scholarly journals Exact and Evolutionary Algorithms for Synchronization of Public Transportation Timetables Considering Extended Transfer Zones

2021 ◽  
Vol 11 (15) ◽  
pp. 7138
Author(s):  
Sergio Nesmachnow ◽  
Claudio Risso
Keyword(s):  
Public Transportation ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Waiting Times ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Synchronization Problem ◽  
Transfer Zones ◽  
Planning Methods ◽  
Problem Instances

This article addresses timetable synchronization in public transportation, an important problem in modern smart cities, in order to guarantee a proper quality of service to citizens. Two variants of the bus timetabling synchronization problem considering extended transfer zones are studied: optimizing offsets and optimizing offsets and headways for each line. An exact mixed integer programming and an evolutionary algorithm are developed to solve both problem variants. The algorithms are evaluated on 45 instances of a real case study, the intelligent transportation system of Montevideo, Uruguay. Experimental results reported significant improvements over the current timetable implemented by the city administration. The number of successful synchronizations improved up to 66.6% and 179.9% for the first and second problem variant, respectively. The average waiting times for transfers improved, especially in tight problem instances (up to 57.8% and 158.3% for the first and second problem variant, respectively). The proposed planning methods are useful to help decision makers to configure public transportation systems.

scholarly journals Integrating Frequency Setting, Timetabling, and Route Assignment to Synchronize Transit Lines

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Omar J. Ibarra-Rojas ◽  
Juan C. Muñoz ◽  
Ricardo Giesen ◽  
Paul Knapp
Keyword(s):  
Low Frequency ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Level Of Service ◽  
Synchronization Problem ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Commercial Solver ◽  
Important Activity

Synchronization of different transit lines is an important activity to increase the level of service in transportation systems. In particular, for passengers, transferring from one line to another, there may be low-frequency periods and transfer zones where walking is needed, or passengers are exposed to adverse weather conditions and uncomfortable infrastructure. In this study, we define the Bus Lines Synchronization Problem that determines the frequency for each line (regarding the even headway), the timetable (including holding times for buses at transfer stops), and passenger-route assignments to minimize the sum of passenger and operational costs. We propose a nonlinear mixed integer formulation with time-indexed variables which allow representing the route choice for passengers and different types of costs. We implement an iterative heuristic algorithm based on fixing variables and solving a simplified formulation with a commercial solver. We implement our proposed heuristic on the transit network in Santiago, Chile. Numerical results indicate that our approach is capable of reducing operating costs and increasing the level of service for large scenarios.

Intelligent transportation system for sustainable environment in smart cities

2021 ◽  
pp. 002072092098350
Author(s):  
Liang Zhao ◽  
Yuanhua Jia
Keyword(s):  
Environmental Sustainability ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Advanced Technology ◽  
Toxic Substances ◽  
Sustainable Environment

Advanced technology has ushered in the urge to enhance the travel experience. Besides the consistent desire to travel faster and more comfortably, the need to ensure transportation sustainability has remained constant. Smart cities employ top-grade technological applications to facilitate operations. Intelligent transportation systems involve the use of advanced transportation technologies. Through the integration of the Internet of Vehicles, cars in traffic can send and receive data between themselves and other vehicles and the environment. This data is processed to ensure efficient transportation by controlling traffic flows and preventing accidents. In this study, a literature review is conducted on how intelligent transportation systems contribute to environmental sustainability in smart cities. With technologies such as electricity-driven cars and autonomous vehicles, the systems minimize the emission of toxic substances to the environment while enhancing the interaction of the car with its surroundings to avoid accidents.

Creating Smart Cities with Intelligent Transportation Solutions

2011 ◽  
pp. 174-190 ◽  
Author(s):  
Leo Tan Wee Hin ◽  
R. Subramaniam
Keyword(s):  
Public Transportation ◽  
Intelligent Transportation Systems ◽  
Electronic Monitoring ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Signaling Systems ◽  
Public Transportation System ◽  
City State

Transportation is often the bane of urban societies. Traffic gridlocks and inadequate availability of a comprehensive and affordable public transportation system further accentuate the problem. This chapter focuses on the Singapore experience with intelligent transportation solutions to alleviate a range of problems, thus contributing to its positioning as a smart city. We focus on seven issues: public transportation using modern mass rapid transit trains; congestion control using electronic road pricing; electronic monitoring advisory systems to guide road users on adverse conditions or incidents on roads; computerized traffic signaling systems to streamline the throughput of vehicles in roadways; intelligent dispatch of taxis, which helps to minimize idle cruising time; parking guidance systems to alert motorists of the nearest car park, in the process decreasing the level of floating traffic on roads; and integrated ticketing systems to promote inter-modal transfer. A unique funding mechanism that has led to the evolution of a modern and efficient public transportation system is also elaborated. Being a city state and a living laboratory of intelligent transportation systems that have attracted international attention, it is suggested that there are some lessons to be drawn from the Singapore experience in managing transportation problems in smart cities.

Planning and Design of a Taxipooling Dispatching System

2005 ◽  
Vol 1903 (1) ◽  
pp. 86-95 ◽  
Author(s):  
Ker-Tsung Lee ◽  
Da-Jie Lin ◽  
Pei-Ju Wu
Keyword(s):  
Public Transportation ◽  
Traffic Congestion ◽  
Information Technologies ◽  
Intelligent Transportation System ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Transit Systems ◽  
Dispatching Algorithm ◽  
Public Transportation Systems ◽  
Parameter Values

Shifting people from driving to using public transportation has been important in alleviating urban traffic congestion. Intelligent transportation system technologies applied to public transportation can provide useful data to system operators and users and increase the use and productivity of high-occupancy vehicles. Integration of metropolitan rapid transit, feeder buses, and taxipooling can attract more public transportation users. Advanced taxipooling transfer assignment systems, a type of advanced public transportation systems program, aims to apply advanced technologies to taxi operations, including dynamic taxi fleet management, taxipooling strategies, and safety monitoring systems. Success in using taxis as a feeder service to mass transit systems requires advanced information technologies such as the Global Positioning System, geographic information systems, wireless communications, and, most important, an efficient taxi dispatching algorithm. The objectives and background of a dedicated taxipooling fleet in a metropolitan area are given. Also, a real-time, two-step taxipooling dispatching system is presented. A case study with parameter values obtained from Taiwan is explained; the simulation result is interpreted to illustrate the feasibility of the algorithm. Sensitivity analysis proves the robustness of the dispatching algorithm and shows the flexibility decision makers can have to serve certain purposes. Assumptions and constraints of the proposed dispatching system are evaluated, and the possibility of system expansion is discussed.

scholarly journals Multi-depot Electric Bus Scheduling Considering Operational Constraint and Partial Charging: A Case Study in Shenzhen, China

2021 ◽  
Vol 14 (1) ◽  
pp. 255
Author(s):  
Mengyan Jiang ◽  
Yi Zhang ◽  
Yi Zhang
Keyword(s):  
Public Transportation ◽  
Programming Model ◽  
Cost Effective ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Long Distance ◽  
Bus Scheduling ◽  
Battery Capacity

Electric buses (e-buses) demonstrate great potential in improving urban air quality thanks to zero tailpipe emissions and thus being increasingly introduced to the public transportation systems. In the transit operation planning, a common requirement is that long-distance non-service travel of the buses among bus terminals should be avoided in the schedule as it is not cost-effective. In addition, e-buses should begin and end a day of operation at their base depots. Based on the unique route configurations in Shenzhen, the above two requirements add further constraint to the form of feasible schedules and make the e-bus scheduling problem more difficult. We call these two requirements the vehicle relocation constraint. This paper addresses a multi-depot e-bus scheduling problem considering the vehicle relocation constraint and partial charging. A mixed integer programming model is formulated with the aim to minimize the operational cost. A Large Neighborhood Search (LNS) heuristic is devised with novel destroy-and-repair operators to tackle the vehicle relocation constraint. Numerical experiments are conducted based on multi-route operation cases in Shenzhen to verify the model and effectiveness of the LNS heuristic. A few insights are derived on the decision of battery capacity, charging rate and deployment of the charging infrastructure.

scholarly journals A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area

2021 ◽  
Vol 13 (19) ◽  
pp. 10885
Author(s):  
Mohsen Momenitabar ◽  
Jeremy Mattson
Keyword(s):  
Travel Time ◽  
Public Transportation ◽  
Transportation Systems ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Nsga Ii ◽  
Transit Network ◽  
Multi Objective ◽  
Total Travel Time ◽  
Initial Route

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.

California Consumer Perceptions of Potential Intelligent Transportation System Innovations

1996 ◽  
Vol 1537 (1) ◽  
pp. 30-37
Author(s):  
Constance D. Frayer ◽  
Louise Kroot
Keyword(s):  
Public Transportation ◽  
Public Perception ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
The State ◽  
Current State ◽  
The People ◽  
And Control

The purpose of the present research was to gain insight into the public perception of existing transportation options and to then explore consumers' needs and wants of those systems and the likely acceptance of possible intelligent transportation system (ITS) initiatives. The selected ITS concepts were based on nationally defined user needs for ITSs. Focus groups were selected as the means of gathering this primary research conducted throughout the state of California. Two perspectives were studied: statewide, to gain broad insights, and smart card specific, for focused insight. There was conspicuous agreement throughout the state as to the feelings about existing transportation systems. Californians are angry that they have not been consulted about their transportation system and that its current state does not reflect their wishes and does not meet their needs. Consumers are open to ITS concepts, including information systems, alternative fuel-powered vehicles, and other high-technology improvements. They support improvements in the automobile system and useful public transportation. Convenience, safety, freedom, flexibility, and control in planning and executing their travel are what they expect within an integrated transportation system. Much is written about the cost-effectiveness of buses. The reality is that the majority of the people will never use public transit in its current state. Electronic fare payment systems were seen as the ultimate in convenience for current users. Integrated fare systems were considered a tool for beginning the improvement of public transportation for existing users and for breaking down barriers of confusion and the lack of connectivity to attract new users.

scholarly journals Bus Arrival Prediction – to Ensure Users not to Miss the Bus

2015 ◽  
Vol 5 (2) ◽  
pp. 333 ◽  
Author(s):  
Lutfi Fanani ◽  
Achmad Basuki ◽  
Deron Liang
Keyword(s):  
Normal Distribution ◽  
Public Transportation ◽  
Arrival Time ◽  
Waiting Times ◽  
Transportation Systems ◽  
Accurate Information ◽  
Peak Time ◽  
Distribution Method ◽  
Arrival Times ◽  
Public Transportation Systems

Predicting arrival times of buses is a key challenge in the context of building intelligent public transportation systems. The bus arrival time is the primary information for providing passengers with an accurate information system that can reduce passenger waiting times. In this paper, we used the normal distribution method to the random of travel times data in a bus line number 243 in Taipei area. In developing the models, data were collected from Taipei Bus Company. A normal distribution method used for predicting the bus arrival time in bus stop to ensure users not to miss the bus, and compare the result with the existing application. The result of our experiment showed that our proposed method has a better prediction than existing application, with the probability user not to miss the bus in peak time is 93% and in normal time is 85%, greater than from the existing application with the 65% probability in peak time, and 70% in normal time.

scholarly journals The Application of Virtual Reality Technology on Intelligent Traffic Construction and Decision Support in Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gongxing Yan ◽  
Yanping Chen
Keyword(s):  
Big Data ◽  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
The Other ◽  
The City

The core of smart city is to build intelligent transportation system.. An intelligent transportation system can analyze the traffic data with time and space characteristics in the city and acquire rich and valuable knowledge, and it is of great significance to realize intelligent traffic scheduling and urban planning. This article specifically introduces the extensive application of urban transportation infrastructure data in the construction and development of smart cities. This article first explains the related concepts of big data and intelligent transportation systems and uses big data to illustrate the operation of intelligent transportation systems in the construction of smart cities. Based on the machine learning and deep learning method, this paper is aimed at the passenger flow and traffic flow in the smart city transportation system. This paper deeply excavates the time, space, and other hidden features. In this paper, the traffic volume of the random sections in the city is predicted by using the graph convolutional neural network (GCNN) model, and the data are compared with the other five models (VAR, FNN, GCGRU, STGCN, and DGCNN). The experimental results show that compared with the other 4 models, the GCNN model has an increase of 8% to 10% accuracy and 15% fault tolerance. In forecasting morning and evening peak traffic flow, the accuracy of the GCNN model is higher than that of other models, and its trend is basically consistent with the actual traffic volume, the predicted results can reflect the actual traffic flow data well. Aimed at the application of intelligent transportation in an intelligent city, this paper proposes a machine learning prediction model based on big data, and this is of great significance for studying the mechanical learning of such problems. Therefore, the research of this paper has a good implementation prospect and academic value.

scholarly journals A P-Hub Location Problem for Determining Park-and-Ride Facility Locations with the Weibit-Based Choice Model

2021 ◽  
Vol 13 (14) ◽  
pp. 7928
Author(s):  
Songyot Kitthamkesorn ◽  
Anthony Chen ◽  
Sathaporn Opasanon ◽  
Suwicha Jaita
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Transportation Network ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Facility Locations ◽  
Park And Ride ◽  
Public Transportation Systems

Park and ride (P&R) facilities provide intermodal transfer between private vehicles and public transportation systems to alleviate urban congestion. This study developed a mathematical programming formulation for determining P&R facility locations. A recently developed Weibit-based model was adopted to represent the traveler choice behavior with heterogeneity. The model’s independence of irrelevant alternatives (IIA) property was explored and used to linearize its nonlinear probability. Some numerical examples are provided to demonstrate a feature of the proposed mixed integer linear programing (MILP). The results indicate a significant impact of route-specific perception variance on the optimal P&R facility locations in a real-size transportation network.

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