Vision Zero: NYC Traffic Collision Prevention Plan

Posted on Nov 3, 2019
The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Coordinating the movement of its 8.5 million residents and the millions of commuters and visitors is an immense task for New York City. Vision Zero is a program started in 2014 with the aim to reduce the number of fatalities and injuries of pedestrians and cyclists down to zero within ten years. Along with better enforcement of existing laws and the introduction of new legislation, the program devoted a great deal of effort and resources to better environment design, as well as community engagement and education.


One of the more noticeable features of NYC Vision Zero is the 80 miles of bike lanes that snake the city. A large portion of the bike lanes in the borough of Manhattan is a “protected” lane separated from moving cars by a physical barrier - often a row of parked cars and sometimes a concrete median. The result is an undeniable decrease in the number of accidents resulting in cyclist injury and fatality.


In the outer boroughs, the bike lanes are much more sparse. The majority of the bike lanes are not at all separated from automobiles and share an already cramped space. These shared bike lanes are essentially car lanes with reminders to the drivers that they will encounter cyclists on the road. Much like a deer crossing sign, these warnings don't give credence to the cyclists' share of the road. In the outer boroughs, there isn’t a clear trend that the cyclist involved accidents are decreasing.


As of end of September 2019, the borough of Brooklyn had 11 cyclist deaths, nearly twice that of any previous year on record and 11 times the number of cyclist fatalities in Manhattan. 


The top causes of all traffic accidents, whether or not people outside the vehicles are involved, are some variety of driver error. The category of “driver inattention” has consistently been the leading cause with no signs of slowing down. 

Manhattan 2014

Manhattan and Number of Accidents

Although Manhattan had reduced the number of accidents in 2018 to nearly half of those in 2014, the number of accidents caused by driver inattention increased by close to 20%.

Manhattan 2018

Another feature dedicated to the safety of pedestrians is the added medians in the roads. These “enhanced” crossings offer a safe refuge for those that don't make it all the way across and ensure that pedestrians don’t have to traverse as far of a distance when crossing the road. We can see the effects of these enhanced crossings near the Williamsbridge Oval by comparing the injuries and fatalities in 2014 and in 2018.

Williamsbridge Oval, Bronx 2014

The area is also a part of Neighborhood Slow Zones. These neighborhoods have speed limits reduced to 20 mph from the citywide limit of 25. It's clear that the combination of these feature resulted in fewer accidents in this neighborhood compared to the past.

Williamsbridge Oval, Bronx 2018

Areas where there had been historically high number of the elderly involved in accidents have been designated Safe Streets for Seniors. In these neighborhoods the crossing signal had been extended to allow those that walk more slowly to cross successfully.

Central Park West 2014
Central Park West 2018

These features are among dozens of environmental changes that vision zero had introduced to the city. You can use the shiny app to explore their impact on pedestrian and cyclist safety.

About Author

Paul Lee

Inquisitive data scientist with proven problem solving skills and strong coding abilities. Great communicator with 10+ years in a heralded career in education.
View all posts by Paul Lee >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI