TRADER: Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities

Cullen Rhodes; Soufiene Djahel

doi:10.1109/ISC2.2017.8090783

TRADER: Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities

Cullen Rhodes, Soufiene Djahel

Manchester Metropolitan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

Despite the significant research efforts and resources spent to alleviate the impact of road traffic congestion on economy, environment and road safety, it is still one of the major unsolved problems of the 21st century. The emergence of smart self-driving vehicles promises a dramatic change in the way road traffic congestion is controlled and mitigated. This can be achieved by enabling efficient communication between these vehicles and modern road infrastructure such as smart traffic lights controllers. This paper, therefore, proposes a simple yet efficient mechanism named (TRADER: TRaffic Light Phases Aware Driving for REduced tRaffic Congestion) in order to reduce the overall vehicles' travel time in smart cities. TRADER has been implemented and extensively evaluated under several scenarios using SUMO and TraCI. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of TRADER in terms of the significant reduction of travel time, up to 31.44% in a random road network topology.

Original language	English
Title of host publication	2017 International Smart Cities Conference, ISC2 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	8
ISBN (Electronic)	9781538625231, 9781538625248
ISBN (Print)	9781538625255
DOIs	https://doi.org/10.1109/ISC2.2017.8090783
Publication status	Published - 2 Nov 2017
Externally published	Yes
Event	2017 International Smart Cities Conference - Wuxi, China Duration: 14 Sept 2017 → 17 Sept 2017

Conference

Conference	2017 International Smart Cities Conference
Abbreviated title	ISC2 2017
Country/Territory	China
City	Wuxi
Period	14/09/17 → 17/09/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

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10.1109/ISC2.2017.8090783Licence: Unspecified

Cite this

@inproceedings{593acf7bd0c54d288db86f4808ea9b19,

title = "TRADER: Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities",

abstract = "Despite the significant research efforts and resources spent to alleviate the impact of road traffic congestion on economy, environment and road safety, it is still one of the major unsolved problems of the 21st century. The emergence of smart self-driving vehicles promises a dramatic change in the way road traffic congestion is controlled and mitigated. This can be achieved by enabling efficient communication between these vehicles and modern road infrastructure such as smart traffic lights controllers. This paper, therefore, proposes a simple yet efficient mechanism named (TRADER: TRaffic Light Phases Aware Driving for REduced tRaffic Congestion) in order to reduce the overall vehicles' travel time in smart cities. TRADER has been implemented and extensively evaluated under several scenarios using SUMO and TraCI. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of TRADER in terms of the significant reduction of travel time, up to 31.44\% in a random road network topology.",

keywords = "Road Traffic Congestion, Smart Cities, Smart Transportation, SUMO, TraCI",

author = "Cullen Rhodes and Soufiene Djahel",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Smart Cities Conference, ISC2 2017 ; Conference date: 14-09-2017 Through 17-09-2017",

year = "2017",

month = nov,

day = "2",

doi = "10.1109/ISC2.2017.8090783",

language = "English",

isbn = "9781538625255",

booktitle = "2017 International Smart Cities Conference, ISC2 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

TY - GEN

T1 - TRADER

T2 - 2017 International Smart Cities Conference

AU - Rhodes, Cullen

AU - Djahel, Soufiene

PY - 2017/11/2

Y1 - 2017/11/2

N2 - Despite the significant research efforts and resources spent to alleviate the impact of road traffic congestion on economy, environment and road safety, it is still one of the major unsolved problems of the 21st century. The emergence of smart self-driving vehicles promises a dramatic change in the way road traffic congestion is controlled and mitigated. This can be achieved by enabling efficient communication between these vehicles and modern road infrastructure such as smart traffic lights controllers. This paper, therefore, proposes a simple yet efficient mechanism named (TRADER: TRaffic Light Phases Aware Driving for REduced tRaffic Congestion) in order to reduce the overall vehicles' travel time in smart cities. TRADER has been implemented and extensively evaluated under several scenarios using SUMO and TraCI. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of TRADER in terms of the significant reduction of travel time, up to 31.44% in a random road network topology.

AB - Despite the significant research efforts and resources spent to alleviate the impact of road traffic congestion on economy, environment and road safety, it is still one of the major unsolved problems of the 21st century. The emergence of smart self-driving vehicles promises a dramatic change in the way road traffic congestion is controlled and mitigated. This can be achieved by enabling efficient communication between these vehicles and modern road infrastructure such as smart traffic lights controllers. This paper, therefore, proposes a simple yet efficient mechanism named (TRADER: TRaffic Light Phases Aware Driving for REduced tRaffic Congestion) in order to reduce the overall vehicles' travel time in smart cities. TRADER has been implemented and extensively evaluated under several scenarios using SUMO and TraCI. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of TRADER in terms of the significant reduction of travel time, up to 31.44% in a random road network topology.

KW - Road Traffic Congestion

KW - Smart Cities

KW - Smart Transportation

KW - SUMO

KW - TraCI

UR - https://www.scopus.com/pages/publications/85039933951

U2 - 10.1109/ISC2.2017.8090783

DO - 10.1109/ISC2.2017.8090783

M3 - Conference contribution

AN - SCOPUS:85039933951

SN - 9781538625255

BT - 2017 International Smart Cities Conference, ISC2 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 14 September 2017 through 17 September 2017

ER -

TRADER: Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities

Abstract

Conference

UN SDGs

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