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A Scoring Method for Driving Safety Credit Using Trajectory Data

arXiv.org Machine Learning

ZhijiePan College of Computer Science and Technology Zhejiang University Hangzhou, China zhijie_pan@zju.edu.cn Abstract--Urban traffic systems worldwide are suffering from severe traffic safety problems. Traffic safety is affected by many complex factors, and heavily related to all drivers' behaviors involved in traffic system. Drivers with aggressive driving behaviors increase the risk of traffic accidents. In order to manage the safety level of traffic system, we propose Driving Safety Credit inspired by credit score in financial security field, and design a scoring method using driver's trajectory data and violation records. First, we extract driving habits, aggressive driving behaviors and traffic violation behaviors from driver's trajectories and traffic violation records. Next, we train a classification modelto filtered out irrelevant features. And at last, we score each driver with selected features. We verify our proposed scoring method using 40 days of traffic simulation, and proves the effectiveness of our scoring method. I. INTRODUCTION Urban traffic worldwide is facing severe traffic safety problems.


Machine Learning Will Save India's Cows from Bad Drivers

#artificialintelligence

In certain parts of the world, cow collisions are the stuff of legend. A car traveling at any significant speed up against a full-grown cow travelling at no speed is most often the end of the car, the cow, and maybe the human(s) inside of the car. That's up to 1,800 pounds of beef standing there with a center of gravity well-optimized to ensure that those pounds wind up where they can be most dangerous. Cows on roads are a big problem in India, where rapid urbanization and industrialization has meant that new roads are increasingly being laid through rangeland. A 2015 study found that some 6 percent of accidents in India can be attributed to animals on the road.


This app wants to spy on bad drivers, but it's really all of us, too

Washington Post - Technology News

The idea behind app Nexar is ambitious: create a type of air-traffic control system for the road. Catalogue the cars in a given location, track dicey behavior and help drivers avoid dangerous intersections and even bad drivers. Nexar is a free dashcam app that, using artificial intelligence, creates a database of an area's roads and drivers. If car stops short in front of you, even a few cars in front of you, Nexar's database can send you a notification so you'll have more time to brake. If an accident happens around the corner and cars are getting detoured onto your route, the app will tell you.


Why Google's Driverless Cars Should Go to Honolulu Next

The Atlantic - Technology

People have a tendency to talk about their city's terrible drivers with a weird sense of pride. In Boston, they're called Massholes. In Philly, being aggressive and rude behind the wheel is just a given. Wherever you go, it seems, traffic is terrible. The automobile, the sociologist Henri Lefebvre once said, was "the last refuge of chance and risk in an increasingly controlled and managed society."