Advantages of retrofitting old electric buses and minibuses

Abstract Old electric buses and minibuses equipped with obsolete energy storage systems are today circulating on the roads all over the world. A minibus prototype equipped with Ion-Lithium batteries developed in the ENEA Casaccia Research Centre demonstrated that an old minibus can be retrofitted by replacing the old lead acid batteries pack with a new pack assembled with LiFePO4 electrochemistry. The new batteries provide sufficient power to the electric motor, an amount of energy to cover nearly 30 kilometers with a full charge, with a new battery load of 50% of the previous battery pack. The new technology allows fast charging, thus solving the problem linked due to the long periods requested to charge of the conventional batteries. For example during public transport service, the minibus can be charged with only twenty minutes, allowing such operation at the terminus while waiting for the passengers. A "depleting" strategy can be applied in order to allow the minibus to be operating all the day with several charges at the stops. In this paper, the performance of a retrofitted minibus in comparison with the same minibus equipped with old generation batteries are reported. The economic benefits for the retrofitted minibus in comparison with a new minibus purchased from factories are also reported

United We Ride National Dialogue

The Coordinating Council on Access and Mobility (CCAM) asked the National Academy of Public Administration and Easter Seals Project ACTION to develop and host the first United We Ride (UWR) National Dialogue. The goal of the Dialogue was to help shape future policy direction and provide input to the next CCAM strategic plan. The National Academy also assembled a small work group with representatives of the Federal Interagency Coordinating Council on Access and Mobility, Easter Seals Project ACTION, and the National Resource Center on Human Service Transportation to help guide the process of design and implementation.The CCAM includes 11 federal departments, nine of which are responsible for providing transportation for people with disabilities, older adults, and people with limited incomes. CCAM officially launched United We Ride in 2004 to (1) provide more rides for target populations while using the same or fewer assets, (2) simplify access, and (3) increase customer satisfaction.Key FindingsThe process used to create coordinated transportation plans needs improvement. Significant federal policy barriers still exist to strategies that would facilitate access to transportation services. Mobility management strategies are underutilized in communities across the country, and missed opportunities to bridge gaps between transportation and other community services still need to be addressed

Ministry of Transport and Communications' research and Development Programme for Accessibility “ELSA”. Final report of the working group

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TransJakarta Service Evaluation in Controlling COVID-19 Transmission Using Twitter Sentiment Analysis

This study attempted to understand passenger perception of using public transport by utilizing Twitter data about the services of the TransJakarta Busway. Tweets were the main data source to capture users’ responses toward these services. Users’ perceptions were analyzed by sentiment analysis using a naïve Bayes algorithm. Furthermore, content analysis was used to inform improvements in service maintenance. The findings showed that the pandemic had a major impact on TransJakarta services, from a decrease in users, route closures, and fleet reductions to changes in user behavior. Most Tweets were negative regarding (1) poor bus frequency, leading to long queues and passenger overcrowding at bus stops and inside buses; (2) failure to maintain social distancing measures; (3) frequent violations of the 50% bus capacity reduction during peak hours, and showing a lack of consideration in measuring demand size during peak hours; (4) staff’s weak control of implementing the health protocol exacerbated poor services. This study suggests service improvement based on peak hour demand analysis to offset the implications of a 50% capacity restriction by providing proper bus frequencies and headway arrangements considerable enough to avoid crowding, followed by optimal monitoring of health protocol by staff. Tweet data may inform poor management in controlling the transmission of COVID-19 on public transportation. Hence, using Twitter data could replace conventional data collection methods like user interviews. Beneficial information from Tweet data can be captured at relatively low costs. Therefore, it may aid the evaluation of PPKM policy implementation to create more resilient public transportation during pandemics

TransJakarta Service Evaluation in Controlling COVID-19 Transmission Using Twitter Sentiment Analysis

This study attempted to understand passenger perception of using public transport by utilizing Twitter data about the services of the TransJakarta Busway. Tweets were the main data source to capture users’ responses toward these services. Users’ perceptions were analyzed by sentiment analysis using a naïve Bayes algorithm. Furthermore, content analysis was used to inform improvements in service maintenance. The findings showed that the pandemic had a major impact on TransJakarta services, from a decrease in users, route closures, and fleet reductions to changes in user behavior. Most Tweets were negative regarding (1) poor bus frequency, leading to long queues and passenger overcrowding at bus stops and inside buses; (2) failure to maintain social distancing measures; (3) frequent violations of the 50% bus capacity reduction during peak hours, and showing a lack of consideration in measuring demand size during peak hours; (4) staff’s weak control of implementing the health protocol exacerbated poor services. This study suggests service improvement based on peak hour demand analysis to offset the implications of a 50% capacity restriction by providing proper bus frequencies and headway arrangements considerable enough to avoid crowding, followed by optimal monitoring of health protocol by staff. Tweet data may inform poor management in controlling the transmission of COVID-19 on public transportation. Hence, using Twitter data could replace conventional data collection methods like user interviews. Beneficial information from Tweet data can be captured at relatively low costs. Therefore, it may aid the evaluation of PPKM policy implementation to create more resilient public transportation during pandemics

An analysis of the passenger vehicle interface of street transit systems with applications to design optimization

This research analyzes the Passenger Vehicle Interface of the street transit systems and presents applications for design optimization. The Passenger Vehicle Interface (PVI) is defined as the interaction between the passenger and vehicle elements of the street transit system. Human observer and photographic studies were conducted in 17 cities in the United States and Canada to measure the time for queues of passengers to board various transit vehicles. The data were analyzed by considering seven factors that affect the Passenger Vehicle Interface: Human Factor, Modal Factor, Operating Practices, Operating Policies, Mobility, Climate and Weather, and Other System Elements. Those effects which could be quantified were divided into the categories of direction of flow, method of fare collection, and door characteristics and use. A series of equations for each of these categories was developed to predict passenger service time when the number of alighting or boarding passengers is known or estimated. A range of values was developed for the parameters of each equation to reflect the effects of unquantifiable factors such as the type of passenger, physical characteristics of the passenger, passenger preferences, baggage carried, seating configuration, and congestion. The use of Passenger Influence Zones has indicated that passenger service time can range from approximately six to 14 percent of total trip time, depending upon vehicle type, door use, and method of fare collection. These zones have also been used to indicate how vehicle door use and characteristics can increase berth requirements by up. to 200 percent, and New different methods of fare collection can increase berth productivity in terms of passengers per hour by 87 percent. Distributions of passenger service times through the vehicle doors were identified based on the analysis of photographic studies and determined to be represented by an Erlang function. The analysis also inferred that the K value in the Erlang function is equal to the number of doors on the vehicle and that the minimum service time is approximately equal to half the average service time. The validity of the Erlang functions was determined by using the special purpose simulation programming language, GPSS, and the Erlang functions to estimate the time requirements for queues of passengers to board vehicles. The simulated times were compared with observed times, and the differences were found to be not statistically significant at the 95 percent level. A GPSS model was used to simulate the operations of a street tran sit loading area and to evaluate the effects of method of fare collection upon queue length and average waiting time under varying rates of passenger arrivals. This research provides sufficient information to perform sub- optimizations of several operations within the Passenger Vehicle Interface. Although not directed toward an optimization of street transit systems, it does provide the necessary information about the Passenger Vehicle Interface for others to perform this optimization after they have assembled comparable information on system elements and other interactions