Scipediacontent: Scipediacontent moved page Draft Content 238093204 to Kemp et al 2019a

2021-02-01T22:22:33Z

Scipediacontent moved page Draft Content 238093204 to Kemp et al 2019a

Scipediacontent: Created page with " == Abstract == Traffic jam is considered as a difficult problem to deal with in many cities around the world due to the continuously increasing number of vehicles compared t..."

2021-02-01T22:22:29Z

Created page with " == Abstract == Traffic jam is considered as a difficult problem to deal with in many cities around the world due to the continuously increasing number of vehicles compared t..."

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== Abstract ==

Traffic jam is considered as a difficult problem to deal with in many cities around the world due to the continuously increasing number of vehicles compared to the available infrastructure. Traffic congestion significantly influences drivers travel journey, fuel consumption and air pollution. However, the most important factor has affected the delay of emergency vehicles, such as ambulances and police cars, leading to increased road deaths and significant financial losses. To reduce this problem, we propose an advanced traffic control allows rapid emergency services response in smart cities. This can be achieved through a traffic management system capable of implementing path planning in road network monitoring and driving the emergency vehicle in the best possible way to reach the hazard zone. The performance of the proposed algorithm is compared with two other algorithms over Birmingham city centre test scenarios. Simulation results show that the proposed approach improves traffic efficiency of emergency vehicles by an overall average of 21.78%, 29.32%, 32.79% and 46.77% in terms of travel time, fuel consumption, CO 2 emission and average speed, respectively.

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1109/sam.2018.8448582 http://dx.doi.org/10.1109/sam.2018.8448582]

* [http://eprints.whiterose.ac.uk/142178/1/Coalition%20Game%20for%20Emergency%20Vehicles%20Re-routing%20in%20Smart%20Cities.pdf http://eprints.whiterose.ac.uk/142178/1/Coalition%20Game%20for%20Emergency%20Vehicles%20Re-routing%20in%20Smart%20Cities.pdf]

* [http://xplorestaging.ieee.org/ielx7/8424836/8448390/08448582.pdf?arnumber=8448582 http://xplorestaging.ieee.org/ielx7/8424836/8448390/08448582.pdf?arnumber=8448582],
: [http://dx.doi.org/10.1109/sam.2018.8448582 http://dx.doi.org/10.1109/sam.2018.8448582]

* [https://ieeexplore.ieee.org/document/8448582 https://ieeexplore.ieee.org/document/8448582],
: [http://eprints.whiterose.ac.uk/136775 http://eprints.whiterose.ac.uk/136775],
: [https://dblp.uni-trier.de/db/conf/ieeesam/sam2018.html#AmerAKMM18 https://dblp.uni-trier.de/db/conf/ieeesam/sam2018.html#AmerAKMM18],
: [https://sigport.org/documents/coalition-game-emergency-vehicles-re-routing-smart-cities https://sigport.org/documents/coalition-game-emergency-vehicles-re-routing-smart-cities],
: [https://academic.microsoft.com/#/detail/2883579231 https://academic.microsoft.com/#/detail/2883579231]

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Kemp et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 238093204 to Kemp et al 2019a

Scipediacontent: Created page with " == Abstract == Traffic jam is considered as a difficult problem to deal with in many cities around the world due to the continuously increasing number of vehicles compared t..."