Connecting Networkwide Travel Time Reliability and the Network Fundamental Diagram of Traffic Flow

2013 ◽  
Vol 2391 (1) ◽  
pp. 80-91 ◽  
Author(s):  
Hani S. Mahmassani ◽  
Tian Hou ◽  
Meead Saberi
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Travel Time Reliability ◽  
Fundamental Diagram ◽  
Network Fundamental Diagram

Investigating the Effects of Reserved Lanes for Autonomous Vehicles on Congestion and Travel Time Reliability

2017 ◽  
Vol 2622 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Alireza Talebpour ◽  
Hani S. Mahmassani ◽  
Amr Elfar
Keyword(s):  
Travel Time ◽  
Autonomous Vehicles ◽  
Potential Benefit ◽  
Flow Dynamics ◽  
System Level ◽  
Market Penetration ◽  
Travel Time Reliability ◽  
Fundamental Diagram ◽  
Mandatory Use ◽  
Daily Travel

Autonomous vehicles are expected to influence daily travel significantly. Despite autonomous vehicles’ potential to enhance safety and to reduce congestion, energy consumption, and emissions, many studies suggest that the system-level effects will be minimal at low market penetration rates. Introducing reserved lanes for autonomous vehicles is one potential approach to address this limitation because these lanes increase autonomous vehicles’ density. However, preventing regular vehicles from using specific lanes can significantly increase congestion in other lanes. Accordingly, this study explored the potential effects of reserving one lane for autonomous vehicles on traffic flow dynamics and travel time reliability. A two-lane hypothetical segment with an on-ramp and a four-lane highway segment in Chicago, Illinois, was simulated under different market penetration rates of autonomous vehicles. Three strategies were evaluated: ( a) mandatory use of the reserved lane by autonomous vehicles, ( b) optional use of the reserved lane by autonomous vehicles, and (c) limiting autonomous vehicles to operate autonomously in the reserved lane. Policies based on combinations of these strategies were simulated. It was found that optional use of the reserved lane without any limitation on the type of operation could improve congestion and could reduce the scatter in a fundamental diagram. Throughput analysis showed the potential benefit of reserving a lane for autonomous vehicles at market penetration rates of more than 50% for the two-lane highway and 30% for the four-lane highway. Travel time reliability analysis revealed that the optional use of the reserved lane was also significantly beneficial.

scholarly journals Network Fundamental Diagram Based Routing of Vehicle Fleets in Dynamic Traffic Simulations

2020 ◽  
Author(s):  
Florian Dandl ◽  
Gabriel Tilg ◽  
Majid Rostami-Shahrbabaki ◽  
Klaus Bogenberger
Keyword(s):  
Travel Time ◽  
Transportation Network ◽  
Time Factor ◽  
Travel Times ◽  
Dynamic Traffic ◽  
Fundamental Diagram ◽  
Trade Off ◽  
On Demand ◽  
Network Fundamental Diagram ◽  
The Impact

The growing popularity of mobility-on-demand fleets increases the importance to understand the impact of mobility-on-demand fleets on transportation networks and how to regulate them. For this purpose, transportation network simulations are required to contain corresponding routing methods. We study the trade-off between computational efficiency and routing accuracy of different approaches to routing fleets in a dynamic network simulation with endogenous edge travel times: a computationally cheap but less accurate Network Fundamental Diagram (NFD) based method and a more typical Dynamic Traffic Assignment (DTA) based method. The NFD-based approach models network dynamics with a network travel time factor that is determined by the current average network speed and scales free-flow travel times. We analyze the different computational costs of the approaches in a case study for 10,000 origin-destination (OD) pairs in a network of the city of Munich, Germany that reveals speedup factors in the range of 100. The trade-off for this is less accurate travel time estimations for individual OD pairs. Results indicate that the NFD-based approach overestimates the DTA-based travel times, especially when the network is congested. Adjusting the network travel time factor based on pre-processed DTA results, the NFD-based routing approach represents a computationally very efficient methodology that also captures traffic dynamics in an aggregated way.

scholarly journals Network Fundamental Diagram Based Routing of Vehicle Fleets in Dynamic Traffic Simulations

2020 ◽  
Author(s):  
Florian Dandl ◽  
Gabriel Tilg ◽  
Majid Rostami-Shahrbabaki ◽  
Klaus Bogenberger
Keyword(s):  
Travel Time ◽  
Transportation Network ◽  
Time Factor ◽  
Travel Times ◽  
Dynamic Traffic ◽  
Fundamental Diagram ◽  
Trade Off ◽  
On Demand ◽  
Network Fundamental Diagram ◽  
The Impact

The growing popularity of mobility-on-demand fleets increases the importance to understand the impact of mobility-on-demand fleets on transportation networks and how to regulate them. For this purpose, transportation network simulations are required to contain corresponding routing methods. We study the trade-off between computational efficiency and routing accuracy of different approaches to routing fleets in a dynamic network simulation with endogenous edge travel times: a computationally cheap but less accurate Network Fundamental Diagram (NFD) based method and a more typical Dynamic Traffic Assignment (DTA) based method. The NFD-based approach models network dynamics with a network travel time factor that is determined by the current average network speed and scales free-flow travel times. We analyze the different computational costs of the approaches in a case study for 10,000 origin-destination (OD) pairs in a network of the city of Munich, Germany that reveals speedup factors in the range of 100. The trade-off for this is less accurate travel time estimations for individual OD pairs. Results indicate that the NFD-based approach overestimates the DTA-based travel times, especially when the network is congested. Adjusting the network travel time factor based on pre-processed DTA results, the NFD-based routing approach represents a computationally very efficient methodology that also captures traffic dynamics in an aggregated way.

scholarly journals Travel Time Reliability of Bus Operation in Heterogeneous Traffic Conditions of Dar es Salaam City, Tanzania

2020 ◽  
Vol 11 (2) ◽  
pp. 44-55
Author(s):  
Prosper S. Nyaki ◽  
Hannibal Bwire ◽  
Nurdin K. Mushule
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Dar Es Salaam ◽  
Heterogeneous Traffic ◽  
Service Reliability ◽  
Travel Time Reliability ◽  
Activity Scheduling ◽  
Traffic Conditions ◽  
Deviation Coefficient

AbstractThe assessment of travel time reliability enables precise prediction of travel times, better activity scheduling and decisions for all users of the road network. Furthermore, it helps to monitor traffic flow as a crucial strategy for reducing traffic congestion and ensuring high-quality service in urban roads. Travel time reliability is a useful reference tool for evaluating transport service quality, operating costs and system efficiency. However, many analyses of travel time reliability do not provide true travel variation under heterogeneous traffic flow conditions where traffic flow is a mixture of motorized and non-motorized transport. This study analysed travel time reliability under heterogeneous traffic conditions. The travel reliabilities focused on passenger waiting time at bus stops, in-vehicle travel time, and delay time at intersections which were analysed using buffer time, standard deviation, coefficient of variation, and planning time. The data used were obtained from five main bus routes in Dar es Salaam. The results indicate low service reliability in the outbound directions compared to inbound directions. They also intend to raise awareness of policy-makers about the situation and to make them shift from expanding road networks towards optimising road operations.

Field Theory for Some Traffic Phenomena and Fundamental Diagram

2021 ◽  
pp. 036119812110064
Author(s):  
Daiheng Ni
Keyword(s):  
Field Theory ◽  
Traffic Flow ◽  
Causal Effect ◽  
Microscopic Approach ◽  
Fundamental Diagram ◽  
Longitudinal Control ◽  
Effect Analysis ◽  
Vehicle Trajectories ◽  
Vehicle Motion ◽  
Cross Reference

A fundamental diagram consists of a scatter of traffic flow data sampled at a specific location and aggregated from vehicle trajectories. These trajectories, if presented equivalently, constitute a microscopic version of the (conventional) fundamental diagram. The cross-reference between vehicle trajectories and the microscopic fundamental diagram provides details of vehicle motion dynamics which allow causal-effect analysis on some traffic phenomena and further reveal the microscopic basis of the conventional fundamental diagram. This observation inspires theoretical modeling by a microscopic approach to address traffic phenomena and the conventional fundamental diagram. Derived from the field theory of traffic flow, the longitudinal control model is capable of serving the purpose without the modifications or exceptions used by other approaches.

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