TY - GEN
T1 - SMARTBIKE
T2 - 2nd IEEE International Smart Cities Conference, ISC2 2016
AU - Ram, Sudha
AU - Dong, Fan
AU - Currim, Faize
AU - Wang, Yun
AU - Dantas, Ezequiel
AU - Sabóia, Luiz Alberto
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/30
Y1 - 2016/9/30
N2 - Bike share systems have been implemented in many cities to provide an alternative low-cost environmentally friendly and healthy public transportation. Citizens can pick up and drop off bikes among stations around the city. The system may be used for both work-related and leisure purposes including supporting last-mile transportation and tourism. In order to sustain and attract more users into the bike system, understanding demand and trip patterns is a key objective. Further, due to the asymmetric and dynamic nature of user demands, some stations tend to run out of bikes whereas other stations tend to be full (impeding returns). Rebalancing stations to provide high quality services to fit pick up and drop off demand is a major challenge in bike share systems. In this paper, we present a three-layer SMARTBIKE system to assist city administrators in Fortaleza, Brazil with bike share system decision making. This is an international cooperative effort between academia and government to aid in building a Smart City. The first layer of the proposed tool includes ¿-means clustering technology to understand the true demand of the city bike share system. We designed a novel station network analysis in the second layer to provide insights on system usage patterns and to help with the rebalancing strategy. The third layer provides rebalancing support at the facility and operation level. Finally, we discuss a dynamic visualization tool to support decision making.
AB - Bike share systems have been implemented in many cities to provide an alternative low-cost environmentally friendly and healthy public transportation. Citizens can pick up and drop off bikes among stations around the city. The system may be used for both work-related and leisure purposes including supporting last-mile transportation and tourism. In order to sustain and attract more users into the bike system, understanding demand and trip patterns is a key objective. Further, due to the asymmetric and dynamic nature of user demands, some stations tend to run out of bikes whereas other stations tend to be full (impeding returns). Rebalancing stations to provide high quality services to fit pick up and drop off demand is a major challenge in bike share systems. In this paper, we present a three-layer SMARTBIKE system to assist city administrators in Fortaleza, Brazil with bike share system decision making. This is an international cooperative effort between academia and government to aid in building a Smart City. The first layer of the proposed tool includes ¿-means clustering technology to understand the true demand of the city bike share system. We designed a novel station network analysis in the second layer to provide insights on system usage patterns and to help with the rebalancing strategy. The third layer provides rebalancing support at the facility and operation level. Finally, we discuss a dynamic visualization tool to support decision making.
KW - Bike share system
KW - Network analysis
KW - Urban public transportation
UR - http://www.scopus.com/inward/record.url?scp=84994175591&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994175591&partnerID=8YFLogxK
U2 - 10.1109/ISC2.2016.7580838
DO - 10.1109/ISC2.2016.7580838
M3 - Conference contribution
AN - SCOPUS:84994175591
T3 - IEEE 2nd International Smart Cities Conference: Improving the Citizens Quality of Life, ISC2 2016 - Proceedings
BT - IEEE 2nd International Smart Cities Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 September 2016 through 15 September 2016
ER -