Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement

Emerging connected vehicle (CV) data sets have recently become commercially available, enabling analysts to develop a variety of powerful performance measures without deploying any field infrastructure. This paper presents several tools using CV data to evaluate traffic progression quality along a signalized corridor. These include both performance measures for high-level analysis as well as visualizations to examine details of the coordinated operation. With the use of CV data, it is possible to assess not only the movement of traffic on the corridor but also to consider its origin-destination (O-D) path through the corridor. Results for the real-world operation of an eight-intersection signalized arterial are presented. A series of high-level performance measures are used to evaluate overall performance by time of day, with differing results by metric. Next, the details of the operation are examined with the use of two visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon progression diagram (PPD). Comparing flow visualizations developed with different included O-D paths reveals several features, such as the presence of secondary and tertiary platoons on certain sections that cannot be seen when only end-to-end journeys are included. In addition, speed heat maps are generated, providing both speed performance along the corridor and locations and the extent of the queue. The proposed visualization tools portray the corridor’s performance holistically instead of combining individual signal performance metrics. The techniques exhibited in this study are compelling for identifying locations where engineering solutions such as access management or timing plan change are required. The recent progress in infrastructure-free sensing technology has significantly increased the scope of CV data-based traffic management systems, enhancing the significance of this study. The study demonstrates the utility of CV trajectory data for obtaining high-level details of the corridor performance as well as drilling down into the minute specifics.

Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data

Local arterials can be significantly impacted by diversions from adjacent work zones. These diversions often occur on unofficial detour routes due to guidance received on personal navigation devices. Often, these routes do not have sufficient sensing or communication equipment to obtain infrastructure-based traffic signal performance measures, so other data sources are required to identify locations being significantly affected by diversions. This paper examines the network impact caused by the start of an 18-month closure of the I-65/70 interchange (North Split), which usually serves approximately 214,000 vehicles per day in Indianapolis, IN. In anticipation of some proportion of the public diverting from official detour routes to local streets, a connected vehicle monitoring program was established to provide daily performances measures for over 100 intersections in the area without the need for vehicle sensing equipment. This study reports on 13 of the most impacted signals on an alternative arterial to identify locations and time of day where operations are most degraded, so that decision makers have quantitative information to make informed adjustments to the system. Individual vehicle movements at the studied locations are analyzed to estimate changes in volume, split failures, downstream blockage, arrivals on green, and travel times. Over 130,000 trajectories were analyzed in an 11-week period. Weekly afternoon peak period volumes increased by approximately 455%, split failures increased 3%, downstream blockage increased 10%, arrivals on green decreased 16%, and travel time increase 74%. The analysis performed in this paper will serve as a framework for any agency that wants to assess traffic signal performance at hundreds of locations with little or no existing sensing or communication infrastructure to prioritize tactical retiming and/or longer-term infrastructure investments.

Selective parsing to enhance SIP performance

The session initiation protocol （SIP） is used as the signaling protocol in the IP multimedia subsystem （IMS） and the signaling is becoming computing intensive comparing to the current telecommunication network. The SIP is a text-based protocol with characteristics of unordered and verbose headers, variable-size message, and case-insensitive keyword. It imposes challenges for an efficient message processing. The property of SIP elements being able to process SIP messages quickly is critical for the performance of IMS networks. This article investigates the performance of SIP message processed in SIP servers, mainly focusing on improving message parsing by introducing a method named selective parsing for SIP message （SP4SIP）. By modeling and analyzing a SIP server with a tandem Jackson network, it is concluded that parsing messages is the bottleneck of a SIP server performance, i.e., it is the most processing intensive activity in the system. To validate the approach, it has been implemented in a high-performance SIP server in the authors＇ lab. The results show that selective parsing for SIP message can indeed reduce processing time.

Recent advances in traffic signal performance evaluation

Signal retiming is a prominent way that transportation agencies use to fight congestion and change of traffic pattern.Performance evaluations of traffic conditions at signalized intersections and arterials provide actionable data for agencies to make well-informed and prioritized signal retiming decisions.However,the abundance of data sources,the lack of standardized evaluation methods and oftentimes the shortage of resources make it a difficult endeavor.The review detailed in this paper examines the advances made in traffic signal performance evaluation.We establish the necessity for the evaluations,study the process of continuous improvement of traffic signal performance using the evaluations,and then examine multiple methodologies in a plethora of research endeavors.Particularly,we focus on probe vehicles and sensors data,the two major sources of data.We discuss how sensors are connected to signal controllers to provide relevant in-depth traffic data including speed and occupancy measures.We also review the nature of probe vehicles and the level of penetration.We then define and summarize performance measures derived from both sources,to aid in performance evaluations.For performance evaluation methods,we discuss the research studies and provide summaries including advantages and disadvantages of the methods used,as well as a holistic outlook for future research.This paper is aimed to provide a comprehensive review on the state-of-the-art to benefit researcher,traffic agencies,and commercial entities that thrive to improve safety and efficiency of traffic signals through performance evaluations.

Durbin test with enhanced detection performance to mismatched signal

This paper deals with the problem of detecting a signal whose amplitude is a scaling factor in the presence of homogeneous Gaussian noise with unknown covariance matrix.Since no uniformly most powerful test exists for the problem at hand,we devise and assess a detection strategy based on the well-known Durbin test design criteria.The closed-form expressions for the probabilities of false alarm and detection of the Durbin test are derived,which show that it bears a constant false alarm rate property against the noise covariance matrix.At the analysis stage,the performance of the new receiver is assessed,also in comparison with some classical adaptive detectors,both in matched and in mismatched signal cases.The results show that the proposed detector achieves a visible performance improvement in the presence of severe steering vector mismatch,while maintaining an acceptable detection loss for matched signal.

Experimental performance evaluation of quadrature amplitude modulation signal transmission in a silicon microring

We comprehensively characterize the transmission performance of m-ary quadrature amplitude modulation(m-QAM) signals through a silicon microring resonator in the experiment. Using orthogonal frequency-division multiplexing based on offset QAM(OFDM/OQAM) which is modulated with m-QAM modulations, we demonstrate low-penalty data transmission of OFDM/OQAM 64-QAM, 128-QAM, 256-QAM, and 512-QAM signals in a silicon microring resonator. The observed optical signal-to-noise ratio(OSNR) penalties are 1.7 dB for 64-QAM,1.7 dB for 128-QAM, and 3.1 dB for 256-QAM at a bit-error rate(BER) of 2 × 10^(-3) and 3.3 dB for 512-QAM at a BER of 2 × 10^(-2). The performance degradation due to the wavelength detuning from the microring resonance is evaluated, showing a wavelength range of ~0.48 nm with BER below 2 × 10^(-3). Moreover, we demonstrate data transmission of 191.2-Gbit/s simultaneous eight wavelength channel OFDM/OQAM 256-QAM signals in a silicon microring resonator, achieving OSNR penalties less than 2 dB at a BER of 2 × 10^(-2).

THE EFFECTS OF CORRELATED SENSOR SIGNAL FLUCTUATION ON THE STATISTICAL PERFORMANCE OF AN AR HIGH RESOLUTION ARRAY PROCESSOR

The statistical performance of AR high resolution array processor in presence of correlated sensor signal fluctuation is studied. Mean square inverse beam pattern and pointing error are examined. Special attention is paid to the effects of reference sensor and correlation between sensors. It is shown that fluctuation causes broadening or even distortion of the mean square inverse beam pattern. Phase fluctuation causes pointing error. Its standard variance is proportional to that of fluctuation and is related to the number of sensors of the array. Correlation between sensors has important effects on pointing error.

Evaluation of the performance of linearly frequency modulated signals generated by heterodyning two free-running laser diodes

A method to evaluate the influence of the laser linewidth on the linearly frequency-modulated(LFM)signals generated by heterodyning two free-running laser diodes(LDs)is proposed.The Pearson correlation coefficient between the instantaneous frequency of the generated LFM signal and that of an ideal LFM signal is introduced to quantify the quality of the generated LFM signal.The closed-form solution of the correlation coefficient is given,which shows that the correlation coefficient is determined by the ratio of the LFM signal bandwidth to the square root of the total linewidth of the two LDs when the observation interval is fixed.Simulation results are also given,which proves the correctness of the theoretical results.

Single-shot incoherent optical processing of microwave signals： opening the path to low cost high performance analog photonics

Incoherent optical processing of microwave signals,where low-coherence broadband light sources are employed instead of costly mode locked lasers,has attracted great interest thanks to its wide applications in microwave photonics filtering[1–3],arbitrary generation[4–6]and analog to digital conversion[7]。

Study on the performance of data fusion system for sonar signal detection

The mathematical model and fusion algorithm for multisensor data fusion are presented, and applied to integrate the decisions obtained by multiple sonars in a distributed detection system. Assuming that all the sonars and the fusion system operate at the same false alarm probability, the expression for the detection probability of the fusion system is obtained. Computer simulations reveals that the detection probability and detection range of the fusion system are significantly improved compared to the original distributed detection system.

Use of Hi-resolution data for evaluating accuracy of traffic volume counts collected by microwave sensors

Over the past few years, the Utah Department of Transportation has developed the signal performance metrics （SPMs） system to evaluate the performance of signalized in- tersections dynamically. This system currently provides data summaries for several per- formance measures, one of them being turning movement counts collected by microwave sensors. As this system became public, there was a need to evaluate the accuracy of the data placed on the SPMs. A large-scale data collection was carried out to meet this need. Vehicles in the Hi-resolution data from microwave sensors were matched with the vehicles by ground-truth volume count data. Matching vehicles from the microwave sensor data and the ground-truth data manually collected required significant effort, A spreadsheet- based data analysis procedure was developed to carry out the task. A mixed model analysis of variance was used to analyze the effects of the factors considered on turning volume count accuracy. The analysis found that approach volume level and number of approach lanes would have significant effect on the accuracy of turning volume counts but the location of the sensors did not significantly affect the accuracy of turning volume counts. In addition, it was found that the location of lanes in relation to the sensor did not significantly affect the accuracy of lane-by-lane volume counts. This indicated that accu- racy analysis could be performed by using total approach volumes without comparing specific turning counts, that is, left-turn, through and right-turn movements. In general, the accuracy of approach volume counts collected by microwave sensors were within the margin of error that traffic engineers could accept. The procedure taken to perform the analysis and a summary of accuracy of volume counts for the factor combinations considered are presented in this paper.