second advanced green signal, including the intersection of Dundas Street West and Mabelle Avenue. The goal, Tory said, is to have the technology implemented at 80 intersections across Toronto by the end of the year. The new intersections were selected based on the number of previous collisions between pedestrians and turning vehicles.

Driver Behaviour Analysis

Improper Driver Action Statistics

Cyclist Involved Collisions

Existing Safety Measures

  1. Toronto Cyclists Handbook
  2. Helmet Safety Education Videos
  3. Space to Cycle Campaign
  4. “Stay Safe, Stay Back” Campaign

New/Enhanced Safety Measures

  • Cycle Tracks
  • Automated Cyclist Detection
  • Advance Green for Cyclists
  • Signalized Crossings for Cyclists
  • Enhanced Cycling Facilities

Fatal and Dangerous Intersections in Toronto

Collisions and Age Groups

Improving Road Safety with Crowd-Sourced Data

Waze Data: Traffic Jam

Waze data also includes a couple of attributes associated with the Waze Alert and Jam: a user rating and a report rating. Each of these attributes provides an indication of event validity. All of these tools, in conjunction with roadside Intelligent Transportation Systems, help indicate what is happening, where it is happening, and how traffic is being impacted. Either way, quicker awareness generates faster event response and reporting. Traffic control systems or police departments can begin implementing the appropriate response for traffic incident management and make it scalable based on Waze’s real-time reporting to prevent traffic accidents. Waze user reports may expose locations plagued with accidents but in lacking police coverage. This knowledge may help police departments to improve road safety by relocating the police units to these locations.

The data from Waze can provide real-time road situational awareness. It can be seen from the map on (please check the web app) the side that 2 weeks Waze data hot spots correspond with traffic crash hot spots.

Conclusion: How to Improve Road Safety?

1. Designing a safer street. In the USA, transport organizations started to adopt European-inspired designs (road diet) that change how drivers, cyclists, and pedestrians use the road in order to reduce speeding and encourage safety for everyone.

2. It is up to both behaviour and attitudes of drivers and pedestrians to keep everyone safe on Toronto roads. (improper behavioural Issues pedestrian 55%, drivers 25%, cyclists 56%)

3. Smart Signal Optimization at Intersection Crossing

real-time traffic data and adjusting the signals to accommodate that real-time data — whether it’s pedestrian volumes or vehicle volumes.

4. Red Light Speeding Camera (set up traffic cameras in school zones, traffic hot spots and high volume intersections ).

The City of Toronto is planning to install automatic speed enforcement technology as part of a pair of new Vision Zero initiatives to reduce traffic-related fatalities.

So, do red-light cameras reduce violations, and more importantly, crashes? The simple answer is yes. Red-light cameras can play a role in improving traffic safety for all road users and should be placed where they can benefit a community, like at intersections with high numbers of fatalities. When properly implemented, red-light cameras can help save lives and can serve to supplement law enforcement efforts, rather than generate revenue for governments.

5. Increase traffic control and fine for traffic rule violators

6.A range of measures including generous pedestrian crossing times, wider curbs, medians, dedicated bus lanes, a reduction of two vehicular lanes, bike lanes and more cross-walks. painted pavements

7. Some other methods of preventing road collisions

  • Vehicles and Vehicle Systems (Collision avoidance, Collision protection, Commercial vehicle safety, Off-road vehicle safety, Crash investigation and reconstruction)
  • Traffic Engineering/Road Design (Impact of road design, Traffic operations and traffic control devices, Intelligent transportation systems, Speed limit setting/monitoring)
  • Injury Prevention (Epidemiology of crashes/injuries, Occupant protection, Biomechanics of injury crashes, Automotive medicine)
  • Enforcement/Legal Issues (Enforcement strategies, Alcohol and drugs, Legal aspects of crashes)
  • Safety Initiatives (Safety promotion programs, Community and partnership engagement, Integrated road safety strategies)
  • Policy and Program Development (Societal costs of crashes, Application of policies and programs, Application of legislation/regulations)
  • Road Users/Behavioural Issues (Epidemiology of crashes or injuries, Specific road users approaches/research (e.g. pedestrian, cyclist, motorcyclist), Human factors and traffic psychology)

Note: WebApp and Dashboards can be accessed by clicking the following references [1,3 and 4]. Please don’t hesitate to write comments and questions.

References

  1. https://data.torontopolice.on.ca/pages/ksi
  2. Pedestrian Fatality Dashboard
  3. KSI Data Analysis Dashboard

Senior Geospatial Specialist in Toronto

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