A survey on demand-responsive public bus systems

Vansteenwegen, Pieter; Melis, Lissa; Aktaş, Dilay; Montenegro, Bryan David Galarza; Vieira, Fábio Sartori; Sörensen, Kenneth

doi:10.1016/j.trc.2022.103573

Cited by 61 publications

(33 citation statements)

References 139 publications

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“…As a final consideration, we note that studies optimizing the decision variables that are elements of strategic planning or tactical planning for SFT like headway and slack time are very limited and are essential to define a timetable for SFT operation [23]. Although Alshalalfah [17] and Fu [8] suggested some interaction between slack time and headway, they focused on the optimization of slack time, assuming a fixed value of headway for system design.…”

Section: Studies Focusing On Headway Optimization For Flexible Transitmentioning

confidence: 99%

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Mishra

Mehran

2023

IEEE Access

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Semi-flexible transit (SFT) is commonly discussed as a cost-effective alternative to serving public transportation users in low-demand conditions. We hypothesize that joint optimization of service headway and slack time per trip for route deviation is essential for designing a schedule for the operation of an integrated SFT that can meet both fixed-route and paratransit demand. An integrated SFT has the potential to lower the cost of transportation for regular transit users (both operators and riders) while redirecting potential paratransit riders to less expensive transit modes; thus, reducing demand for overwhelmed paratransit services operating with limited resources. The optimization problem has three competing objectives: minimizing operator costs, minimizing user costs, and maximizing service benefits. Two state-ofthe-art multi-objective evolutionary algorithms NSGA-II and SMPSO are compared to obtain the most representative deterministic Pareto optimal solution set. This study has three major contributions. First, quantile regression is used to suggest multiple slack time values for a given headway that transit planners can consider when generating a static schedule for SFT operation. Second, relationships derived to analyze cost trade-offs suggest that headway governs operator cost and is negatively correlated, user cost is positively and equally influenced by both variables, and slack time governs service benefit and is positively correlated. Third, sensitivity analysis for an integrated SFT operation reveals that low-capacity minivans and standard vans offer higher vehicle occupancy and cost efficiency, mostly economical for low to medium demand (5-20 pass/hr), low permissible deviation from the fixed route is desirable during peak hours to avoid delays for passengers on-board, and extreme weather conditions dramatically and negatively influence costs. Policy recommendations for integrated SFT implementation include a recommendation for fare structure design addressing service equity through surcharges/discounts, vehicle technology and service booking technology advancements for cost reduction, and fleet mix design through estimation of passenger loading profile. The application of the study methodology is demonstrated for a low-demand bus route in Regina, Canada.

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Section: Studies Focusing On Headway Optimization For Flexible Transitmentioning

confidence: 99%

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Mishra

Mehran

2023

IEEE Access

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“…The central challenge to the ride-pooling problem pertains to its computational complexity -the number of feasible groups of travellers grows combinatorically and even for relatively small problems the search space quickly exceeds reasonable processing capabilities. This is also true for the public transit network design problem, where solutions are limited to heuristic approximations and the dis-crete search space is not exploitable in practice (Vansteenwegen et al, 2022). In a previous study, we managed to successfully contain the search space and propose an exact solution for the ride-pooling problem.…”

Section: Research Approach and Contributionmentioning

confidence: 99%

“…Research on ride-pooling shares several similarities with on-demand public transport (for a recent review of the latter see Vansteenwegen et al (2022)). The mathematical complexity is similarly challenging and supply-side and demand-side constraints are similar (Yoon et al, 2022), in both systems a critical mass is needed to take off (Papanikolaou and Basbas, 2021), yet the strategic planning perspective in the design of on-demand public transport remains more popular than in ride-pooling (Narayan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Hyper-pool: pooling private trips into high-occupancy transit-like attractive shared rides

Kucharski¹,

Cats²

2022

Preprint

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We propose Hyper-pool, an analytical, offline, utility-driven ride-pooling algorithm to aggregate individual trip requests into attractive shared rides of high-occupancy.We depart from our ride-pooling ExMAS algorithm where single rides are pooled into attractive door-to-door rides and propose two novel demand-side algorithms for further aggregating individual demand towards more compact pooling. First, we generate stop-to-stop rides, with a single pick up and drop off points optimal for all the travellers. Second, we bundle such rides again, resulting with hyper-pooled rides compact enough to resemble public transport operations. We propose a bottom-up framework where the pooling degree of identified rides is gradually increased, thereby ensuring attractiveness at subsequent aggregation levels.Our Hyper-pool method outputs the set of attractive pooled rides per service variant for a given travel demand. The algorithms are publicly available and reproducible. It is applicable for real-size demand datasets and opens new opportunities for exploiting the limits of ride-pooling potential.In our Amsterdam case-study we managed to pool over 220 travellers into 40 hyper-pooled rides of average occupancy 5.8 pax/veh.

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“…Door-to-door demand responsive transit (DRT) has emerged as a promising solution for sustainable mobility to meet travellers' diverse and individualized demand [3,4]. Motivated by breakthroughs in mobile internet technologies, a more flexible DRT service with appbased reservation platforms has been emergence to drive the reinvention of transit services as a whole [5].As shown in Table 1 [6,7], in contrast to conventional bus and customized bus (CB), dynamic DRT can moderately adjust routes and schedules to respond to real-time travel demands [8,9]. Meanwhile, it is costeffective, environmentally friendly, and socially aware compared to taxi [6].…”

Section: Introductionmentioning

confidence: 99%

Towards a more flexible demand responsive transit service with compensation mechanism considering boundedly rational passengers

Wang

Qin

et al. 2023

IET Intelligent Trans Sys

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Demand responsive transit (DRT) with app-based reservation platforms is experiencing a renaissance to bring the tremendous potential for mobility in the urban universe. Nevertheless, how to attract and retain passengers for long-term use has become one of the most significant problems. The decision-making psychology of passengers is often overlooked but incredibly critical in the practical applicability of DRT services. This paper proposes a more flexible DRT service with soft time windows considering boundedly rational passengers. A compensation mechanism is developed to alleviate the dissatisfaction of passengers while considerably promoting the system efficiency. A two-stage model is designed to incorporate bounded rationality into the optimization process of mixed demand, including the static phase for reservation passengers and the dynamic phase for real-time passengers. To enhance the computational efficiency, a hybrid heuristic algorithm combining spatiotemporal clustering and non-dominated sorting genetic algorithm (NSGA)-II is constructed to obtain the Pareto solutions set. An illustrative example of the Nguyen-Dupuis network is presented to demonstrate the validity of the algorithm. Subsequently, a largescale case study in Beijing evaluated the applicability of DRT in the real-world network. The results reveal that dynamic DRT with compensation mechanism can substantially improve the system performance while ensuring the service quality. The response rate of passengers has been dramatically promoted to 80%. The operating profit has been enormously improved by up to 73%. Therefore, this study is radically conducive to understanding the passenger's decision-making psychology while constructing a more cost-efficient flexible strategy for the service provider.

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A survey on demand-responsive public bus systems

Cited by 61 publications

References 139 publications

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Optimal Design of Integrated Semi-Flexible Transit Services in Low-Demand Conditions

Hyper-pool: pooling private trips into high-occupancy transit-like attractive shared rides

Towards a more flexible demand responsive transit service with compensation mechanism considering boundedly rational passengers

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