Smaller Buses Research Articles

Charging Infrastructure and Schedule Planning for a Public Transit Network with a Mixed Fleet of Electric and Diesel Buses

Promoting battery electric buses (BEBs) can reduce fuel consumption and air pollution from the transit system. A complete transition from the current diesel fleet to BEBs is costly and time-consuming. Thus, the intermediate solution is a combination of diesel, hybrid, and BEBs. Therefore, a planning framework is required that simultaneously tackles three contiguous aspects of transit electrification and their interconnections, namely charging infrastructure, fleet configuration, and scheduling. Accordingly, this study considers a mixed fleet of diesel and BEBs. It aims to concurrently find (i) the optimal location and capacity of charging infrastructure, considering micro-grid specifications, the impact of distributed energy resources, and time-of-use electricity rates and (ii) optimum operation and refueling strategies. Another objective of this study is to capture the impacts of adverse weather conditions on transit electrification. A mixed-integer problem is proposed and solved using a metaheuristic algorithm based on simulated annealing to minimize system costs, including infrastructure, fleet, and operation costs. A subnetwork of transit in Worcester, Massachusetts, is selected as a case study, including three routes, five candidate charging locations, and three bus types. Findings suggest that BEBs can operate and serve the passenger demand with sufficient charging infrastructure. Sensitivity analyses show that even though high-power chargers are more expensive per piece, they reduce the overall cost as fewer chargers are required. The cost rises for chargers with power of 350 kW or more. It is worth noting that the benefits of BEBs are more significant in smaller buses and are heavily affected by adverse weather conditions.

Factors affecting variability in fossil-fueled transit bus emission rates

Abstract Globally, there are over 10 million transit buses. Exhaust emissions from transit buses include carbon dioxide (CO2), carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particulate matter (PM). Key factors affecting bus emission rates have been evaluated separately or in limited combinations in prior studies, including bus size, fuel and powertrain, passenger load, driving cycle, and model year. However, bus emission rates are jointly affected by all of these factors. To systematically evaluate these factors, a transit bus emissions model (TBEM) was developed. TBEM is calibrated based on generic compressed natural gas (CNG) and diesel bus types represented in the U.S. Environmental Protection Agency MOtor Vehicle Emission Simulator and empirical cycle average emission rates from the Integrated Bus Information System. The importance of the factors varies depending on the pollutant. For emission rates per vehicle-kilometer, model year is an important factor for NOx and PM, fuel and powertrain is an important factor for CO and THC, and driving cycle and bus size are important factors for CO2. For emission rates per passenger-kilometer, passenger load is generally an important factor for each pollutant. For a given fuel and powertrain and pollutant, smaller buses have lower emission rates per vehicle-kilometer than larger buses. However, a full large bus has lower emission rates per passenger-kilometer than a full small bus. There are tradeoffs among bus types regarding emission rates, especially for THC and PM. The comparison of bus emission rates is dependent on interactions between these key factors. For example, the effect of bus size and passenger load on emission rates is larger for lower speed driving cycles. For 2010 and newer model year buses and for moderate to high speed driving cycles, diesel buses have the lowest NOx emission rates whereas for low speed cycles, CNG buses have the lowest NOx emission rates. However, for 2007 to 2009 model year buses, CNG buses have the lowest NOx emission rates regardless of driving cycle. The study will be useful in helping transit planners and policy makers to develop strategies to reduce transit bus fleet emissions and in providing accurate emission factors for use in bus life cycle inventories and emission inventories.

Modernization and/or Sustainable Transportation System in Dakar: Identification of Problems and Mode Requirements

Transport is in crisis in the Senegalese capital city. The urban structure in Dakar is characterized by a main urban pole, monopolizing industrial activities; harbor and port activities were also moved from other cities to Dakar. Around 80% of the activities are concentrated is the capital city. However, the public transport sector is not very organized and reliable; it is also informal except the bus system. Since 2000, Conventional bus services are operated by Dakar Dem Dikk (DDD), but the situation deteriorated in 2003 and 2004 so that very few vehicles were operate daily. There are around 2,500 to 4,000 smaller buses, known as cars rapides, with between 25 and 40 seats. Only 10% of the population in Dakar own a car and 76% of the population uses mass transit as Ndiaga Ndiaye and car rapid. They are all facing to worsening traffic congestion. This paper aims to analyze the urban transportation situation in Dakar, classify the problems encountered by the urban structure and define the transportation needs of Dakar urban system. Thus Integrated Rapid Transit (IRT) was suggested as the alternative solution to the transportation system in Senegal.

Optimizing bus-size and headway in transit networks

Optimization models for calculating the best size for passenger carrying vehicles in urban areas were popular during the 1980s. These studies were abandoned in the ‘90s concluding that it was more efficient to use smaller buses at higher frequencies. This article returns to this controversial question, starting from the point of view that any calculation of bus size can only be made after considering the demand for each of the routes on the system. Therefore, an optimization model for sizing the buses and setting frequencies on each route in the system is proposed in accordance with the premises detailed below. The proposed model is a bi-level optimization model with constraints on bus capacity. The model allows buses of different sizes to be assigned to public transport routes optimizing the headways on each route in accordance with observed levels of demand. At the upper level the model considers the optimization of the system’s social and operating costs, these are understood to be the sum of the user’s and operator’s costs. At the lower level there is an assignment model for public transport with constraints on vehicle capacity which balances the flows for bus sizes and headways at each iteration. By graphically representing the results of the model applied to a real case, a series of useful conclusions are reached for the management and planning of a fleet of public transport vehicles.

Local public transport on the basis of social economic criteria

Applying the welfare economic approach it is demonstrated what the effects of certain supply changes in the local public transport will be and the potential of innovative demand management measures are examined. Straighter bus routes would reduce the average travel time from door to door. The travel time on the buses decreases and the frequency increases, which reduces waiting times at bus stops. Using smaller buses and more of them would also increase the net benefit, but increase the need for subsidisation. The peak within the peak in the morning is hard to handle by price policy alone. Introducing a small variation of the start of the school-day for high-school pupils would make investment- and operation cost savings possible, and the inconvenience costs for the pupils could be limited. It is only during peak hours in the main direction of peak travel and in the critical section of the line that optimal price becomes high relative to the present level. Zero fares in off-peak will be social profitable, but an increase in subsidy is needed. An introduction of these policy changes would give rise to a net social benefit of 30 million SEK per year in Linköping.

A low-power high-throughput link splitting router for NoCs

In this paper, we propose a technique for lowering the latency of the communication in a NoC (network on chip). The technique, which can support two qualities of service (QoS), i.e., the guaranteed throughput (GT) and best effort (BE), is based on splitting a wider link into narrower links to increase throughput and decrease latency in the NoC. In addition, to ease the synchronization and reduce the crosstalk, we use the 1-of-4 encoding for the smaller buses. The use of the encoding in the proposed NoC architecture considerably lowers the latency for both BE and GT packets. In addition, the bandwidth is increased while the power consumption of the links is reduced.

Theoretical analysis of bus-invert coding

The closed-form formulas derived from the Markov chains depicting the bus-invert coding processes for even and odd bus widths are employed to compute switching activity and weight per bus transfer, to explain the diminishing returns with increasing bus width and to show the nonviability of partitioning a bus into smaller buses of odd number bits, etc. Probing into the codewords generated by the coding process, we obtain the same closed-form formulas as that obtained by the Markov-based approach. Our contributions form a superset over the previously published theoretical results and provide comprehensive background information for exploiting the bus-invert method for low-power applications.

A multicomputer architecture with a segmented shared bus

Single-bus multicomputer systems can support only a relatively small number of processing elements as the bus quickly becomes the communication bottleneck. Multiple-bus systems provide increased communication bandwidth and can support larger numbers of processing elements. The segmented-bus architecture is an important extension of these systems and offers even more communication bandwidth. The segmented bus contains switches between every pair of adjacent processing elements and can be dynamically segmented into smaller buses that can simultaneously connect more than one pair of processing elements. This paper examines the design of the processing elements, the mathematical modeling and the simulation of the architecture. It relates the performance of the system to the number of processing elements and the bus segmentation and allocation procedure, given a specific load.