Effecting Analysis of Real-Time Traffic Guidance Information on Travel Time Reliability in a Connected Vehicle Environment

CICTP 2016 ◽  
2016 ◽  
Author(s):  
Jiangfeng Wang ◽  
Zhouyuan Zhu ◽  
Qian Zhang ◽  
Chang Gao
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Connected Vehicle ◽  
Travel Time Reliability ◽  
Real Time Traffic ◽  
Traffic Guidance ◽  
Guidance Information

scholarly journals Modeling Travel Time Reliability of Road Network Considering Connected Vehicle Guidance Characteristics Indexes

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jiangfeng Wang ◽  
Chao Wang ◽  
Jiarun Lv ◽  
Zhiqi Zhang ◽  
Cuicui Li
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Compliance Rate ◽  
Connected Vehicle ◽  
Travel Time Reliability ◽  
Improvement Rate ◽  
Explanatory Variables ◽  
Real Time Traffic ◽  
Traffic Guidance ◽  
The Impact

Travel time reliability (TTR) is one of the important indexes for effectively evaluating the performance of road network, and TTR can effectively be improved using the real-time traffic guidance information. Compared with traditional traffic guidance, connected vehicle (CV) guidance can provide travelers with more timely and accurate travel information, which can further improve the travel efficiency of road network. Five CV characteristics indexes are selected as explanatory variables including the Congestion Level (CL), Penetration Rate (PR), Compliance Rate (CR), release Delay Time (DT), and Following Rate (FR). Based on the five explanatory variables, a TTR model is proposed using the multilogistic regression method, and the prediction accuracy and the impact of characteristics indexes on TTR are analyzed using a CV guidance scenario. The simulation results indicate that 80% of the RMSE is concentrated within the interval of 0 to 0.0412. The correlation analysis of characteristics indexes shows that the influence of CL, PR, CR, and DT on the TTR is significant. PR and CR have a positive effect on TTR, and the average improvement rate is about 77.03% and 73.20% with the increase of PR and CR, respectively, while CL and DT have a negative effect on TTR, and TTR decreases by 31.21% with the increase of DT from 0 to 180 s.

scholarly journals RealTE: Real-time Trajectory Estimation Over Large-Scale Road Networks

2022 ◽  
Author(s):  
Qibin Zhou ◽  
Qingang Su ◽  
Dingyu Yang
Keyword(s):  
Travel Time ◽  
Real Time ◽  
High Speed ◽  
Road Network ◽  
Large Scale ◽  
Road Networks ◽  
Trajectory Data ◽  
Real Time Traffic ◽  
Histogram Estimation ◽  
Traffic Estimation

Real-time traffic estimation focuses on predicting the travel time of one travel path, which is capable of helping drivers selecting an appropriate or favor path. Statistical analysis or neural network approaches have been explored to predict the travel time on a massive volume of traffic data. These methods need to be updated when the traffic varies frequently, which incurs tremendous overhead. We build a system RealTER⁢e⁢a⁢l⁢T⁢E, implemented on a popular and open source streaming system StormS⁢t⁢o⁢r⁢m to quickly deal with high speed trajectory data. In RealTER⁢e⁢a⁢l⁢T⁢E, we propose a locality-sensitive partition and deployment algorithm for a large road network. A histogram estimation approach is adopted to predict the traffic. This approach is general and able to be incremental updated in parallel. Extensive experiments are conducted on six real road networks and the results illustrate RealTE achieves higher throughput and lower prediction error than existing methods. The runtime of a traffic estimation is less than 11 seconds over a large road network and it takes only 619619 microseconds for model updates.

scholarly journals Cross-Vendor and Cross-State Analysis of GPS Probe Data Latency

2018 ◽  
Vol 2672 (42) ◽  
pp. 180-191 ◽  
Author(s):  
Zhongxiang Wang ◽  
Masoud Hamedi ◽  
Elham Sharifi ◽  
Stanley Young
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Ground Truth ◽  
Traffic Information ◽  
Incident Detection ◽  
Dynamic Message Signs ◽  
Real Time Traffic ◽  
Outsourced Data ◽  
Message Signs

Crowd sourced GPS probe data have become a major source of real-time traffic information applications. In addition to traditional traveler advisory systems such as dynamic message signs (DMS) and 511 systems, probe data are being used for automatic incident detection, integrated corridor management (ICM), end of queue warning systems, and mobility-related smartphone applications. Several private sector vendors offer minute by minute network-wide travel time and speed probe data. The quality of such data in terms of deviation of the reported travel time and speeds from ground-truth has been extensively studied in recent years, and as a result concerns over the accuracy of probe data have mostly faded away. However, the latency of probe data—defined as the lag between the time at which disturbance in traffic speed is reported in the outsourced data feed, and the time at which the traffic is perturbed—has become a subject of interest. The extent of latency of probe data for real-time applications is critical, so it is important to have a good understanding of the amount of latency and its influencing factors. This paper uses high-quality independent Bluetooth/Wi-Fi re-identification data collected on multiple freeway segments in three different states, to measure the latency of the vehicle probe data provided by three major vendors. The statistical distribution of the latency and its sensitivity to speed slowdown and recovery periods are discussed.

scholarly journals Effect of Traffic Information on Travel Time of Medium-distance Trips: A Case Study in Tehran

2018 ◽  
Vol 30 (3) ◽  
pp. 281-291 ◽  
Author(s):  
Roozbeh Mohammadi ◽  
Amir Golroo ◽  
Mahdieh Hasani
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Information Dissemination ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Trip Distance ◽  
Traffic Information Dissemination ◽  
Time Reduction

In populated cities with high traffic congestion, traffic information may play a key role in choosing the fastest route between origins and destinations, thus saving travel time. Several research studies investigated the effect of traffic information on travel time. However, little attention has been given to the effect of traffic information on travel time according to trip distance. This paper aims to investigate the relation between real-time traffic information dissemination and travel time reduction for medium-distance trips. To examine this relation, a methodology is applied to compare travel times of two types of vehicle, with and without traffic information, travelling between an origin and a destination employing probe vehicles. A real case study in the metropolitan city of Tehran, the capital of Iran, is applied to test the methodology. There is no significant statistical evidence to prove that traffic information would have a significant impact on travel time reduction in a medium-distance trip according to the case study.

scholarly journals Connected Vehicle Technology for Improved Multimodal Winter Travel: Agency Perspective and a Conceptual Exploration

2020 ◽  
Vol 12 (12) ◽  
pp. 5071
Author(s):  
Yaqin He ◽  
Md Tawhidur Rahman ◽  
Michelle Akin ◽  
Yinhai Wang ◽  
Kakan Dey ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Nationwide Survey ◽  
Travel Agency ◽  
Connected Vehicle ◽  
The Road ◽  
Real Time Traffic ◽  
Positive Attitudes ◽  
Connected Vehicle Technology ◽  
Transit Operation

Accurate and real-time traffic and road weather information acquired using connected vehicle (CV) technologies can help commuters perform safe and reliable trips. A nationwide survey of transit operation managers/supervisors was conducted to assess the suitability for CV transit applications in improving the safety and mobility during winter weather. Almost all respondents expressed positive attitudes towards the potential of CV applications in improving winter transit travel and voiced their concerns over the safety consequences of CV equipment failure, potential of increased driver distraction, and reliability of system performance in poor weather. A concept of operations of CV applications for multimodal winter travel was developed. In the conceptual framework, route-specific road weather and traffic flow data will be used by the transit managers/supervisors to obtain real-time operational status, forecast operational routes and schedules, and assess operational performance. Subsequently, multimodal commuters can receive the road-weather and traffic-flow information as well as transit routes and schedule information.

scholarly journals An Improved Healthcare Accessibility Measure Considering the Temporal Dimension and Population Demand of Different Ages

2018 ◽  
Vol 15 (11) ◽  
pp. 2421 ◽  
Author(s):  
Lan Ma ◽  
Nianxue Luo ◽  
Taili Wan ◽  
Chunchun Hu ◽  
Mingjun Peng
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Supply And Demand ◽  
Spatial Accessibility ◽  
Accurate Estimation ◽  
Temporal Dimension ◽  
Medical Needs ◽  
Real Time Traffic ◽  
Healthcare Accessibility ◽  
Time Periods

Healthcare accessibility has become an issue of social equity. An accurate estimation of existing healthcare accessibility is vital to plan and allocate health resources. Healthcare capacity, population demand, and geographic impedance are three essential factors to measure spatial accessibility. Additionally, geographic impedance is usually represented with a function of travel time. In this paper, the three-step floating catchment area (3SFCA) method is improved from the perspectives of the temporal dimension and population demand. Specifically, the travel time from the population location to the service site is precisely calculated by introducing real-time traffic conditions instead of utilizing empirical speed in previous studies. Additionally, with the utilization of real-time traffic, a dynamic result of healthcare accessibility is derived during different time periods. In addition, since the medical needs of the elderly are higher than that of the young, a demand weight index of demand is introduced to adjust the population demand. A case study of healthcare accessibility in Wuhan shows that the proposed method is effective to measure healthcare accessibility during different time periods. The spatial accessibility disparities of communities and crowdedness of hospitals are identified as an important reference for the balance between the supply and demand of medical resources.

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