scholarly journals Enabling In-Depot Automated Routing and Recharging Scheduling for Automated Electric Bus Transit Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lei Wang ◽  
Wanjing Ma ◽  
Ling Wang ◽  
Yongli Ren ◽  
Chunhui Yu
Keyword(s):  
Autonomous Vehicles ◽  
Job Shop ◽  
Optimal Solution ◽  
Transit System ◽  
Transit Systems ◽  
Bus Transit ◽  
Electric Bus ◽  
Minimum Number ◽  
First Come First Serve ◽  
High Level

The bus transit system is promising to enable electric and autonomous vehicles for massive urban mobility, which relies on high-level automation and efficient resource management. Besides the on-road automation, the in-depot automated scheduling for battery recharging has not been adequately studied yet. This paper presents an integrated in-depot routing and recharging scheduling (IDRRS) problem, which is modeled as a constraint programming (CP) problem with Boolean satisfiability conditions (SAT). The model is converted to a flexible job-shop problem (FJSP) and is feasible to be solved by a CP-SAT solver for the optimal solution or feasible solutions with acceptable performance. This paper also presents a case study in Shanghai and compares the results from the FJSP model and the first-come first-serve (FCFS) method. The result demonstrates the allocation of routes and chargers under multiple scenarios with different numbers of chargers. The results show that the FJSP model shortens the delay and increases the time conservation for future rounds of operation than FCFS, while FCFS presents the simplicity of programming and better computational efficiency. The multiple random input test suggests that the proposed approach can decide the minimum number of chargers for stochastic charging requests. The proposed method can conserve the investment by increasing the utilization of automated recharging devices, improving vehicles’ in-depot efficiency.

Assessing Transit Changes in Columbus, Ohio, and Sacramento, California

2005 ◽  
Vol 1930 (1) ◽  
pp. 62-67 ◽  
Author(s):  
John Schumann
Keyword(s):  
Federal Funding ◽  
Light Rail ◽  
Rail Transit ◽  
Transit System ◽  
Transit Systems ◽  
Bus Transit ◽  
The Past ◽  
Voter Approval ◽  
Capital Funding ◽  
Bus Service

This paper compares the changes experienced by transit systems in two state capitals of similar size: Columbus, Ohio, and Sacramento, California. Over the past two decades, Sacramento added a light rail transit (LRT) starter line and experienced significant ridership growth on its multimodal rail and bus system, while Columbus remained all-bus and experienced a decline in patronage. Reasons underlying the divergent performances of these two systems are analyzed and discussed. It is concluded that, in Sacramento, willing political leadership took good advantage of a one-time opportunity for federal funding to build an LRT starter line; that adding LRT made transit more visible and effective and encouraged voter approval of additional local operating and capital funding; and that all of this resulted in a synergy that attracted more riders to the total LRT and bus transit system and led to extension of the rail system to a third corridor in 2003. Although planning for LRT was begun in Columbus during these same years, a serious interruption in the flow of local funds hampered transit development, required cuts in bus service, and prevented development of that region's planned LRT line. Columbus currently has an LRT project in preliminary engineering, and recent reports suggest a consensus to proceed may be emerging.

Using Deficit Function to Determine the Minimum Fleet Size of an Autonomous Modular Public Transit System

2020 ◽  
Vol 2674 (11) ◽  
pp. 532-541 ◽  
Author(s):  
Tao Liu ◽  
Avishai (Avi) Ceder ◽  
Andreas Rau
Keyword(s):  
Autonomous Vehicles ◽  
Large Scale ◽  
Public Transit ◽  
Programming Model ◽  
Real Life ◽  
Single Line ◽  
Continuum Approximation ◽  
Transit System ◽  
Fleet Size ◽  
Minimum Number

Emerging technologies, such as connected and autonomous vehicles, electric vehicles, and information and communication, are surrounding us at an ever-increasing pace, which, together with the concept of shared mobility, have great potential to transform existing public transit (PT) systems into far more user-oriented, system-optimal, smart, and sustainable new PT systems with increased service connectivity, synchronization, and better, more satisfactory user experiences. This work analyses such a new PT system comprised of autonomous modular PT (AMPT) vehicles. In this analysis, one of the most challenging tasks is to accurately estimate the minimum number of vehicle modules, that is, its minimum fleet size (MFS), required to perform a set of scheduled services. The solution of the MFS problem of a single-line AMPT system is based on a graphical method, adapted from the deficit function (DF) theory. The traditional DF model has been extended to accommodate the definitions of an AMPT system. Some numerical examples are provided to illustrate the mathematical formulations. The limitations of traditional continuum approximation models and the equivalence between the extended DF model and an integer programming model are also provided. The extended DF model was applied, as a case study, to a single line of an AMPT system, the dynamic autonomous road transit (DART) system in Singapore. The results show that the extended DF model is effective in solving the MFS problem and has the potential to be applied to solving real-life MFS problems of large-scale, multi-line and multi-terminal AMPT systems.

scholarly journals Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm

2020 ◽  
Vol 12 (21) ◽  
pp. 8971
Author(s):  
Gang Chen ◽  
Dawei Hu ◽  
Steven Chien ◽  
Lei Guo ◽  
Mingzheng Liu
Keyword(s):  
Genetic Algorithm ◽  
Service Life ◽  
Ghg Emissions ◽  
Optimal Solution ◽  
Mathematic Model ◽  
Bus Transit ◽  
Route Network ◽  
Electric Bus ◽  
Battery Capacity ◽  
Bus Network

Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion and overcome the drawback (short service range) with opportunity charging. This paper proposes a mathematic model which optimizes the locations for DWPT devices deployed at stops and size of battery capacity for battery electric buses (BEB) in a multi-route network, which considers the battery’s service life, depth of discharge and weight. A tangible solution algorithm based on a genetic algorithm (GA) is developed to find the optimal solution. A case study based on the bus network from Xi’an China is conducted to investigate the relationship among optimized costs, greenhouse gas (GHG) emissions, battery service life, size of the battery capacity and the number of DWPT devices. The results demonstrated that a bus network powered by DWPT shows better performance in both costs (a 43.3% reduction) and emissions (a 14.4% reduction) compared to that with stationary charging at bus terminals.

scholarly journals Evaluating Route and Frequency Design of Bus Lines Based on Data Envelopment Analysis with Network Epsilon-Based Measures

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yiling Deng ◽  
Yadan Yan
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Monthly Basis ◽  
Transit System ◽  
Transit Systems ◽  
Bus Transit ◽  
Route Network ◽  
Study Results ◽  
Dea Models ◽  
Improvement Measures

Increasing the efficiency of bus transit remains to be a challenge of urban transportation. Since the optimization of bus routes and their frequencies is significant for transit efficiency, this study aims to develop two data envelopment analysis (DEA) models using network epsilon-based measures (NEBMs). The first NEBM model adopts twelve indicators to evaluate the rationality of the route network design; the second NEBM model uses nine indicators to evaluate the efficiency of the frequency setting. Both NEBM models can simultaneously consider radial and nonradial inputs and outputs and dig into details of the “input/output transformation box.” Finally, the bus transit system of Nanjing in China is used as a case study. Results show that the overall efficiency of network route design is higher than that of frequency setting. According to comparisons between descriptive statistics of the top and bottom performers, inefficiency causes of bottom performers are identified and corresponding improvement measures are suggested. The proposed models are helpful for the development of bus transit systems and can be applied on a yearly/monthly basis.

A novel fast-charging stations locational planning model for electric bus transit system

Energy ◽  
2021 ◽  
Vol 224 ◽  
pp. 120106
Author(s):  
Xiaomei Wu ◽  
Qijin Feng ◽  
Chenchen Bai ◽  
Chun Sing Lai ◽  
Youwei Jia ◽  
...  
Keyword(s):  
Planning Model ◽  
Transit System ◽  
Bus Transit ◽  
Electric Bus ◽  
Fast Charging ◽  
Charging Stations

Planning and Design Model for Transit Route Networks with Coordinated Operations

1998 ◽  
Vol 1623 (1) ◽  
pp. 16-23 ◽  
Author(s):  
Mao-Chang Shih ◽  
Hani S. Mahmassani ◽  
M. Hadi Baaj
Keyword(s):  
Selection Procedure ◽  
Transit System ◽  
Transit Systems ◽  
Transit Networks ◽  
Bus Transit ◽  
Planning And Design ◽  
Assignment Model ◽  
Route Coordination ◽  
Vehicle Size

A heuristic model is presented for the design of bus transit networks with coordinated operations. Different from past solution methodologies focusing on conventional uncoordinated transit systems, this model addresses the design of transit networks with coordinated operations, using a transit center concept and incorporating a trip assignment model explicitly developed for coordinated (timed-transfer) systems. In addition, this model determines the appropriate vehicle size for each bus route and incorporates demand-responsive capabilities to meet demand that cannot be served effectely by fixed-route, fixed-schedule services. This model is composed of four major procedures: ( a) a route generation procedure (RGP), which constructs the transit network around the transit center concept; ( b) a network analysis procedure, which incorporates a trip assignment model (for both coordinated and uncoordinated operations) and a frequency-setting and vehicle-sizing procedure; ( c) a transit center selection procedure, which identifies the suitable transit centers for route coordination; and ( d) a network improvement procedure, which improves on the set of routes generated by the RGP. The model is demonstrated via a case-study application to data generated from the existing transit system in Austin, Texas.

scholarly journals Joint Optimization of Regular Charging Electric Bus Transit Network Schedule and Stationary Charger Deployment considering Partial Charging Policy and Time-of-Use Electricity Prices

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xinghua Li ◽  
Tianzuo Wang ◽  
Lingjie Li ◽  
Feiyu Feng ◽  
Wei Wang ◽  
...  
Keyword(s):  
Traffic Noise ◽  
Joint Optimization ◽  
Maintenance Cost ◽  
Adaptive Genetic Algorithm ◽  
Electricity Prices ◽  
Transit System ◽  
Transit Network ◽  
Bus Transit ◽  
Electric Bus ◽  
Network Schedule

Electric buses (EBs) have been implemented worldwide and exhibited great potential for air pollution reduction and traffic noise control. In regular charging scenarios, the deployment of charging facilities and the operational scheduling of the transit system is crucial to bus transit system management. In this paper, we proposed a joint optimization model of regular charging electric bus transit network schedule and stationary charger deployment considering partial charging policy and time-of-use electricity prices. The objective of the model is to minimize the total investment cost of the transit system including the capital and maintenance cost of EBs and chargers, the power consumption cost, and time-related in-service cost. A solving procedure based on the improved adaptive genetic algorithm (AGA) is further designed and a transit network at inner Anting Town, Shanghai, with 8 individual bus routes and 867 daily service trips is adopted for the model validation. The validation results illustrated that the methodology considering the partial charging policy can arrange the charging schedule adaptive to the time-of-use electricity prices. Compared with the benchmark of single line separate scheduling, the proposed model can yield 3 million RMB investment saving by highly utilizing EBs and battery chargers.

scholarly journals Economic Assessment of Autonomous Electric Microtransit Vehicles

2019 ◽  
Vol 11 (3) ◽  
pp. 648 ◽  
Author(s):  
Aybike Ongel ◽  
Erik Loewer ◽  
Felix Roemer ◽  
Ganesh Sethuraman ◽  
Fengqi Chang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Autonomous Vehicles ◽  
Economic Assessment ◽  
Transit System ◽  
Bus Transit ◽  
Cost Impact ◽  
Cost Competitiveness ◽  
Acquisition Costs ◽  
The Cost ◽  
Autonomous Electric Vehicles

There is rapidly growing interest in autonomous electric vehicles due to their potential in improving safety, accessibility, and environmental outcomes. However, their market penetration rate is dependent on costs. Use of autonomous electric vehicles for shared-use mobility may improve their cost competitiveness. So far, most of the research has focused on the cost impact of autonomy on taxis and ridesourcing services. Singapore is planning for island-wide deployment of autonomous vehicles for both scheduled and on-demand services as part of their transit system in the year 2030. TUMCREATE developed an autonomous electric vehicle concept, a microtransit vehicle with 30-passenger capacity, which can complement the existing bus transit system. This study aims to determine the cost of autonomous electric microtransit vehicles and compare them to those of buses. A total cost of ownership (TCO) approach was used to compare the lifecycle costs. It was shown that although the acquisition costs of autonomous electric vehicles are higher than those of their conventional counterparts, they can reduce the TCO per passenger-km up to 75% and 60% compared to their conventional counterparts and buses, respectively.

scholarly journals An Open-Source Scale Model Platform for Teaching Autonomous Vehicle Technologies

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3850
Author(s):  
Bastien Vincke ◽  
Sergio Rodriguez Rodriguez Florez ◽  
Pascal Aubert
Keyword(s):  
Open Source ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Constrained Systems ◽  
Scale Model ◽  
Technical Students ◽  
Vehicle Technologies ◽  
Model Platform ◽  
High Level ◽  
Time And Energy

Emerging technologies in the context of Autonomous Vehicles (AV) have drastically evolved the industry’s qualification requirements. AVs incorporate complex perception and control systems. Teaching the associated skills that are necessary for the analysis of such systems becomes a very difficult process and existing solutions do not facilitate learning. In this study, our efforts are devoted to proposingan open-source scale model vehicle platform that is designed for teaching the fundamental concepts of autonomous vehicles technologies that are adapted to undergraduate and technical students. The proposed platform is as realistic as possible in order to present and address all of the fundamental concepts that are associated with AV. It includes all on-board components of a stand-alone system, including low and high level functions. Such functionalities are detailed and a proof of concept prototype is presented. A set of experiments is carried out, and the results obtained using this prototype validate the usability of the model for the analysis of time- and energy-constrained systems, as well as distributed embedded perception systems.

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

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