The influence of passenger load, driving cycle, fuel price and different types of buses on the cost of transport service in the BRT system in Curitiba, Brazil
Dennis Dreier (ddreier@kth.se),
Semida Silveira,
Dilip Khatiwada,
Keiko V. O. Fonseca,
Rafael Nieweglowski and
Renan Schepanski
Additional contact information
Dennis Dreier: KTH Royal Institute of Technology
Semida Silveira: KTH Royal Institute of Technology
Dilip Khatiwada: KTH Royal Institute of Technology
Keiko V. O. Fonseca: Federal University of Technology – Paraná (UTFPR)
Rafael Nieweglowski: Volvo Bus Corporation
Renan Schepanski: Volvo Bus Corporation
Transportation, 2019, vol. 46, issue 6, No 13, 2195-2242
Abstract:
Abstract This study analyses the influence of passenger load, driving cycle, fuel price and four different types of buses on the cost of transport service for one bus rapid transit (BRT) route in Curitiba, Brazil. First, the energy use is estimated for different passenger loads and driving cycles for a conventional bi-articulated bus (ConvBi), a hybrid-electric two-axle bus (HybTw), a hybrid-electric articulated bus (HybAr) and a plug-in hybrid-electric two-axle bus (PlugTw). Then, the fuel cost and uncertainty are estimated considering the fuel price trends in the past. Based on this and additional cost data, replacement scenarios for the currently operated ConvBi fleet are determined using a techno-economic optimisation model. The lowest fuel cost ranges for the passenger load are estimated for PlugTw amounting to (0.198–0.289) USD/km, followed by (0.255–0.315) USD/km for HybTw, (0.298–0.375) USD/km for HybAr and (0.552–0.809) USD/km for ConvBi. In contrast, the coefficient of variation ($$C_{v}$$Cv) of the combined standard uncertainty is the highest for PlugTw ($$C_{v}$$Cv: 15–17%) due to stronger sensitivity to varying bus driver behaviour, whereas it is the least for ConvBi ($$C_{v}$$Cv: 8%). The scenario analysis shows that a complete replacement of the ConvBi fleet leads to considerable higher cost of transport service on the BRT route, amounting to an increase by 64% to 139%, depending on the bus fleet composition. Meanwhile, the service quality is improved resulting in 42% up to 64% less waiting time for passengers at a bus stop.
Keywords: Bi-articulated; Driving pattern; Fuel consumption; Optimization; Ridership; Service quality (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:kap:transp:v:46:y:2019:i:6:d:10.1007_s11116-018-9925-0
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DOI: 10.1007/s11116-018-9925-0
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