For 2018 Google Girl Hackathon IV in Shanghai
It's forked from Prudence's github. She was our team leader. In this competition, I was mainly in charge of back-end code for data preprocessing, visualization and prediction using Python
[Start Playing Here]https://prudenceyyx.github.io/Old-Driver/index.html
- Content-security using HTTPS
- Reduce loading time by making logo icon small
- Use deck.gl visualization instead of Google Map integration, consequently move to Mapbox Integration
- Unify UI and transform to responsive web design by adopting Bulma CSS framework
- Add game instruction
What is a typical day like for a taxi driver in New York City? Try our data-driven simulation game built within 48 hours in Google Girl Hackathon. In this game, you, playing a role of driver, need to choose proper places to await passengers by clicking on the map. On the map provides data visualization of the pick-up demands proximity, showing as the opacity of red dots.
Your goal is to earn as much as possible within the 8-hour work time. Be careful about your choices and be efficient.
morning: (Road direction appears after you click the button and choose a place)
noon:
afternoon:
night:
Given a dataset of the taxi tranffic in the New York City in 2016, it comes naturally to us, and also to other teams, to optimize and make prediciton on the data from the perspective of taxi passengers. However, could the same dataset in turn benefit taxi drivers? Drivers nowadays couldn't but rely heavily on the advice from ridesharing apps, whose companies have recently shrunk the drivers' agency to pick orders. Experienced drivers may have their own preference between fast ride or long-distance ride, downtown or suburb, and morning time or late night, which is probably hardly taken into consideration of the algorithm of ridesharing apps. To meet drivers' need, we intent to offer quantified support for drivers, and for users to experience a driver's trade-off decision making every day.
Jin, Yuhang
Huang, Xiao(YeahHuang)
Wu, Yuanyuan
Yao, Yuxia (Prudence)
Zhang, Peiying
Best Innovation Award
People's Choice Award(1/8)