scholarly journals Resilience-Based Optimization of Postdisaster Restoration Strategy for Road Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xinhua Mao ◽  
Jibiao Zhou ◽  
Changwei Yuan ◽  
Dan Liu
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Network Performance ◽  
Network Flows ◽  
Programming Model ◽  
Mixed Integer ◽  
Total System ◽  
Network Resilience ◽  
The Road ◽  
Restoration Strategies

This work proposes a framework for the optimization of postdisaster road network restoration strategies from a perspective of resilience. The network performance is evaluated by the total system travel time (TSTT). After the implementation of a postdisaster restoration schedule, the network flows in a certain period of days are on a disequilibrium state; thus, a link-based day-to-day traffic assignment model is employed to compute TSTT and simulate the traffic evolution. Two indicators are developed to assess the road network resilience, i.e., the resilience of performance loss and the resilience of recovery rapidity. The former is calculated based on TSTT, and the latter is computed according to the restoration makespan. Then, we formulate the restoration optimization problem as a resilience-based bi-objective mixed integer programming model aiming to maximize the network resilience. Due to the NP-hardness of the model, a genetic algorithm is developed to solve the model. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The effects of key parameters including the number of work crews, travelers’ sensitivity to travel time, availability of budget, and decision makers’ preference on the values of the two objectives are investigated as well.

scholarly journals A Multistage Multiobjective Model for Emergency Evacuation Considering ATIS

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Ming-Hua Zeng ◽  
Ke-Jun Long ◽  
Zi-Wen Ling ◽  
Xi-Yan Huang
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Network Performance ◽  
Programming Model ◽  
Choice Model ◽  
Compliance Rate ◽  
Emergency Evacuation ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Traffic Demand

The impacts of advanced traveler information system’s (ATIS’s) penetration and compliance rates on network performances during hybrid traffic emergency evacuation are investigated in a degraded road network. Before traffic incident a Path-Size Logit (PSL) route choice model is integrated with constraints on the level of service (LOS) of traffic to formulate a bilevel programming model. It aims at minimizing traffic demand in road network which may locally deteriorate the LOS. The lower level is a PSL-stochastic user equilibrium model for multiple classes of users. During the ongoing incident, a multiobjective multiuser-class stochastic optimization model is established with the objectives of maximizing evacuation reliability and minimizing expected network travel time. Furthermore, computations and analyses are completed for five designated scenarios including a method proposed in previous literature. The results show that the evacuation reliability and different kinds of total expected travel time costs regularly increase with emergency traffic’s ATIS compliance rate and decrease with general traffic’s ATIS penetration rate. The research will help improve transport network performance when considering ATIS’s effect on hybrid traffic.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

scholarly journals A Multimodal Passenger-and-Package Sharing Network for Urban Logistics

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yuxiong Ji ◽  
Yujing Zheng ◽  
Jizhou Zhao ◽  
Yu Shen ◽  
Yuchuan Du
Keyword(s):  
Network Performance ◽  
Programming Model ◽  
Mixed Integer ◽  
Covering Problem ◽  
Hub Location ◽  
Real World Data ◽  
Hub And Spoke ◽  
Taxi Drivers ◽  
Optimal Value ◽  
Peripheral Areas

This paper envisions a multimodal passenger-and-package sharing (PPS) network for urban logistics integrating metro, taxi, and truck. A hub-and-spoke structure is designed including hubs located at metro stations and service stores connected to the hubs. Packages are transported by metro on backbone links between the hubs and are carried by taxis or trucks between service stores and hubs, depending on the unit costs of these two modes and capacity constraint of the taxi. A mixed integer linear programming model for hub location problems—fusing the multiassignment p-hub median problem without capacity constraints and the capacitated multiassignment p-hub covering problem—is formulated to optimize the multimodal PPS network. The model is implemented based on the real-world data in Shanghai (China) under a series of scenarios to evaluate the network performance from two perspectives: the number of hubs and the proportion of taxi drivers who are willing to carry packages. The scenarios show that with increased number of hubs, the spatial distribution of hubs disperses from the city center to peripheral areas and more areas can be serviced by taxis. There is, however, a trade-off between the operation cost saved by taxis and the establishment cost of an extra hub. The analysis also presents that if the proportion of taxis willing to carry packages associates with the incentive payments to taxi drivers, an optimal value of incentives exists, by balancing the operation costs of taxis and trucks.

Estimation of Origin-Destination Matrix with Tolling Data

2011 ◽  
Vol 50-51 ◽  
pp. 239-244 ◽  
Author(s):  
Hua Wang ◽  
Xiao Ning Zhang
Keyword(s):  
Simulated Annealing ◽  
Travel Time ◽  
Road Network ◽  
Programming Model ◽  
Heuristic Method ◽  
Traffic Information ◽  
Traditional Model ◽  
Matrix Estimation ◽  
Od Estimation ◽  
The Cost

Prior matrix and surveyed link volumes were, in most cases, employed to estimate origin-destination matrix. With the development of BOT and of congestion pricing, charged links become an important component of road network, due to the fact that the tolling data: volumes and travel time on pricing entry-exit are traffic information, both cost-free and accurate. In this paper, we put forward a bi-level programming model, taking account of data on charging entry-exit to estimate OD matrix based upon the traditional model. Meanwhile, a heuristic method -the simulated annealing approach - is utilized to solve the OD estimation problem. Results of examples indicate that the accuracy of estimation will be improved while adding the tolling data, and that it is feasible to calculate OD matrix by combining the volumes and travel time on entry-exit with partial common link flows. In this light, this way can be applied to enhance accuracy, and also to reduce the cost spent on surveying the link flows in common OD matrix estimation.

scholarly journals OPTIMIZING THE CONTAINER TRUCK PATHS WITH UNCERTAIN TRAVEL TIME IN CONTAINER PORTS

Transport ◽  
2021 ◽  
Vol 36 (6) ◽  
pp. 444-462
Author(s):  
Jiaming Liu ◽  
Bin Yu ◽  
Wenxuan Shan ◽  
Baozhen Yao ◽  
Yao Sun
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Programming Model ◽  
Mixed Integer ◽  
A Algorithm ◽  
Shuffled Complex Evolution ◽  
Proposed Model ◽  
Container Ports ◽  
Yard Template

The yard template problem in container ports determines the assignment of space to store containers for the vessels, which could impact container truck paths. Actually, the travel time of container truck paths is uncertain. This paper considers the uncertainty from two perspectives: (1) the yard congestion in the context of yard truck interruptions, (2) the correlation among adjacent road sections (links). A mixed-integer programming model is proposed to minimize the travel time of container trucks. The reliable shortest path, which takes the correlation among links into account is firstly discussed. To settle the problem, a Shuffled Complex Evolution Approach (SCE-UA) algorithm is designed to work out the assignment of yard template, and the A* algorithm is presented to find the reliable shortest path according to the port operator’s attitude. In our case study, one yard in Dalian (China) container port is chosen to test the applicability of the model. The result shows the proposed model can save 9% of the travel time of container trucks, compared with the model without considering the correlation among adjacent links.

scholarly journals Method for Reliable Shortest Path Determination in Stochastic Networks using Parametrically Defined Stable Probability Distributions

2019 ◽  
Vol 18 (3) ◽  
pp. 558-582
Author(s):  
Anton Agafonov ◽  
Vladislav Myasnikov
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Road Network ◽  
Large Scale ◽  
Probability Distributions ◽  
Time Budget ◽  
Stochastic Networks ◽  
Computational Time ◽  
Transport Networks ◽  
The Road

An increase in the number of vehicles, especially in large cities, and inability of the existing road infrastructure to distribute transport flows, leads to a higher congestion level in transport networks. This problem makes the solution to navigational problems more and more important. Despite the popularity of these tasks, many existing commercial systems find a route in deterministic networks, not taking into account the time-dependent and stochastic properties of traffic flows, i.e. travel time of road links is considered as constant. This paper addresses the reliable routing problem in stochastic networks using actual information of the traffic flow parameters. We consider the following optimality criterion: maximization of the probability of arriving on time at a destination given a departure time and a time budget. The reliable shortest path takes into account the variance of the travel time of the road network segments, which makes it more applicable for solving routing problems in transport networks compared to standard shortest path search algorithms that take into account only the average travel time of network segments. To describe the travel time of the road network segments, it is proposed to use parametrically defined stable Levy probability distributions. The use of stable distributions allows replacing the operation of calculating convolution to determine the reliability of the path to recalculating the parameters of the distributions density, which significantly reduces the computational time of the algorithm. The proposed method gives a solution in the form of a decision, i.e. the route proposed in the solution is not fixed in advance, but adaptively changes depending on changes in the real state of the network. An experimental analysis of the algorithm carried out on a large-scale transport network of Samara, Russia, showed that the presented algorithm can significantly reduce the computational time of the reliable shortest path algorithm with a slight increase in travel time.

scholarly journals Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

2018 ◽  
Vol 10 (11) ◽  
pp. 4188 ◽  
Author(s):  
Myungsik Do ◽  
Hoyong Jung
Keyword(s):  
Road Network ◽  
Network Performance ◽  
Evaluation Method ◽  
Critical Path ◽  
Regional Scale ◽  
The Road ◽  
Performance Loss ◽  
Asset Value ◽  
Total Travel Time ◽  
Infrastructure Performance

In this study, we focus on resilience as the ability of specific infrastructure systems at the regional scale to absorb the shocks of extreme events, such as earthquakes. The occurrence of a disaster such as an earthquake leads to a rapid decrease in infrastructure performance. In the case of road networks, performance might refer to the number of drivers using the road within a certain period of time. The objective of this study is to propose a quantitative evaluation method to analyze road network performance (or performance loss) when natural disasters occur. Furthermore, we use cluster analysis and consider the performance loss and asset value in an attempt to propose a method to determine the critical path that should be prioritized for maintenance. This study aimed at analyzing hazard resilience from the network aspect through a scenario analysis depending on damage recovery after disaster occurrence. This study compared the hazard resilience speed to recover existing performance according to the scenario for damage recovery targeting the selected road network. It was found that the total increase in the utility (e.g., total travel time saved) gradually diminished as the restoration cost increased.

scholarly journals Impact on Road Safety and Operation of Rerouting Traffic in Rural Travel Time Information System

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4145
Author(s):  
Mariusz Kiec ◽  
Carmelo D’Agostino ◽  
Sylwia Pazdan
Keyword(s):  
Information System ◽  
Travel Time ◽  
Traffic Control ◽  
Time Management ◽  
Road Safety ◽  
Road Network ◽  
Safety Level ◽  
The Road ◽  
Traffic Operation ◽  
Time Information

The Travel Time Information System (TTIS) is an Intelligent Traffic Control System installed in Poland. As is common, travel time is the only factor in the decision about rerouting traffic, while a route recommendation may consider multiple criteria, including road safety. The aim of the paper is to analyze the safety level of the entire road network when traffic is rerouted on paths with different road categories, intersection types, road environments, and densities of access points. Furthermore, a comparison between traffic operation and road safety performance was carried out, considering travel time and delay, and we predicted the number of crashes for each possible route. The results of the present study allow for maximizing safety or traffic operation characteristics, providing an effective tool in the management of the rural road system. The paper provides a methodology that can be transferred to other TTISs for real-time management of the road network.

scholarly journals Estimated travel time between the city (Case study: Waru Street-Mojokerto)

2018 ◽  
Vol 181 ◽  
pp. 06004
Author(s):  
S. Waloejo Budi ◽  
Dadang Meru Utomo ◽  
Salsabila W Ninditarari
Keyword(s):  
Land Use ◽  
Travel Time ◽  
Network Performance ◽  
Industrial Area ◽  
Land Use Modeling ◽  
The Road ◽  
On The Road ◽  
The City ◽  
Main Factor

The area in Surabaya and Mojokerto is an industrial area that is increasing quite rapidly. Based on City Mojokerto in Figures Year 2016. From an industrial estate is a change of land use from agriculture or ponds into settlements and / or industries. The occurrence of congestion along this road because of the capacity that is not sufficient to accommodate the number of vehicles passing. The purpose of this research is to know the model of land use interaction, knowing the network performance and know the travel time to be passed. And analyze what components affect the calculation of travel time. Necessary data. The existing land layout along the road and the average traffic calculation data on the road in the study area. To know the travel time must be known in advance the capacity of the road that can be accommodated along the road. After the capacity is known the service performance becomes the main factor in determining road network performance. This research uses regression analysis for land use modeling.

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