scholarly journals Impact on Network Performance of Probe Vehicle Data Usage: An Experimental Design for Simulation Assessment

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lídia Montero ◽  
Maria Paz Linares ◽  
Josep Casanovas ◽  
Esteve Codina ◽  
Gonzalo Recio ◽  
...  
Keyword(s):  
Network Performance ◽  
Point Of View ◽  
Traffic Information ◽  
Route Guidance ◽  
Microscopic Simulation ◽  
Model Driven ◽  
Probe Vehicles ◽  
Real Time Traffic ◽  
Vehicle Data ◽  
Navigation Service

Probe-based technologies are proliferating as a means of inferring traffic states. Technological companies are interested in traffic data for computing the best routes in a traffic-aware manner and they also provide real-time traffic information with certain temporal accuracy. This paper analyses and evaluates how data provided by a fleet of probe cars can be used to develop a navigation service and how the penetration rate of this service affects a set of city-scale KPIs (Key Performance Indicators) and driver KPIs. The case study adopts a model-driven approach in which microscopic simulation emulates real-size fleets of probe vehicles that provide positions and speed data. What is noteworthy about the modelling behaviour is that drivers are segmented according to their knowledge of network conditions for selected trips: experts, regular drivers, and tourists. The paper presents and discusses the modelling approach and the results obtained from an experimental Barcelona CBD model designed to evaluate the penetration rates of probe vehicles and route guidance. An analysis of the simulation experiments reveals remarkable links among city-scale KPIs, which—from a multivariate point of view—is a novelty. A simulation-based framework for results analysis and visualization is also introduced in order to simplify the simulation results analysis and easily visualize OD paths for driver segments.

scholarly journals Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements

2020 ◽  
Vol 12 (19) ◽  
pp. 8145
Author(s):  
Maximilian Braun ◽  
Jan Kunkler ◽  
Florian Kellner
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Network Performance ◽  
Service Providers ◽  
Traffic Information ◽  
Performance Measurements ◽  
Real World Data ◽  
Network Characteristics ◽  
Navigation Service ◽  
German Cities

Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.

Determination of Number of Probe Vehicles Required for Reliable Travel Time Measurement in Urban Network

1996 ◽  
Vol 1537 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Karthik K. Srinivasan ◽  
Paul P. Jovanis
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
High Speed ◽  
Time Estimation ◽  
Traffic Information ◽  
Peak Period ◽  
Urban Network ◽  
Reliability Criterion ◽  
Probe Vehicles ◽  
Real Time Traffic

Several intelligent vehicle–highway system demonstration projects are currently assessing the feasibility of using probe vehicles to collect realtime traffic data for advanced traffic management and information systems. They have used a variety of criteria to determine the number of probes necessary, but few generalizable algorithms have been developed and tested. The described algorithm explicitly considers the time period for travel time estimation (e.g., 5, 10, or 15 min), the number of replications of travel time desired for each link during each measurement period (reliability criterion), the proportion of links to be covered, and the length of the peak period. This algorithm is implemented by using a simulation of the Sacramento Network (170 mi2) for the morning peak period. The results indicate that the number of probe vehicles required increases non-linearly as the reliability criterion is made more stringent. More probes are required for shorter measurement periods. As the desired proportion of link coverage in the network increases, the number of probes required increases. With a given number of probes a greater proportion of freeway links than of major arterials can reliably be covered. Probe vehicles appear to be an attractive source of real-time traffic information in heavily traveled, high-speed corridors such as freeways and major arterials during peak periods, but they are not recommended for coverage of minor arterials or local and collector streets or during off-peak hours.

Perspectives on Driver Preferences for Dynamic Route Guidance Systems

1997 ◽  
Vol 1588 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Joseph L. Schofer ◽  
Frank S. Koppelman ◽  
William A. Charlton
Keyword(s):  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Route Planning ◽  
Traffic Information ◽  
Route Guidance ◽  
Real Time Traffic ◽  
Operational Test ◽  
Guidance Systems ◽  
Dynamic Route ◽  
And Storage

Insights about the design of route guidance systems based on the needs and desires of drivers who are familiar with the travel network are provided. Results from the ADVANCE Intelligent Transportation System operational test, in which more than 100 drivers used vehicles equipped with dynamic route guidance systems for 2-week periods, suggest that such drivers value real-time traffic information, and they want to incorporate their own knowledge and perspectives into the development of route plans, which they expect to be superior to those prepared by the navigation computer. This suggests that future route guidance systems likely to be targeted at familiar drivers should be based on a sharing of tasks between computer and driver that takes greater advantage of driver knowledge than that considered in current designs. Specifically, the driver should be able to take more responsibility for route planning, with the computer responsible mainly for traffic congestion data acquisition, organization and storage, and evaluation of driver-defined routes.

Online Dispatching and Routing Model for Emergency Vehicles with Area Coverage Constraints

2005 ◽  
Vol 1923 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Saini Yang ◽  
Masoud Hamedi ◽  
Ali Haghani
Keyword(s):  
Emergency Response ◽  
Response Times ◽  
Service Area ◽  
Area Coverage ◽  
Traffic Information ◽  
Route Guidance ◽  
Shortest Path Algorithm ◽  
Emergency Response System ◽  
Real Time Traffic ◽  
Different Types

Response time plays a crucial role in reducing the loss of assets and lives caused by emergencies. Good dispatch strategies for emergency response vehicles result in more efficient service, and route guidance can help reduce vehicles’ travel times. Because of a limited number and type of emergency response vehicles at each station, service area gaps will be created: they cannot be properly covered by the remaining emergency response vehicles when some vehicles are dispatched. Future emergency calls in these areas may experience longer response times than usual. In this paper, an optimization model is developed that, given real-time traffic information, can assist dispatchers of emergency response vehicle in assigning multiple emergency response vehicles to incidents and in determining the routes that avoid congestion spots in the transportation networks. This model accounts for the service area coverage concerns (when several vehicles are busy) by relocation and redistribution of the remaining vehicles among stations. The results show that coordination of different types of vehicles, relocation of vehicles for better area coverage, and use of a time-dependent shortest path algorithm in this model significantly improve the performance of the emergency response system.

M-Traffic

2011 ◽  
pp. 229-250
Author(s):  
Teresa Romão ◽  
Luís Rato ◽  
Antão Almada ◽  
A. Eduardo Dias
Keyword(s):  
Proper Time ◽  
Information Service ◽  
Traffic Information ◽  
Microscopic Simulation ◽  
High Concentration ◽  
Real Time Traffic ◽  
Online Traffic ◽  
Mobile Information Service ◽  
Behaviour Models ◽  
Definition Of

Traffic information is crucial in metropolitan areas, where a high concentration of moving vehicles causes traffic congestion and blockage. Appropriate traffic information received at the proper time helps users to avoid unnecessary delays, choosing the fastest route that serves their purposes. This work presents Mobile Traffic (M-Traffic), a multiplatform online traffic information system, which provides real-time traffic information based on image processing, sensor’s data, and traveller behaviour models. This system has a modular architecture that allows it to easily be adapted to new data sources and additional distribution platforms. In order to estimate route delay and feed the optimal routing algorithm, a traffic microscopic simulation model was developed, and simulation results are presented. This mobile information service ubiquitously provides users with traffic information regarding their needs and preferences, according to an alert system, which allows a personalized pre-definition of warning messages.

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