How to Improve the Transit Service with Integrated Operational Strategies Considering Emissions under Heterogeneous Demand
Publication: Journal of Urban Planning and Development
Volume 149, Issue 4
Abstract
Recently, traffic problems such as congestion and emission have been increasing. Transit travel is considered to be one of the effective ways to relieve these problems. The attractiveness of transit travel can be improved by integrating operational strategies with multitype services. Therefore, a study focusing on tapping the potential of integrated operational strategies, which combine local services, skip-stop services, and short-turning services, considering emissions under heterogeneous demand, was conducted. Two types of integrated service patterns were proposed. Pattern 1 comprised local services, skip-stop services, and short-turning services, all operating simultaneously and independently, while Pattern 2 comprised the combined local services and skip-stop services with a flexible route length. The estimation of heterogeneous travel demand for different services and high-resolution bus emissions based on short trips between stops and at stops was conducted. The optimized models to minimize system costs considering passengers, agencies, and environmental interests were developed to explore the effectiveness of integrated operational strategies for performing the transit service. The real-world cases of Bus Route 4 and Route 543 in Beijing, China, were studied. The performances of the proposed strategies under the two integrated service patterns were compared with the baseline. The results showed that the total costs of two integrated service patterns are reduced significantly, with a maximum reduction of above 30%. Moreover, under the route of limited vehicles and denes travel demand, Pattern 2 implementing skip-stop services in a flexible route length had more advantages over Pattern 1, where all three services existed simultaneously. The finding can be used to design the preferred transit development strategy and improve the service quality.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors acknowledge that this paper is supported by the National Natural Science Foundation of China (NSFC) under Grant #71871013. Thanks are extended to the anonymous reviewers for their helpful comments on this paper.
Notation
The following symbols are used in this paper:
- C
- vehicle-rated passenger capacity (persons);
- C′
- total cost (RMB);
- CE
- emission cost (RMB);
- CO
- operation cost (RMB);
- CP
- travel time cost (RMB);
- i, j, k, p
- stop numbers;
- ,
- number of emissions of pollutant k for all-stop services and skip-stop services (g), respectively;
- F
- fleet size (vehicles);
- fi,j, fb
- frequencies of all-stop services and skip-stop services (veh/h), respectively;
- fuel1, fuel2
- fuel consumption of all-stop services and skip-stop services (g), respectively;
- hmin, hmax
- lower or upper limit of headway (s);
- L
- total route length (m);
- Li, Lj
- route length from stop i or j to the origination stop (m);
- M, N
- short-turn points M and N, respectively;
- n
- total number of stops;
- number of passengers choosing all-stop services (persons);
- number of passengers choosing skip-stop services (persons);
- number of passengers choosing to transfer (persons);
- T
- duration of the statistical period (h);
- tI
- in-vehicle time (s);
- tR
- transfer time (s);
- tW
- waiting time (s);
- uW
- unit time value for waiting time (RMB/s);
- uR
- unit time value for transfer time (RMB/s);
- uI
- unit time value for in-vehicle time (RMB/s);
- us
- unit time salary of crew members (RMB/h);
- uv
- unit purchase costs per vehicle (RMB/vehicle*h);
- uf
- unit price of LNG (liquefied natural gas) (RMB/g);
- uk
- unit emissions costs of pollutant k (RMB/g);
- v1, v2
- average speed of all-stop services and skip-stop services (m/s);
- maximum load factor;
- 0–1 variable, in which = 1 if passengers board at stop p from stop i to stop j; otherwise, ηs = 0;
- 0–1 variable, in which ηs = 1 if passengers pass through stop p from stop i to stop j; otherwise, ηs = 0;
- λi
- 0–1 decision variable, in which λi = 1 if stop i is permitted to provide skip-stop services; otherwise, λi = 0; and
- λp
- 0–1 variable, in which ηs = 1 if skip-stop services are provided at stop p; otherwise, ηs = 0.
References
Agarwal, A., and I. Kaddoura. 2020. “On-road air pollution exposure to cyclists in an agent-based simulation framework.” Period. Polytech. Transp. Eng. 48: 117–125. https://doi.org/10.3311/PPtr.12661.
Ansari Esfeh, M., S. C. Wirasinghe, S. Saidi, and L. Kattan. 2021. “Waiting time and headway modelling for urban transit systems—A critical review and proposed approach.” Transp. Rev. 41: 141–163. https://doi.org/10.1080/01441647.2020.1806942.
Bhandari, D., N. R. Pal, and S. K. Pal. 1994. “Directed mutation in genetic algorithms.” Inf. Sci. 79: 251–270. https://doi.org/10.1016/0020-0255(94)90123-6.
Cao, Z., and A. (Avi) Ceder. 2019. “Autonomous shuttle bus service timetabling and vehicle scheduling using skip-stop tactic.” Transp. Res. Part C Emerging Technol. 102: 370–395. https://doi.org/10.1016/j.trc.2019.03.018.
Ceder, A. 1989. “Optimal design of transit short-turn trips.” Transp. Res. Rec. 1221: 8–22.
Ceder, A. 2007. Public transit planning and operation: Theory, modelling and practice. Amsterdam, Netherlands: Butterworth-Heinemann.
Ceder, A. 2016. Public transit planning and operation: Modeling, practice and behavior. 2nd ed. Boca Raton, FL: CRC Press.
Chappidi, E., and A. Singh. 2022. “An evolutionary approach for obnoxious cooperative maximum covering location problem.” Appl. Intell. 52: 16651–16666. https://doi.org/10.1007/s10489-022-03239-3.
Chen, J., Z. Liu, S. Zhu, and W. Wang. 2015. “Design of limited-stop bus service with capacity constraint and stochastic travel time.” Transp. Res. Part E Logist. Transp. Rev. 83: 1–15. https://doi.org/10.1016/j.tre.2015.08.007.
Chen, X., X. Han, L. Yu, and C. Wei. 2017. “Does operation scheduling make a difference: Tapping the potential of optimized design for skipping-stop strategy in reducing bus emissions.” Sustainability 9 (10): 1737. https://doi.org/10.3390/su9101737.
Choudhary, R., S. Ratra, and A. Agarwal. 2022. “Multimodal routing framework for urban environments considering real-time air quality and congestion.” Atmos. Pollut. Res. 13: 101525. https://doi.org/10.1016/j.apr.2022.101525.
Chriqui, C., and P. Robillard. 1975. “Common bus lines.” Transp. Sci. 9 (2): 115–121. https://doi.org/10.1287/trsc.9.2.115.
Cortés, C. E., S. Jara-Díaz, and A. Tirachini. 2011. “Integrating short turning and deadheading in the optimization of transit services.” Transp. Res. Part A Policy Pract. 45 (5): 419–434. https://doi.org/10.1016/j.tra.2011.02.002.
Daganzo, C. F., and Y. Ouyang. 2019. Public transportation systems: Principles of system design, operations planning and real-timecontrol. Singapore: World Scientific.
Delle Site, P., and F. Filippi. 1998. “Service optimization for bus corridors with short-turn strategies and variable vehicle size.” Transp. Res. Part A Policy Pract. 32 (1): 19–38. https://doi.org/10.1016/S0965-8564(97)00016-5.
Durrett, R. 2019. Vol. 49 of Probability: Theory and examples. Cambridge, UK: Cambridge University Press.
Fan, W., and Y. Ran. 2021. “Planning skip-stop services with schedule coordination.” Transp. Res. Part E Logist. Transp. Rev. 145: 102119. https://doi.org/10.1016/j.tre.2020.102119.
Fei, H., C. Zhang, and X. Wang. 2018. “Optimizing the composite cost involved in road motor-transporting trucks by taking into account traffic condition.” Discret. Dyn. Nat. Soc. 2018: 8703852. https://doi.org/10.1155/2018/8703852.
Fu, L., and Q. Liu. 2003. “Real-time optimization model for dynamic scheduling of transit operations.” Transp. Res. Rec. 3 (1857): 48–55. https://doi.org/10.3141/1857-06.
Furth, P. G. 1985. “Alternating deadheading in Bus route operations.” Transp. Sci. 19 (1): 13–28. https://doi.org/10.1287/trsc.19.1.13.
Furth, P. G., and F. B. Day. 1985. “Transit routing and scheduling strategies for heavy demand corridors.” Transp. Res. Rec. 1011: 23–26.
Gkiotsalitis, K. 2019. “Robust stop-skipping at the tactical planning stage with evolutionary optimization.” Transp. Res. Rec. 2673 (3): 611–623. https://doi.org/10.1177/0361198119834549.
Gkiotsalitis, K. 2021. “Stop-skipping in rolling horizons.” Transp. A Transp. Sci. 17 (4): 1–29. https://doi.org/10.1080/23249935.2020.1798554.
Gkiotsalitis, K., and O. Cats. 2021. “At-stop control measures in public transport: Literature review and research agenda.” Transp. Res. Part E Logist. Transp. Rev. 145: 102176. https://doi.org/10.1016/j.tre.2020.102176.
Gkiotsalitis, K., Z. Wu, and O. Cats. 2019. “A cost-minimization model for bus fleet allocation featuring the tactical generation of short-turning and interlining options.” Transp. Res. Part C Emerging Technol. 98: 14–36. https://doi.org/10.1016/j.trc.2018.11.007.
Gu, W., Z. Amini, and M. J. Cassidy. 2016. “Exploring alternative service schemes for busy transit corridors.” Transp. Res. Part B Methodol. 93: 126–145. https://doi.org/10.1016/j.trb.2016.07.010.
Han, X. 2019. Optimization of integrated scheduling plan considering bus emissions. Beijing: Beijing Jiaotong Univ.
Jaynes, E. T. 2003. Probability theory: The logic of science. Cambridge, UK: Cambridge University Press.
Larrain, H., and J. C. Muñoz. 2016. “When and where are limited-stop bus services justified?” Transp. A Transp. Sci. 12 (9): 811–831. https://doi.org/10.1080/23249935.2016.1177135.
Leiva, C., J. C. Muñoz, R. Giesen, and H. Larrain. 2010. “Design of limited-stop services for an urban bus corridor with capacity constraints.” Transp. Res. Part B Methodol. 44 (10): 1186–1201. https://doi.org/10.1016/j.trb.2010.01.003.
Loeve, M. 2017. Probability theory. New York: Courier Dover Publications.
Mei, Y., W. Gu, M. Cassidy, and W. Fan. 2021. “Planning skip-stop transit service under heterogeneous demands.” Transp. Res. Part B Methodol. 150: 503–523. https://doi.org/10.1016/j.trb.2021.06.008.
Mohammed, A., A. Shalaby, and E. J. Miller. 2014. “Development of P-TRANE: GIS-based model of bus transit network evolution.” J. Urban Plann. Dev. 140 (1): 1–11. https://doi.org/10.1061/(asce)up.1943-5444.0000166.
Mou, Z., H. Zhang, and S. Liang. 2020. “Reliability optimization model of stop-skipping bus operation with capacity constraints.” J. Adv. Transp. 2020: 4317402. https://doi.org/10.1155/2020/4317402.
Pan, S., J. Yu, X. Yang, Y. Liu, and N. Zou. 2015. “Designing a flexible feeder transit system serving irregularly shaped and gated communities: Determining service area and feeder route planning.” J. Urban Plann. Dev. 141 (3): 1–9. https://doi.org/10.1061/(asce)up.1943-5444.0000224.
Pei, M., P. Lin, and J. Ou. 2019. “Real-time optimal scheduling model for transit system with flexible bus line length.” Transp. Res. Rec. 2673 (4): 800–810. https://doi.org/10.1177/0361198119837502.
Perugu, H. 2018. “Emission modelling of light-duty vehicles in India using the revamped VSP-based MOVES model: The case study of Hyderabad.” Transp. Res. Part D Transp. Environ. 68: 150–163. https://doi.org/10.1016/j.trd.2018.01.031.
Qu, H., S. I. Chien, and X. Liu. 2016. “Improving vehicle emissions of bus transit with integrated service and different vehicle sizes.” In Proc., 95th Annual Meeting of the Transportation Research Board. Washington, DC: Transportation Research Board.
Singh, V., K. K. Meena, and A. Agarwal. 2021. “Travellers’ exposure to air pollution: A systematic review and future directions.” Urban Clim. 38: 100901. https://doi.org/10.1016/j.uclim.2021.100901.
Soto, G., H. Larrain, and J. C. Muñoz. 2017. “A new solution framework for the limited-stop bus service design problem.” Transp. Res. Part B Methodol. 105: 67–85. https://doi.org/10.1016/j.trb.2017.08.026.
Tang, C., A. Avi Ceder, and S. Zhao. 2018a. “Minimizing user and operator costs of single line bus service using operational strategies.” Transport 33 (4): 993–1004. https://doi.org/10.3846/transport.2018.6595.
Tang, C., A. Ceder, and Y. E. Ge. 2018b. “Optimal public-transport operational strategies to reduce cost and vehicle’s emission.” PLoS One 13 (8): 1–17. https://doi.org/10.1371/journal.pone.0201138.
Tang, C., A. Ceder, Y. E. Ge, and N. Wu. 2020. “Optimal operational strategies for multiple bus lines considering passengers’ preferences.” Transp. Res. Rec. 2674 (5): 572–586. https://doi.org/10.1177/0361198120917159.
Tang, C., A. Ceder, S. Zhao, and Y. E. Ge. 2019. “Vehicle scheduling of single-line bus service using operational strategies.” IEEE Trans. Intell. Transp. Syst. 20 (3): 1149–1159. https://doi.org/10.1109/TITS.2018.2841061.
Tuzun Aksu, D., and U. Akyol. 2014. “Transit coordination using integer-ratio headways.” IEEE Trans. Intell. Transp. Syst. 15: 1633–1642. https://doi.org/10.1109/TITS.2014.2301821.
Ulusoy, Y. Y., S. Chien, and C. H. Wei. 2010. “Optimal all-stop, short-turn, and express transit services under heterogeneous demand.” Transp. Res. Rec. 2197: 8–18. https://doi.org/10.3141/2197-02.
USEPA. 2010. Technical support document: Social cost of carbon for regulatory impact analysis, under executive order 12866. interagency working group on social cost of carbon. Washington, DC: EPA.
USEPA. 2016. The social cost of carbon. Washington, DC: EPA.
Vuchic, V. R. 2005. Urban transit: Operations, planning, and economics. New York: John Wiley & Sons.
Wang, D. Z. W., A. Nayan, and W. Y. Szeto. 2018. “Optimal bus service design with limited stop services in a travel corridor.” Transp. Res. Part E Logist. Transp. Rev. 111: 70–86. https://doi.org/10.1016/j.tre.2018.01.007.
Wang, Y. 2015. Passenger flow assignment of urban all-stop bus and skip-stop bus based on logit model. Beijing: Beijing Jiaotong Univ.
WRI (World Resources Institute). 2017. Transport emissions & social cost assessment: Methodology guide. Washington, DC: WRI.
Wu, W., R. Liu, W. Jin, and C. Ma. 2019. “Simulation-based robust optimization of limited-stop bus service with vehicle overtaking and dynamics: A response surface methodology.” Transp. Res. Part E Logist. Transp. Rev. 130: 61–81. https://doi.org/10.1016/j.tre.2019.08.012.
Wu, Y., G. Song, and L. Yu. 2014. “Sensitive analysis of emission rates in MOVES for developing site-specific emission database.” Transp. Res. Part D Transp. Environ. 32: 193–206. https://doi.org/10.1016/j.trd.2014.07.009.
Yang, A., B. Wang, J. Huang, and C. Li. 2020. “Service replanning in urban rail transit networks: Cross-line express trains for reducing the number of passenger transfers and travel time.” Transp. Res. Part C Emerging Technol. 115: 102629. https://doi.org/10.1016/j.trc.2020.102629.
Yang, X., Y. Ji, Y. Du, and H. M. Zhang. 2017. “Bi-level model for design of transit short-turning service considering bus crowding.” Transp. Res. Rec. 2649 (1): 52–60. https://doi.org/10.3141/2649-06.
Yu, Q., T. Li, and H. Li. 2016. “Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving.” Appl. Energy 161: 101–111. https://doi.org/10.1016/j.apenergy.2015.09.096.
Zhang, H., S. Zhao, Y. Cao, H. Liu, and S. Liang. 2017. “Real-time integrated limited-stop and short-turning bus control with stochastic travel time.” J. Adv. Transp. 2017: 2960728. https://doi.org/10.1155/2017/2960728.
Zhang, H., S. Zhao, H. Liu, and S. Liang. 2016. “Design of integrated limited-stop and short-turn services for a bus route.” Math. Probl. Eng. 2016: 7901634. https://doi.org/10.1155/2016/7901634.
Zhang, L., J. Huang, Z. Liu, and H. L. Vu. 2021a. “An agent-based model for real-time bus stop-skipping and holding schemes.” Transp. A Transp. Sci. 17 (4): 615–647. https://doi.org/10.1080/23249935.2020.1802363.
Zhang, R., S. Yin, M. Ye, Z. Yang, and S. He. 2021b. “A timetable optimization model for urban rail transit with express/local mode.” J. Adv. Transp. 2021: 5589185. https://doi.org/10.1155/2021/5589185.
Zheng, Y., W. Li, F. Qiu, and H. Wei. 2020. “Travelers’ potential demand toward flex-route transit: Nanjing, China, case study.” J. Urban Plann. Dev. 146 (1): 1–10. https://doi.org/10.1061/(asce)up.1943-5444.0000538.
Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 149 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jul 19, 2022
Accepted: May 24, 2023
Published online: Aug 3, 2023
Published in print: Dec 1, 2023
Discussion open until: Jan 3, 2024
ASCE Technical Topics:
- Air pollution
- Benefit cost ratios
- Buses
- Business management
- Chemical properties
- Chemistry
- Emissions
- Engineering fundamentals
- Environmental engineering
- Financial management
- Heterogeneity
- Highway transportation
- Infrastructure
- Models (by type)
- Optimization models
- Pollution
- Practice and Profession
- Traffic congestion
- Traffic engineering
- Traffic management
- Transportation engineering
- Travel demand
- Travel patterns
- Vehicles
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.