Assessing Connected Vehicle's Response to Green Light Optimal Speed Advisory From Field Operational Test and Scaling Up
What are the main factors related to road or service configuration influencing the response behaviour of connected vehicles? How does it evolve with respect to the Market Penetration Rate (MPR) of connected vehicles? Here are some questions raised by this paper with a focus made on Green Light Optim...
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Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2023-06, Vol.24 (6), p.6725-6736 |
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description | What are the main factors related to road or service configuration influencing the response behaviour of connected vehicles? How does it evolve with respect to the Market Penetration Rate (MPR) of connected vehicles? Here are some questions raised by this paper with a focus made on Green Light Optimal Speed Advisory (GLOSA) strategy. Such a system, based on V2I communication, aims at providing speed advice/recommendations when approaching an intersection to adjust speed and enhance fuel consumption. The message is displayed on the Human Machine Interface (HMI) of the connected vehicles and a response is expected from the driver. This paper derives its interest in the response behaviour of the driver to HMI. It develops a two-stage methodology based on (i) Field Operational Test to collect realistic inputs (e.g., response rate, delay, deceleration profile, etc.) and (ii) a simulated environment used for extending the findings to non-observed cases (e.g. higher MPR). Besides, the methodology that is well-fitted for generic evaluation and comparison of pilots sites' conclusions, one further contribution lies in the process to select the explaining factors. Factors are targeted among features of (i) the road configuration (e.g. number of lanes), (ii) the service configuration (e.g. activation distance), or (iii) the individual route choice and traffic conditions. Among others, it is highlighted that the activation distance plays a significant role in the response behaviour and, depending on the cycle duration, a short activation distance might be completely inefficient, while a true environmental impact requires high MPR. |
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How does it evolve with respect to the Market Penetration Rate (MPR) of connected vehicles? Here are some questions raised by this paper with a focus made on Green Light Optimal Speed Advisory (GLOSA) strategy. Such a system, based on V2I communication, aims at providing speed advice/recommendations when approaching an intersection to adjust speed and enhance fuel consumption. The message is displayed on the Human Machine Interface (HMI) of the connected vehicles and a response is expected from the driver. This paper derives its interest in the response behaviour of the driver to HMI. It develops a two-stage methodology based on (i) Field Operational Test to collect realistic inputs (e.g., response rate, delay, deceleration profile, etc.) and (ii) a simulated environment used for extending the findings to non-observed cases (e.g. higher MPR). Besides, the methodology that is well-fitted for generic evaluation and comparison of pilots sites' conclusions, one further contribution lies in the process to select the explaining factors. Factors are targeted among features of (i) the road configuration (e.g. number of lanes), (ii) the service configuration (e.g. activation distance), or (iii) the individual route choice and traffic conditions. Among others, it is highlighted that the activation distance plays a significant role in the response behaviour and, depending on the cycle duration, a short activation distance might be completely inefficient, while a true environmental impact requires high MPR.</description><identifier>ISSN: 1524-9050</identifier><identifier>EISSN: 1558-0016</identifier><identifier>DOI: 10.1109/TITS.2022.3187532</identifier><identifier>CODEN: ITISFG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Applications ; Communications systems ; Computer Science ; Configurations ; connected vehicle ; Connected vehicles ; Deceleration ; Driving conditions ; Energy consumption ; Environmental impact ; field operational test ; Global Positioning System ; GLOSA/eco-driving ; Green products ; Humanities and Social Sciences ; Man-machine interfaces ; Methods and statistics ; microscopic simulation ; Modeling and Simulation ; regression ; response behaviour ; Road design ; Roads ; Servers ; Statistics ; Traffic ; Urban areas ; Vehicles</subject><ispartof>IEEE transactions on intelligent transportation systems, 2023-06, Vol.24 (6), p.6725-6736</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c327t-f79e879b2f7e02afcee9dab63c24ea84add3a1eee3729d7e9b2894b6160557b73</citedby><cites>FETCH-LOGICAL-c327t-f79e879b2f7e02afcee9dab63c24ea84add3a1eee3729d7e9b2894b6160557b73</cites><orcidid>0000-0002-5826-897X ; 0000-0003-4508-0182 ; 0000-0002-6838-5360 ; 0000-0002-6873-695X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9829229$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,776,780,792,881,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9829229$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://hal.science/hal-03774018$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Bhattacharyya, Kinjal</creatorcontrib><creatorcontrib>Laharotte, Pierre-Antoine</creatorcontrib><creatorcontrib>Burianne, Arthur</creatorcontrib><creatorcontrib>Faouzi, Nour-Eddin El</creatorcontrib><title>Assessing Connected Vehicle's Response to Green Light Optimal Speed Advisory From Field Operational Test and Scaling Up</title><title>IEEE transactions on intelligent transportation systems</title><addtitle>TITS</addtitle><description>What are the main factors related to road or service configuration influencing the response behaviour of connected vehicles? How does it evolve with respect to the Market Penetration Rate (MPR) of connected vehicles? Here are some questions raised by this paper with a focus made on Green Light Optimal Speed Advisory (GLOSA) strategy. Such a system, based on V2I communication, aims at providing speed advice/recommendations when approaching an intersection to adjust speed and enhance fuel consumption. The message is displayed on the Human Machine Interface (HMI) of the connected vehicles and a response is expected from the driver. This paper derives its interest in the response behaviour of the driver to HMI. It develops a two-stage methodology based on (i) Field Operational Test to collect realistic inputs (e.g., response rate, delay, deceleration profile, etc.) and (ii) a simulated environment used for extending the findings to non-observed cases (e.g. higher MPR). Besides, the methodology that is well-fitted for generic evaluation and comparison of pilots sites' conclusions, one further contribution lies in the process to select the explaining factors. Factors are targeted among features of (i) the road configuration (e.g. number of lanes), (ii) the service configuration (e.g. activation distance), or (iii) the individual route choice and traffic conditions. 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Besides, the methodology that is well-fitted for generic evaluation and comparison of pilots sites' conclusions, one further contribution lies in the process to select the explaining factors. Factors are targeted among features of (i) the road configuration (e.g. number of lanes), (ii) the service configuration (e.g. activation distance), or (iii) the individual route choice and traffic conditions. 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subjects | Applications Communications systems Computer Science Configurations connected vehicle Connected vehicles Deceleration Driving conditions Energy consumption Environmental impact field operational test Global Positioning System GLOSA/eco-driving Green products Humanities and Social Sciences Man-machine interfaces Methods and statistics microscopic simulation Modeling and Simulation regression response behaviour Road design Roads Servers Statistics Traffic Urban areas Vehicles |
title | Assessing Connected Vehicle's Response to Green Light Optimal Speed Advisory From Field Operational Test and Scaling Up |
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