Loading…

An Agent-Based Fleet Management Model for First- and Last-Mile Services

With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to inv...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2022-12
Main Authors: Bhatnagar, Saumya, Rambha, Tarun, Ramadurai, Gitakrishnan
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Bhatnagar, Saumya
Rambha, Tarun
Ramadurai, Gitakrishnan
description With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit attractive, ridership in these systems has often failed to reach targeted levels. FLM service providers also experience lower demand and revenues in the wake of shifts to other means of transport. Effective FLM options are required to prevent this phenomenon and make public transport attractive for commuters. One possible solution is to forge partnerships between public transport and FLM providers that offer competitive joint mobility options. Such solutions require prudent allocation of supply and optimised strategies for FLM operations and ride-sharing. To this end, we build an agent- and event-based simulation model which captures interactions between passengers and FLM services using statecharts, vehicle routing models, and other trip matching rules. An optimisation model for allocating FLM vehicles at different transit stations is proposed to reduce unserved requests. Using real-world metro transit demand data from Bengaluru, India, the effectiveness of our approach in improving FLM connectivity and quantifying the benefits of sharing trips is demonstrated.
doi_str_mv 10.48550/arxiv.2208.04563
format article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2700435774</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2700435774</sourcerecordid><originalsourceid>FETCH-LOGICAL-a953-2997f7e490579b0cbaeae117b4aa2ada68e029df0be0624d0aef28edc50ffd013</originalsourceid><addsrcrecordid>eNotjcFKw0AURQdBsNR-gLsB16kvb2YymWUspgoJLuy-vGTelJSYaCYtfr4BXd3DWZwrxEMKW50bA080_XTXLSLkW9AmUzdihUqlSa4R78QmxjMAYGbRGLUS-2KQxYmHOXmmyF6WPfMsaxroxJ-LlvXouZdhnGTZTXFOJA1eVrRQ3fUsP3i6di3He3EbqI-8-d-1OJQvh91rUr3v33ZFlZAzKkHnbLCsHRjrGmgbYuI0tY0mQvKU5QzofICGIUPtgThgzr41EIKHVK3F41_2axq_Lxzn43m8TMPyeEQLoJWxVqtf2slMkg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2700435774</pqid></control><display><type>article</type><title>An Agent-Based Fleet Management Model for First- and Last-Mile Services</title><source>Publicly Available Content (ProQuest)</source><creator>Bhatnagar, Saumya ; Rambha, Tarun ; Ramadurai, Gitakrishnan</creator><creatorcontrib>Bhatnagar, Saumya ; Rambha, Tarun ; Ramadurai, Gitakrishnan</creatorcontrib><description>With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit attractive, ridership in these systems has often failed to reach targeted levels. FLM service providers also experience lower demand and revenues in the wake of shifts to other means of transport. Effective FLM options are required to prevent this phenomenon and make public transport attractive for commuters. One possible solution is to forge partnerships between public transport and FLM providers that offer competitive joint mobility options. Such solutions require prudent allocation of supply and optimised strategies for FLM operations and ride-sharing. To this end, we build an agent- and event-based simulation model which captures interactions between passengers and FLM services using statecharts, vehicle routing models, and other trip matching rules. An optimisation model for allocating FLM vehicles at different transit stations is proposed to reduce unserved requests. Using real-world metro transit demand data from Bengaluru, India, the effectiveness of our approach in improving FLM connectivity and quantifying the benefits of sharing trips is demonstrated.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2208.04563</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Automobiles ; Car sharing ; Developing countries ; Fleet management ; LDCs ; Optimization ; Public transportation ; Ridership ; Route planning ; Simulation models ; Subway stations ; Vehicle routing</subject><ispartof>arXiv.org, 2022-12</ispartof><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2700435774?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25752,27924,37011,44589</link.rule.ids></links><search><creatorcontrib>Bhatnagar, Saumya</creatorcontrib><creatorcontrib>Rambha, Tarun</creatorcontrib><creatorcontrib>Ramadurai, Gitakrishnan</creatorcontrib><title>An Agent-Based Fleet Management Model for First- and Last-Mile Services</title><title>arXiv.org</title><description>With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit attractive, ridership in these systems has often failed to reach targeted levels. FLM service providers also experience lower demand and revenues in the wake of shifts to other means of transport. Effective FLM options are required to prevent this phenomenon and make public transport attractive for commuters. One possible solution is to forge partnerships between public transport and FLM providers that offer competitive joint mobility options. Such solutions require prudent allocation of supply and optimised strategies for FLM operations and ride-sharing. To this end, we build an agent- and event-based simulation model which captures interactions between passengers and FLM services using statecharts, vehicle routing models, and other trip matching rules. An optimisation model for allocating FLM vehicles at different transit stations is proposed to reduce unserved requests. Using real-world metro transit demand data from Bengaluru, India, the effectiveness of our approach in improving FLM connectivity and quantifying the benefits of sharing trips is demonstrated.</description><subject>Automobiles</subject><subject>Car sharing</subject><subject>Developing countries</subject><subject>Fleet management</subject><subject>LDCs</subject><subject>Optimization</subject><subject>Public transportation</subject><subject>Ridership</subject><subject>Route planning</subject><subject>Simulation models</subject><subject>Subway stations</subject><subject>Vehicle routing</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNotjcFKw0AURQdBsNR-gLsB16kvb2YymWUspgoJLuy-vGTelJSYaCYtfr4BXd3DWZwrxEMKW50bA080_XTXLSLkW9AmUzdihUqlSa4R78QmxjMAYGbRGLUS-2KQxYmHOXmmyF6WPfMsaxroxJ-LlvXouZdhnGTZTXFOJA1eVrRQ3fUsP3i6di3He3EbqI-8-d-1OJQvh91rUr3v33ZFlZAzKkHnbLCsHRjrGmgbYuI0tY0mQvKU5QzofICGIUPtgThgzr41EIKHVK3F41_2axq_Lxzn43m8TMPyeEQLoJWxVqtf2slMkg</recordid><startdate>20221204</startdate><enddate>20221204</enddate><creator>Bhatnagar, Saumya</creator><creator>Rambha, Tarun</creator><creator>Ramadurai, Gitakrishnan</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20221204</creationdate><title>An Agent-Based Fleet Management Model for First- and Last-Mile Services</title><author>Bhatnagar, Saumya ; Rambha, Tarun ; Ramadurai, Gitakrishnan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a953-2997f7e490579b0cbaeae117b4aa2ada68e029df0be0624d0aef28edc50ffd013</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Automobiles</topic><topic>Car sharing</topic><topic>Developing countries</topic><topic>Fleet management</topic><topic>LDCs</topic><topic>Optimization</topic><topic>Public transportation</topic><topic>Ridership</topic><topic>Route planning</topic><topic>Simulation models</topic><topic>Subway stations</topic><topic>Vehicle routing</topic><toplevel>online_resources</toplevel><creatorcontrib>Bhatnagar, Saumya</creatorcontrib><creatorcontrib>Rambha, Tarun</creatorcontrib><creatorcontrib>Ramadurai, Gitakrishnan</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bhatnagar, Saumya</au><au>Rambha, Tarun</au><au>Ramadurai, Gitakrishnan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Agent-Based Fleet Management Model for First- and Last-Mile Services</atitle><jtitle>arXiv.org</jtitle><date>2022-12-04</date><risdate>2022</risdate><eissn>2331-8422</eissn><abstract>With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit attractive, ridership in these systems has often failed to reach targeted levels. FLM service providers also experience lower demand and revenues in the wake of shifts to other means of transport. Effective FLM options are required to prevent this phenomenon and make public transport attractive for commuters. One possible solution is to forge partnerships between public transport and FLM providers that offer competitive joint mobility options. Such solutions require prudent allocation of supply and optimised strategies for FLM operations and ride-sharing. To this end, we build an agent- and event-based simulation model which captures interactions between passengers and FLM services using statecharts, vehicle routing models, and other trip matching rules. An optimisation model for allocating FLM vehicles at different transit stations is proposed to reduce unserved requests. Using real-world metro transit demand data from Bengaluru, India, the effectiveness of our approach in improving FLM connectivity and quantifying the benefits of sharing trips is demonstrated.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.2208.04563</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2022-12
issn 2331-8422
language eng
recordid cdi_proquest_journals_2700435774
source Publicly Available Content (ProQuest)
subjects Automobiles
Car sharing
Developing countries
Fleet management
LDCs
Optimization
Public transportation
Ridership
Route planning
Simulation models
Subway stations
Vehicle routing
title An Agent-Based Fleet Management Model for First- and Last-Mile Services
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T03%3A39%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Agent-Based%20Fleet%20Management%20Model%20for%20First-%20and%20Last-Mile%20Services&rft.jtitle=arXiv.org&rft.au=Bhatnagar,%20Saumya&rft.date=2022-12-04&rft.eissn=2331-8422&rft_id=info:doi/10.48550/arxiv.2208.04563&rft_dat=%3Cproquest%3E2700435774%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a953-2997f7e490579b0cbaeae117b4aa2ada68e029df0be0624d0aef28edc50ffd013%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2700435774&rft_id=info:pmid/&rfr_iscdi=true