Dynamic reversible lane optimization in autonomous driving environments: balancing efficiency and safety. (English) Zbl 07799950
Summary: Reversible lanes are a cost-effective road control method to increase road capacity without significant infrastructure changes. However, their current fixed schedules and low frequency limit their effectiveness in adapting to dynamic traffic patterns. We propose leveraging autonomous driving technologies and cooperative intelligent transportation systems (C-ITS) to enable dynamic operation of reversible lanes. Our study aims to optimize reversible lane location, timing, and installation mode to maximize traffic capacity while minimizing costs, including potential risks and economic expenses. By formulating the problem as a minimum-cost maximum-flow approach for an urban traffic network, we address key decision-making challenges in setting up reversible lanes. We find that choosing the installation mode involves a trade-off between expenses and safety guarantees. We also explore how autonomous driving technology impacts the installation of dynamic reversible lanes. Our results show that dynamic operation with suitable modes significantly improves traffic optimization from both economic and efficiency perspectives. Additionally, autonomous driving reduces risk costs and enhances dynamic adjustment efficiency. We validate the proposed algorithm through comparisons and experiments with real-world traffic data from Xi’an city, demonstrating its practical effectiveness in optimizing reversible lanes.
MSC:
| 90B06 | Transportation, logistics and supply chain management |
| 90B10 | Deterministic network models in operations research |
| 90B35 | Deterministic scheduling theory in operations research |
| 68Q25 | Analysis of algorithms and problem complexity |
| 90C29 | Multi-objective and goal programming |
Software:
MOEA/DReferences:
| [1] | R. K. Ahuja, T. L. Magnanti and J. B. Orlin, Network Flows, Handbooks Oper. Res. Management Sci., 1. North-Holland Publishing Co., Amsterdam, 1989 |
| [2] | T. O. L. O. O. T. Alakoya Jolaoso Mewomo, A self adaptive inertial algorithm for solving split variational inclusion and fixed point problems with applications, J. Ind. Manage. Optim., 18, 239-265 (2021) · Zbl 1497.47090 · doi:10.3934/jimo.2020152 |
| [3] | P. K. A. Bansal Kockelman Singh, Assessing public opinions of and interest in new vehicle technologies: An austin perspective, Transp. Res. Part C Emerg. Technol., 67, 1-14 (2016) · doi:10.1016/j.trc.2016.01.019 |
| [4] | J. Bhuiyan, Amazon patented a highway network that controls self-driving cars and trucks, Accessed: 2023-5-31, (2017), https://www.vox.com/2017/1/17/14294498/amazon-self-driving-roads-patent |
| [5] | A. H. T. Chehri Mouftah, Autonomous vehicles in the sustainable cities, the beginning of a green adventure, Sustain. Cities Soc., 51, 101751 (2019) · doi:10.1016/j.scs.2019.101751 |
| [6] | S. H. Q. Chen Wang Meng, An optimal dynamic lane reversal and traffic control strategy for autonomous vehicles, IEEE Trans. Intell. Transp. Syst., 23, 3804-3815 (2022) · doi:10.1109/TITS.2021.3074011 |
| [7] | R. M. J. C. Curry Smith, Minimum-cost flow problems having arc-activation costs, Nav. Res. Logist., 69, 320-335 (2022) · Zbl 1523.90066 · doi:10.1002/nav.22006 |
| [8] | C. F. Daganzo, Stochastic network equilibrium with multiple vehicle types and asymmetric, indefinite link cost jacobians, Transp. Sci., 17, 282-300 (1983) · doi:10.1287/trsc.17.3.282 |
| [9] | A. Daniel, It’s time to reverse our thinking on reversible lanes, Accessed: 2015-3-19, (2015), https://www.bloomberg.com/news/articles/2015-03-19/what-the-golden-gate-bridge-can-teach-us-about-reversible-lanes-and-infrastructure. |
| [10] | K. A. A. K. E. C. R. Dannemiller Mondal Asmussen Bhat, Investigating autonomous vehicle impacts on individual activity-travel behavior, Transp. Res. Part A Policy Pract., 148, 402-422 (2021) · doi:10.1016/j.tra.2021.04.006 |
| [11] | A. R. P. E. de Blaeij Florax Rietveld Verhoef, The value of statistical life in road safety: A meta-analysis, Accid. Anal. Prev., 35, 973-986 (2003) · doi:10.1016/S0001-4575(02)00105-7 |
| [12] | K. A. S. T. Deb Pratap Agarwal Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ, IEEE Trans. Evol. Comput., 6, 182-197 (2002) · doi:10.1109/4235.996017 |
| [13] | Z. L. Di Yang, Reversible lane network design for maximizing the coupling measure between demand structure and network structure, Transp. Res. Part E: Logist. Trans. Rev., 141, 102021 (2020) · doi:10.1016/j.tre.2020.102021 |
| [14] | Y. F. S. Q. Fang Chu Mammar Shi, A new cut-and-solve and cutting plane combined approach for the capacitated lane reservation problem, Comput. Ind. Eng., 80, 212-221 (2015) · doi:10.1016/j.cie.2014.12.014 |
| [15] | Z. Y. Feng Zhu, A survey on trajectory data mining: Techniques and applications, IEEE Access, 4, 2056-2067 (2016) |
| [16] | J. I. M. E. Frejo Papamichail Papageorgiou Camacho, Macroscopic modeling and control of reversible lanes on freeways, IEEE Trans. Intell. Transp. Syst., 17, 948-959 (2016) · doi:10.1109/TITS.2015.2493127 |
| [17] | N. Gunantara, A review of multi-objective optimization: Methods and its applications, Cogent Eng., 5, 1502242 (2018) · doi:10.1080/23311916.2018.1502242 |
| [18] | L. P. C. Han Wu Chu, Service-oriented distributionally robust lane reservation, J. Ind. Inf. Integr., 25, 100302 (2022) · doi:10.1016/j.jii.2021.100302 |
| [19] | M. Hausknecht, T.-C. Au, P. Stone, D. Fajardo and T. Waller, Dynamic lane reversal in traffic management, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), (2011). |
| [20] | D. S. Hochbaum, The pseudoflow algorithm: A new algorithm for the maximum-flow problem, Oper. Res., 56, 992-1009 (2008) · Zbl 1167.90394 · doi:10.1287/opre.1080.0524 |
| [21] | Z. J. W. H. Huang Long Szeto Liu, Modeling and managing the morning commute problem with park-and-ride-sharing, Trans. Res. Part B: Methodol., 150, 190-226 (2021) · doi:10.1016/j.trb.2021.06.004 |
| [22] | S. P. L. L. Huband Hingston Barone While, A review of multiobjective test problems and a scalable test problem toolkit, IEEE Trans. Evol. Comput., 10, 477-506 (2006) |
| [23] | R. M. Q. W. Jiang Hu Wu Song, Traffic dynamics of bicycle flow: Experiment and modeling, Transp. Sci., 51, 998-1008 (2017) · doi:10.1287/trsc.2016.0690 |
| [24] | A. D.-Y. Karoonsoontawong Lin, Time-varying lane-based capacity reversibility for traffic management, Comput.-aided Civ. Infrastruct. Eng., 26, 632-646 (2011) · doi:10.1111/j.1467-8667.2011.00722.x |
| [25] | H. L. Q. Khoo Teoh Meng, A bi-objective optimization approach for exclusive bus lane selection and scheduling design, Eng. Optim., 46, 987-1007 (2014) · doi:10.1080/0305215X.2013.812728 |
| [26] | P. G. Kotagi Asaithambi, Microsimulation approach for evaluation of reversible lane operation on urban undivided roads in mixed traffic, Transp. Transp. Sci., 15, 1613-1636 (2019) · doi:10.1080/23249935.2019.1632387 |
| [27] | L. E. W. LeBlanc Morlok Pierskalla, An efficient approach to solving the road network equilibrium traffic assignment problem, Transp. Res., 9, 309-318 (1975) · doi:10.1016/0041-1647(75)90030-1 |
| [28] | H. Q. Li Zhang, Multiobjective optimization problems with complicated pareto sets, MOEA/D and NSGA-Ⅱ, IEEE Trans. Evol. Comput., 13, 284-302 (2009) |
| [29] | T. N. B. M. Li Wang Jiang Zhang, A bi-objective lane reservation problem considering dynamic traffic flow, IEEE Transactions on Intelligent Transportation Systems, 24, 367-381 (2022) · doi:10.1109/TITS.2022.3212553 |
| [30] | X. J. H. Li Chen Wang, Study on flow direction changing method of reversible lanes on urban arterial roadways in China, Procedia Soc. Behav. Sci., 96, 807-816 (2013) · doi:10.1016/j.sbspro.2013.08.092 |
| [31] | X. Li and Y. Fang, Dynamic environmental economic scheduling for microgrid using improved MOEA/D-M2M, Math. Probl. Eng., 2016 (2016), 2167153, 14 pp. · Zbl 1400.90172 |
| [32] | Y. J. L. P. Li Côté Callegari-Coelho Wu, Novel formulations and logic-based benders decomposition for the integrated parallel machine scheduling and location problem, INFORMS J. Comput., 34, 1048-1069 (2022) · Zbl 1492.90057 · doi:10.1287/ijoc.2021.1113 |
| [33] | Y. G. Liu Chang, An arterial signal optimization model for intersections experiencing queue spillback and lane blockage, Transp. Res. Part C Emerg. Technol., 19, 130-144 (2011) · doi:10.1016/j.trc.2010.04.005 |
| [34] | A. A. R. Manuel de Barros Tay, Traffic safety meta-analysis of reversible lanes, Accid. Anal. Prev., 148, 105751 (2020) · doi:10.1016/j.aap.2020.105751 |
| [35] | L. W. P. G. H. J. Mao Li Hu Zhou Zhang Dai, Design of real-time dynamic reversible lane in intelligent cooperative vehicle infrastructure system, J. Adv. Transp., 2020, 1-8 (2020) · doi:10.1155/2020/8838896 |
| [36] | P. B. Murray-Tuite Wolshon, Evacuation transportation modeling: An overview of research, development, and practice, Transp. Res. Part C Emerg. Technol., 27, 25-45 (2013) · doi:10.1016/j.trc.2012.11.005 |
| [37] | A. M. S. M. A. Muzahid Rahman Murad Kamal Alenezi, Multiple vehicle cooperation and collision avoidance in automated vehicles: Survey and an AI-enabled conceptual framework, Sci. Rep., 13, 603 (2023) · doi:10.1038/s41598-022-27026-9 |
| [38] | M. T. G. Nasri Bektaş Laporte, Route and speed optimization for autonomous trucks, Comput. Oper. Res., 100, 89-101 (2018) · Zbl 1458.90125 · doi:10.1016/j.cor.2018.07.015 |
| [39] | D. N. H. H. L. D. Ngoduy Hoang Vu Watling, Multiclass dynamic system optimum solution for mixed traffic of human-driven and automated vehicles considering physical queues, Trans. Res. Part B: Methodol., 145, 56-79 (2021) · doi:10.1016/j.trb.2020.12.008 |
| [40] | I. G. Panagiotopoulos Dimitrakopoulos, An empirical investigation on consumers’ intentions towards autonomous driving, Transp. Res. Part C Emerg. Technol., 95, 773-784 (2018) · doi:10.1016/j.trc.2018.08.013 |
| [41] | S. M. W. S. Patil Burris Shaw Concas, Variation in the value of travel time savings and its impact on the benefits of managed lanes, Transp. Plan. Technol., 34, 547-567 (2011) · doi:10.1080/03081060.2011.600068 |
| [42] | F. Preparata, Analysis of traffic flow on a signalized one-way artery, Transp. Sci., 6, 32-51 (1972) · doi:10.1287/trsc.6.1.32 |
| [43] | M. N. N. Rabbani Oladzad-Abbasabady Akbarian-Saravi, Ambulance routing in disaster response considering variable patient condition: Nsga-ii and mopso algorithms, J. Ind. Manage. Optim., 18, 1035-1062 (2022) · Zbl 1499.90032 · doi:10.3934/jimo.2021007 |
| [44] | C. Raskar and N. Shikha, A prototype of the dynamic traffic management: Smart barricade system, 2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), (2019). |
| [45] | S. K. S. P. C. Schroedl Wagstaff Rogers Langley Wilson, Mining GPS traces for map refinement, Data Min. Knowl. Discov., 9, 59-87 (2004) · doi:10.1023/B:DAMI.0000026904.74892.89 |
| [46] | F. D. Shahrokhi Matula, The maximum concurrent flow problem, J. Assoc. Comput. Mach., 37, 318-334 (1990) · Zbl 0696.68071 · doi:10.1145/77600.77620 |
| [47] | M. M. Shaikh Shaikh, Traffic control using reverse lane system: A queuing theory approach, Int. J. Inf. Bus. Manage, 10, 238-247 (2018) |
| [48] | Y. J. E. Stephanedes Kwon, Adaptive dmand-diversion prediction for integrated control of freeway corridors, Transp. Res. Part C Emerg. Technol., 1, 23-42 (1993) · doi:10.1016/0968-090X(93)90018-B |
| [49] | H. A. Tuydes Ziliaskopoulos, Tabu-based heuristic approach for optimization of network evacuation contraflow, Transp. Res. Rec., 1964, 157-168 (2006) · doi:10.1177/0361198106196400117 |
| [50] | E. J. E. D. L. L. V. P. R. E. Vingilis Roseborough Wiesenthal Vingilis-Jaremko Nuzzo Fischer Mann, Experimental examination of the effects of televised motor vehicle commercials on risk-positive attitudes, emotions and risky driving inclinations, Accid. Anal. Prev., 75, 86-92 (2015) · doi:10.1016/j.aap.2014.11.008 |
| [51] | J. W. Wang Deng, Optimizing capacity of signalized road network with reversible lanes, Transport, 33, 1-11 (2018) · doi:10.3846/16484142.2014.994227 |
| [52] | L. X. P. Wang Zhao Wu, Large-scale emergency medical services scheduling during the outbreak of epidemics, Ann. Oper. Res., 321, 1-25 (2023) · doi:10.1007/s10479-023-05218-4 |
| [53] | N. M. A. B. Wang Zhang Che Jiang, Bi-objective vehicle routing for hazardous materials transportation with no vehicles travelling in echelon, IEEE Trans. Intell. Transp. Syst., 19, 1867-1879 (2017) · doi:10.1109/TITS.2017.2742600 |
| [54] | S. I. C. Wollenstein-Betech Paschalidis Cassandras, Optimizing lane reversals in transportation networks to reduce traffic congestion: A global optimization approach, Transp. Res. Part C Emerg. Technol., 143, 103840 (2022) · doi:10.1016/j.trc.2022.103840 |
| [55] | B. L. Wolshon Lambert, Reversible lane systems: Synthesis of practice, J. Transp. Eng., 132, 933-944 (2006) |
| [56] | J. H. Z. H. Wu Sun Gao Zhang, Reversible lane-based traffic network optimization with an advanced traveller information system, Eng. Optim., 41, 87-97 (2009) · doi:10.1080/03052150802368799 |
| [57] | P. L. A. Y. C. Wu Xu D’Ariano Zhao Chu, Novel formulations and improved differential evolution algorithm for optimal lane reservation with task merging, IEEE Trans. Intell. Transp. Syst., 23, 21329-21344 (2022) |
| [58] | C. Y. H. W. X. Yu Feng Liu Ma Yang, Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections, Trans. Res. Part B: Methodol., 112, 89-112 (2018) · doi:10.1016/j.trb.2018.04.007 |
| [59] | M. N. Z. B. Zhang Wang He Jiang, Vehicle routing optimization for hazmat shipments considering catastrophe avoidance and failed edges, Transp. Res. Part E: Logist. Trans. Rev., 150, 102337 (2021) · doi:10.1016/j.tre.2021.102337 |
| [60] | M. N. Z. Z. Y. Zhang Wang He Yang Guan, Bi-objective vehicle routing for hazardous materials transportation with actual load dependent risks and considering the risk of each vehicle, IEEE Trans. Eng. Manage., 66, 429-442 (2018) · doi:10.1109/TEM.2018.2832049 |
| [61] | Q. H. Zhang Li, MOEA/D: A multiobjective evolutionary algorithm based on decomposition, IEEE Trans. Evol. Comput., 11, 712-731 (2007) |
| [62] | X. W. M. S. Zhang Liu Levin Waller, Equilibrium analysis of morning commuting and parking under spatial capacity allocation in the autonomous vehicle environment, Transp. Res. Part E: Logist. Trans. Rev., 172, 103071 (2023) · doi:10.1016/j.tre.2023.103071 |
| [63] | J. Y. X. Zhao Liu Yang, Operation of signalized diamond interchanges with frontage roads using dynamic reversible lane control, Transp. Res. Part C Emerg. Technol., 51, 196-209 (2015) · doi:10.1016/j.trc.2014.11.010 |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
