Worst-Case Response Time of Mixed Vehicles at Complex Intersections
Operating autonomous vehicles (AVs) and human-driven vehicles (HVs) at urban intersections while observing requirements of safety and service level is complex due not only to the existence of multiple inflow and outflow lanes, conflicting crossing zones, and low-speed conditions but also due to diff...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10443586/ |
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| _version_ | 1832590323049562112 |
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| author | Radha Reddy Luis Almeida Harrison Kurunathan Miguel Gutierrez Gaitan Pedro M. Santos Eduardo Tovar |
| author_facet | Radha Reddy Luis Almeida Harrison Kurunathan Miguel Gutierrez Gaitan Pedro M. Santos Eduardo Tovar |
| author_sort | Radha Reddy |
| collection | DOAJ |
| description | Operating autonomous vehicles (AVs) and human-driven vehicles (HVs) at urban intersections while observing requirements of safety and service level is complex due not only to the existence of multiple inflow and outflow lanes, conflicting crossing zones, and low-speed conditions but also due to differences between control mechanisms of HVs and AVs. Intelligent intersection management (IIM) strategies can tackle the coordination of mixed AV/HV intersections while improving intersection throughput and reducing travel delays and fuel wastage in the average case. An endeavor relevant to traffic planning and safety is assessing whether given worst-case service levels can be met. Given a specific arrival pattern, this can be done via the worst-case response time (WCRT) that any vehicle experiences when crossing intersections. In this research line, this paper estimates WCRT upper bounds and discusses the analytical characterization of arrival and service curves, including estimating maximum queue length and associated worst-case waiting time for various traffic arrival patterns. This analysis is then used to compare six state-of-the-art intersection management approaches from conventional to intelligent and synchronous. The analytical results show the advantage of employing a synchronous management approach and are validated with the vehicles floating car data (timestamped location and speed) and simulations carried out using SUMO. |
| format | Article |
| id | doaj-art-4a9e0e8a6f1a43d5a6965da0bdda5b0b |
| institution | Kabale University |
| issn | 2687-7813 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj-art-4a9e0e8a6f1a43d5a6965da0bdda5b0b2025-01-24T00:02:37ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132024-01-01518620110.1109/OJITS.2024.336879710443586Worst-Case Response Time of Mixed Vehicles at Complex IntersectionsRadha Reddy0https://orcid.org/0000-0002-9651-3294Luis Almeida1https://orcid.org/0000-0002-9544-3028Harrison Kurunathan2Miguel Gutierrez Gaitan3https://orcid.org/0000-0002-3307-8731Pedro M. Santos4https://orcid.org/0000-0002-7162-0560Eduardo Tovar5CISTER Research Center, Porto, PortugalCISTER Research Center, Porto, PortugalCISTER Research Center, Porto, PortugalCISTER Research Center, Porto, PortugalCISTER Research Center, Porto, PortugalCISTER Research Center, Porto, PortugalOperating autonomous vehicles (AVs) and human-driven vehicles (HVs) at urban intersections while observing requirements of safety and service level is complex due not only to the existence of multiple inflow and outflow lanes, conflicting crossing zones, and low-speed conditions but also due to differences between control mechanisms of HVs and AVs. Intelligent intersection management (IIM) strategies can tackle the coordination of mixed AV/HV intersections while improving intersection throughput and reducing travel delays and fuel wastage in the average case. An endeavor relevant to traffic planning and safety is assessing whether given worst-case service levels can be met. Given a specific arrival pattern, this can be done via the worst-case response time (WCRT) that any vehicle experiences when crossing intersections. In this research line, this paper estimates WCRT upper bounds and discusses the analytical characterization of arrival and service curves, including estimating maximum queue length and associated worst-case waiting time for various traffic arrival patterns. This analysis is then used to compare six state-of-the-art intersection management approaches from conventional to intelligent and synchronous. The analytical results show the advantage of employing a synchronous management approach and are validated with the vehicles floating car data (timestamped location and speed) and simulations carried out using SUMO.https://ieeexplore.ieee.org/document/10443586/managementintelligent transportation systemsmixed traffictraffic waiting timeurban traffic management |
| spellingShingle | Radha Reddy Luis Almeida Harrison Kurunathan Miguel Gutierrez Gaitan Pedro M. Santos Eduardo Tovar Worst-Case Response Time of Mixed Vehicles at Complex Intersections IEEE Open Journal of Intelligent Transportation Systems management intelligent transportation systems mixed traffic traffic waiting time urban traffic management |
| title | Worst-Case Response Time of Mixed Vehicles at Complex Intersections |
| title_full | Worst-Case Response Time of Mixed Vehicles at Complex Intersections |
| title_fullStr | Worst-Case Response Time of Mixed Vehicles at Complex Intersections |
| title_full_unstemmed | Worst-Case Response Time of Mixed Vehicles at Complex Intersections |
| title_short | Worst-Case Response Time of Mixed Vehicles at Complex Intersections |
| title_sort | worst case response time of mixed vehicles at complex intersections |
| topic | management intelligent transportation systems mixed traffic traffic waiting time urban traffic management |
| url | https://ieeexplore.ieee.org/document/10443586/ |
| work_keys_str_mv | AT radhareddy worstcaseresponsetimeofmixedvehiclesatcomplexintersections AT luisalmeida worstcaseresponsetimeofmixedvehiclesatcomplexintersections AT harrisonkurunathan worstcaseresponsetimeofmixedvehiclesatcomplexintersections AT miguelgutierrezgaitan worstcaseresponsetimeofmixedvehiclesatcomplexintersections AT pedromsantos worstcaseresponsetimeofmixedvehiclesatcomplexintersections AT eduardotovar worstcaseresponsetimeofmixedvehiclesatcomplexintersections |