scholarly journals Emerging Technologies and Methods in Shared Mobility Systems Layout Optimization of Campus Bike-Sharing Parking Spots

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Tangyi Guo ◽  
Jie Yang ◽  
Liu He ◽  
Kun Tang
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Rapid Development ◽  
Construction Cost ◽  
Study Analysis ◽  
Parking Spot ◽  
Average Travel Time ◽  
Shared Mobility ◽  
Bike Sharing ◽  
Scientific Decision

The rapid development of bike sharing has posed some challenges to the traffic management on campus. The bike sharing on campus has problems such as messy parking, and some buildings in the peak hours have no bikes to borrow. Thus, alternative parking spots are proposed based on the layout principle of parking spots for bicycles. An optimization model of the layout of campus bike-sharing parking spots with travel time and construction cost as the optimization goal is established, and the branch and bound algorithm is used to solve the model. Finally, the study analysis is carried out by optimizing the layout of the bike-sharing parking spot of Nanjing University of Science and Technology. The results show that, after optimizing the layout of parking spots, the average travel time of users is reduced by 6.0%, and the total construction cost is reduced by 27.3%. While being convenient for campus bike-sharing users, it also provides scientific decision-making support for the campus traffic management.

scholarly journals Travel Time Reliability for Urban Networks: Modelling and Empirics

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Fangfang Zheng ◽  
Xiaobo Liu ◽  
Henk van Zuylen ◽  
Jie Li ◽  
Chao Lu
Keyword(s):  
Standard Deviation ◽  
Travel Time ◽  
Network Traffic ◽  
Traffic Management ◽  
Weighted Average ◽  
Network Density ◽  
Travel Time Reliability ◽  
Time Rate ◽  
Traffic Characteristics ◽  
Average Travel Time

The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data collected by Automated Number Plate Recognition (ANPR) cameras. We further investigate the network-level travel time reliability by connecting the network reliability measures such as the weighted standard deviation of travel time rate and the weighted skewness of travel time rate distributions with network traffic characteristics (e.g., the network density). The weighting is done with respect to the number of signalized intersections on a trip. A clear linear relation between the weighted average travel time rate and the weighted standard deviation of travel time rate can be observed for different time periods with time-varying demand. Furthermore, both the weighted average travel time rate and the weighted standard deviation of travel time rate increase monotonically with network density. The empirical findings of the relation between network travel time reliability and network traffic characteristics can be possibly applied to assess traffic management and control measures to improve network travel time reliability.

DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

2021 ◽  
Author(s):  
Matheus Bernardino de Araújo ◽  
Matheus Monteiro Silveira ◽  
Rafael Lopes Gomes
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Network Flows ◽  
Urban Traffic ◽  
Traffic Information ◽  
Transport Systems ◽  
Packet Delivery ◽  
Vehicle Accidents ◽  
Average Travel Time ◽  
Definition Of

Intelligent Transport Systems (ITS) arose as a modern solution to traffic jams and vehicle accidents in the urban environment. A key part of the ITS is Traffic Management (TM), which concerns the planning and route definition of the vehicle. Existing TM solution focuses specifically on urban traffic information, ignoring the issues related to the network infrastructure and the applications at the top of it. Within this context, this paper presents a vehicle routing and re-routing strategy, called DINO, that considers both travel time of vehicles on the roads and the active network flows in the network, aiming to dynamically bring a suitable balance between travel time and packet delivery through a heuristic. The experiments performed suggest that DINO improves the packet delivery of the applications while reduces the average travel time of vehicles.

scholarly journals Sustainable urban transportation development in China: A behavioral perspective

2021 ◽  
Author(s):  
Shuai Ling ◽  
Shoufeng Ma ◽  
Ning Jia
Keyword(s):  
Traffic Management ◽  
Rapid Development ◽  
Demand Management ◽  
Urban Transportation ◽  
Transportation Systems ◽  
Transportation Demand ◽  
Special Cases ◽  
Traffic Systems ◽  
Four Levels ◽  
Transportation Development

AbstractThe rapid development of economics requires highly efficient and environment-friendly urban transportation systems. Such requirement presents challenges in sustainable urban transportation. The analysis and understanding of transportation-related behaviors provide one approach to dealing with complicated transportation activities. In this study, the management of traffic systems is divided into four levels with a structural and systematic perspective. Then, several special cases from the perspective of behavior, including purchasing behaviors toward new energy vehicles, choice behaviors toward green travel, and behavioral reactions toward transportation demand management policies, are investigated. Several management suggestions are proposed for transportation authorities to improve sustainable traffic management.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

ORGANIZATION OF ROAD TRAFFIC TAKING INTO ACCOUNT ELECTRIC ROUTE PASSENGER TRANSPORT

2021 ◽  
Vol 2 (65) ◽  
pp. 66-77
Author(s):  
Denis V. Kapsky ◽  
◽  
Sergey S. Semchenkov ◽  
Evgeny N. Kot ◽  
◽  
...  
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Rapid Development ◽  
Living Environment ◽  
Transport Sector ◽  
Passenger Transport ◽  
Wide Range ◽  
Practical Development ◽  
The Republic ◽  
Conducting Research

The rapid development of the transport sector leads not only to positive changes in the life of cities and towns, to an increase in convenience and comfort for residents, but also worsens the ecology and their living environment. The “profitable-safe” dilemma can be solved by the approach of environmentally oriented selection of the type of route passenger transport and decisionmaking in favor of electric route passenger transport. The article discusses the types of such transport on the example of the experience of their use in the Republic of Belarus. The classification and systematization developed by the authors are presented with subsequent recommendations for its application. On the basis of the results of the authors’ research, the issues of interaction of rail and non-rail route vehicles with an electric drive with the organization of road traffic are separately considered. The presented materials can be useful to a wide range of readers, as well as to specialists conducting research and practical development in the field of electrically powered route vehicles and traffic management.

scholarly journals The Effect of Route-choice Strategy on Transit Travel Time Estimates

2019 ◽  
Author(s):  
Nate Wessel ◽  
Steven Farber
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Imperfect Information ◽  
Optimal Path ◽  
Shortest Paths ◽  
Route Choice ◽  
Travel Times ◽  
Selection Strategies ◽  
Time Estimates ◽  
Average Travel Time

Estimates of travel time by public transit often rely on the calculation of a shortest-path between two points for a given departure time. Such shortest-paths are time-dependent and not always stable from one moment to the next. Given that actual transit passengers necessarily have imperfect information about the system, their route selection strategies are heuristic and cannot be expected to achieve optimal travel times for all possible departures. Thus an algorithm that returns optimal travel times at all moments will tend to underestimate real travel times all else being equal. While several researchers have noted this issue none have yet measured the extent of the problem. This study observes and measures this effect by contrasting two alternative heuristic routing strategies to a standard shortest-path calculation. The Toronto Transit Commission is used as a case study and we model actual transit operations for the agency over the course of a normal week with archived AVL data transformed into a retrospective GTFS dataset. Travel times are estimated using two alternative route-choice assumptions: 1) habitual selection of the itinerary with the best average travel time and 2) dynamic choice of the next-departing route in a predefined choice set. It is shown that most trips present passengers with a complex choice among competing itineraries and that the choice of itinerary at any given moment of departure may entail substantial travel time risk relative to the optimal outcome. In the context of accessibility modelling, where travel times are typically considered as a distribution, the optimal path method is observed in aggregate to underestimate travel time by about 3-4 minutes at the median and 6-7 minutes at the \nth{90} percentile for a typical trip.

scholarly journals Estimates of Economic Cost of Congestion Travel Time Delay Between Onne-Seaport and Eleme-Junction Traffic Corridor

2020 ◽  
Vol 11 (2) ◽  
pp. 33-43
Author(s):  
Theophilus C. Nwokedi ◽  
Lazarus I. Okoroji ◽  
Ifiok Okonko ◽  
Obed C. Ndikom
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Oil And Gas ◽  
Economic Cost ◽  
Oil And Gas Industry ◽  
Research Approach ◽  
Traffic Corridor ◽  
Output Losses

AbstractTravelers along the Onne-seaport to Eleme-junction road corridor in the hub of the oil and gas industry in Port-Harcourt, Nigeria, have continued to experience very serious traffic congestion travel time delays, culminating into loss of man-hours and declining productivity. This study estimated the economic cost of traffic congestion travel time delay along the corridor, with a view to providing economic justification for developing traffic management policies and road infrastructure, to remedy it. A mixed research approach was adopted in which data was sourced through field survey and from secondary sources. The gross output model was used to estimate the output losses occasioned by productive time losses related to traffic congestion. The study established that the average daily traffic congestion travel time delay along the traffic corridor by travelers in trucks, car, bus and taxi modes are 104.17 minutes, 46.60 minutes, 58.5 minutes and 56.4 minutes respectively. The estimated daily aggregate economic cost of output losses associated with traffic congestion time delay on the corridor is 46049809.8 naira (210923.5USD) for all modes. This justifies any investment in traffic congestion remedial strategies along the route.

scholarly journals Delay Measurement of Manually Controlled Intersection Using GPS

2014 ◽  
Vol 8 (1) ◽  
pp. 130-135
Author(s):  
S. Nithya ◽  
D. Senthurkumar ◽  
K. .Gunasekaran
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Weather Conditions ◽  
Heterogeneous Traffic ◽  
Gps Data ◽  
Peak Period ◽  
Control Delay ◽  
Average Travel Time ◽  
Vehicle Acceleration ◽  
Acceleration And Deceleration

The travel time studies are one of the most important measures used for evaluating the performance of road networks. The Global Positioning System (GPS) is a space-based system that provides position and time information in all weather conditions. GPS data could be used to obtain the values of traffic control delay, vehicle queue, average travel time and vehicle acceleration and deceleration at intersections.The task of estimation of delay becomes complex if it is performed for intersections carrying heterogeneous traffic and that to for over saturated conditions. Most of the urban signalized intersections are manually controlled during peak hours. GPS device fitted in a vehicle was run repeatedly during morning peak period and the period during which vehicles were allowed to cross the intersection was recorded with video graphic camera. The attempt to identify the control delay with the GPS data from the test vehicle while crossing manually operated major intersection is presented in this paper.

scholarly journals THE ACCESSIBILITY OF EUROPEAN REGIONS AND AIRPORT NETWORK

2015 ◽  
Vol 6 (2) ◽  
pp. 87-109 ◽  
Author(s):  
Renato Redondi ◽  
Paolo Malighetti ◽  
Stefano Paleari
Keyword(s):  
Travel Time ◽  
High Speed ◽  
Waiting Times ◽  
Weighted Average ◽  
Air Transport ◽  
High Speed Train ◽  
Territorial Unit ◽  
Average Travel Time ◽  
Direct Flight ◽  
Total Travel Time

The objective of this work is to evaluate the accessibility of European municipalities by air transport. We focus on travels that typically require the use of air transport by computing the quickest paths between any pair of municipalities separated by more than 500 km. The total travel time includes three components: i) travel by car or High Speed Train to reach the origin airport, ii) travel by air from the origin airport to the destination airport, including waiting times when no direct flight is available and iii) travel by car or High Speed Train from the destination airport to the municipality of destination. For each territorial unit, we calculate the population-weighted average travel time to reach any other municipality in Europe.

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