Jiaqi Ma

How big data serves for freight safety management at highway-rail grade crossings? A spatial approach fused with path analysis

Future vehicle warning systems needs a local (instead of global) analysis of real-time information transmitted between vehicles and infrastructures, to provide local warning information matching the instantaneous driving contexts. Spatial modeling techniques extracting the location information into the analysis fulfill the needs of local analysis. For truck-involved collisions at highway-rail crossings, the local warnings seem to matters more, than for traffic crashes at the normal highway segments and regular intersections. Crashes at rail grade crossings can result in severe injuries and fatalities to vehicle occupants, while truck-involved crashes at crossings can further result in serious damage to train, crossing and railway equipment. Truck-involved crashes at grade crossings have received limited attention compared with crashes involved with passenger cars. This study presents a methodology of improving safety of trucks at railroad crossings, by taking advantage of the big data containing location information. Unlike previous studies that constructed a direct relationship between the safety outcomes and associated factors, this study investigates direct relationships together with indirect relationships through the truck driver behaviors before collisions, using path analysis techniques. To sum up, this study applies a spatial approach fused with path analysis to uncover the local relationships between truck driver injury severity and crossing controls across the space. By doing so, the research is able to: i) provide a benchmark of identifying potentially risky vehicles on a real time basis; ii) evaluate current control devices at railroad crossing across the country and pin point the potentially problematic crossing sites. An empirical study was conducted by using a rich crash database from the Federal Railroad Administration (N= 4738 for 2004-2014). The results show that truck-involved crashes occurring at crossings without gate controls are generally associated with higher chance of injury, while the associations vary significantly across the space. In general, crashes in the Midwest and Great Lake regions are associated with an even higher chance of injury at crossings without gates, compared with other regions. More Results and implications are discussed in the paper.

Examining the Impact of Adverse Weather on Urban Rail Transit Facilities on the Basis of Fault Tree Analysis and Fuzzy Synthetic Evaluation

The increasingly frequent extreme weather disasters caused by global climate change have attracted more attention to adverse weathers effect on infrastructure systems. This paper aims to establish an integrated approach to assessing adverse weathers effect on urban rail transit facilities and to provide decision makers with a powerful tool to analyze potential risks and allocate limited sources for risk management. First, fault tree analysis is used to understand where the risks are, how the risks will occur, and what factors have the most significant effects by analyzing all possible basic events. All wind-, rain-, and snow-related adverse weather, along with human-related factors (construction leftover problems and design drawbacks), are found to potentially cause great risks. Adverse impact scenarios are summarized based on the fault tree analysis. Next, an analytic hierarchical process (AHP)-based fuzzy synthetic evaluation model is established to assess the risk level based on an evaluation index system. AHP is used to calculate the weights between the indices for each adverse weather factor. A fuzzy synthetic evaluation process is then carried out to identify the risk level of an evaluation target, an urban rail transit station, or line section. A case study on the Beijing URT Line 8 Olympic Center Station is conducted to illustrate the process of evaluation. The results show that the risk level is high and it becomes acceptable only after countermeasures are taken. Potential countermeasures regarding facility capacity, protection area management, and monitoring/inspection are then briefly discussed. Language: en

Freeway Speed Harmonization

In this paper, we present an overview and background on speed harmonization (SH). This paper reviews a number of representative studies that designed traffic control algorithms based on variable speed limits, ramp metering, connected vehicle, or automated vehicle for SH. We summarize fundamental mechanisms, control algorithms, and evaluation results of these studies. We investigate the opportunities brought by a portion of the vehicles communicating with each other using new technologies. We also investigate opportunities due to some vehicles having automated speed control. We discuss experiments undertaken and underline a new experiment performed in real traffic. Finally, we discuss other new SH experiments that can be undertaken as market penetration makes communication ubiquitous.

Field Evaluations of an Adaptive Traffic Signal—Using Private-Sector Probe Data

AbstractThis study evaluated the in-service performance of the InSync adaptive signal control (ASC) system utilizing field data collected from the private sector travel time vendor INRIX. A total of six corridors in Virginia were tested, with extensive data collected over 6 months. The measurements of effectiveness (MOEs) adopted are mainline delay savings and travel time reliability measurements (95th percentile travel time and buffer index). All the before-and-after MOEs were compared using t-tests, and the Pearson correlation of the MOEs with respect to various quantitative site-specific factors was assessed to determine if effectiveness could be tied to specific site characteristics. The results indicate that the adaptive signal control system generally reduces delay by about 25% and improves travel time reliability by about 16%. The performance of ASC system is affected by site-specific factors, like annual average daily traffic, signal density, and access point density.

Comparison of In-Vehicle Auditory Public Traffic Information With Roadside Dynamic Message Signs

Dynamic message signs (DMS) have been widely used by transportation agencies to disseminate traffic information (referred to in this article as “public traffic information”) for decades. Unfortunately, their effectiveness is limited, based on the following reasons: they are costly, can only present a limited amount of information, and typically only display information in one language. The wide availability of smart devices and the development of connected vehicles offer the possibility to create “virtual” DMS (VDMS), utilizing geofencing and audible messages to convey public traffic information. This research compares the ability of VDMS to convey public traffic information with existing DMS. A mixed repeated-measure experiment using a driving simulator was designed that examined the impacts of driver age, information transmission mode, amount of information, and driving complexity on message comprehension. Forty-two participants were recruited and each of them was tested under different combinations of the three within-subject factors. Participant performance was measured in terms of message comprehension, distraction, and self-reported overall difficulty level in receiving messages. Results revealed that VDMS generally performs better than DMS as information content increases and driving condition complexity increases, regardless of driver age. VDMS increased message comprehension by 16% under relatively complex driving conditions, reduced driver reaction time to unexpected stimuli (as measured with a reduced time-to-brake of 0.39 s), and made the same messages easier to process and retain for drivers than DMS. Based on these results, it is recommended that transportation agencies give careful consideration to VDMS as a future strategy for delivering public traffic information in a connected vehicle environment.

Estimation of Crash Modification Factors for an Adaptive Traffic-Signal Control System

AbstractAdaptive traffic-signal control (ATSC) is a traffic management strategy in which traffic-signal timings change, or adapt, based on observed traffic demand. Although ATSC can improve mobility, it also has the potential to reduce crashes because mainline stops should be reduced. This paper aims to evaluate the safety effectiveness of ATSC using the empirical Bayes method. This analysis examines 47 urban or suburban intersections where ATSC was deployed in Virginia using 235 site-years of before data and 66 site-years of after data. Installing ATSC was found to produce a crash modification factor (CMF) for total intersection crashes of 0.83 with a standard error of 0.05. This CMF was statistically significant at a 95 percent confidence level. Fatal and injury crashes did not change by a statistically significant amount, indicating that the primary safety benefit of ATSC was reduction in property damage crashes. Analyses of ATSC safety effects by crash type, by traffic volume level, and by operational...

Dynamic Hard Shoulder Running for Traffic Incident Management

Hard shoulder running (HSR), used in many large cities for reducing peak hour recurring congestion, has been proved effective. This paper looks at another perspective of using hard shoulders and proposes dynamic hard shoulder running (D-HSR) for traffic incident management. The purpose of this paper is to show the benefits and make recommendations to state departments of transportation and local agencies on how to use hard shoulders dynamically to reduce the effects of nonrecurring traffic incidents. An approach based on microscopic simulation with factorial experimental design is adopted in this study, and interesting results are obtained from the discussion and statistical analyses of simulation results: (a) D-HSR strategies are more suitable for property damage only incidents in which traffic operations centers have more flexibility in managing traffic; (b) only the part of the shoulder that is 0.5 mi upstream and downstream of the incident location needs to be opened to achieve maximum benefits for relieving a bottleneck; (c) the opened shoulder can be closed after the incident is cleared, and opening the shoulder for a longer time will not improve traffic conditions; and (d) the effectiveness of D-HSR is significant across different roadway geometry, traffic, and incident scenarios. Equations to estimate potential benefits are also available in this paper. These results are favorable particularly in practice because shoulders need to serve as refuge areas for incident vehicles and be used by emergency vehicles. It is recommended that departments of transportation and local agencies consider D-HSR for relieving congestion during incidents.

Quality of Private Sector Travel-Time Data on Arterials

AbstractAccurate traffic state information is essential for both travelers and transportation agencies. In the past, traffic condition data were usually collected by a government agency using its own sensors. Recently, a number of private sector companies have started selling travel-time and speed data collected using probe vehicles, which provides a viable opportunity to outsource traffic data collection. Because these data sources and their related algorithms are proprietary, the reliability and accuracy of this private sector data is often an important issue for transportation agencies. Previous studies have examined the accuracy of private sector data on freeways, but arterials have not been examined extensively. Arterials represent a fundamentally more challenging environment for probe vehicle data given the larger variance in travel times created by traffic signals and other intermediate access points. In the research, the quality of private sector data on arterials is evaluated by utilizing Bluetoo...

Hardware-in-the-Loop Testing of Connected and Automated Vehicle Applications: A Use Case for Queue-Aware Signalized Intersection Approach and Departure

Most existing studies on connected and automated vehicle (CAV) applications apply simulation to evaluate system effectiveness. Model accuracy, limited data for calibration, and simulation assumptions limit the validity of evaluation results. One alternative approach is to use emerging hardware-in-the-loop (HIL) testing methods. HIL test environments enable physical test vehicles to interact with virtual vehicles from traffic simulation models, providing an evaluation environment that can replicate deployment conditions at early stages of CAV technology implementation without incurring excessive costs related to large field tests. In this study, a HIL testing system for vehicle-to-infrastructure (V2I) CAV applications is developed. The involved software and hardware includes a physical CAV controlled in real time, a traffic signal controller, communication devices, and a traffic simulator (VISSIM). Such HIL systems increase validity by considering the physical vehicle’s trajectories—which are constrained by real-world factors such as GPS accuracy, communication delay, and vehicle dynamics—in a simulated traffic environment. The developed HIL system is applied to test a representative early deployment CAV application: queue-aware signalized intersection approach and departure (Q-SIAD). The Q-SIAD algorithm generates recommended speed profiles based on the vehicle’s status, signal phase and timing (SPaT), downstream queue length, and system constraints and parameters (e.g., maximum acceleration and deceleration). The algorithm also considers the status of other vehicles in designing the speed profiles. The experiment successfully demonstrated this functionality with one test CAV driving through one intersection controlled by a fixed-timing traffic signal under various simulated traffic conditions.

Evaluation of countermeasures for red light running by traffic simulator–based surrogate safety measures

ABSTRACT Objective: The conflicts among motorists entering a signalized intersection with the red light indication have become a national safety issue. Because of its sensitivity, efforts have been made to investigate the possible causes and effectiveness of countermeasures using comparison sites and/or before-and-after studies. Nevertheless, these approaches are ineffective when comparison sites cannot be found, or crash data sets are not readily available or not reliable for statistical analysis. Considering the random nature of red light running (RLR) crashes, an inventive approach regardless of data availability is necessary to evaluate the effectiveness of each countermeasure face to face. Method: The aims of this research are to (1) review erstwhile literature related to red light running and traffic safety models; (2) propose a practical methodology for evaluation of RLR countermeasures with a microscopic traffic simulation model and surrogate safety assessment model (SSAM); (3) apply the proposed methodology to actual signalized intersection in Virginia, with the most prevalent scenarios—increasing the yellow signal interval duration, installing an advance warning sign, and an RLR camera; and (4) analyze the relative effectiveness by RLR frequency and the number of conflicts (rear-end and crossing). Results: All scenarios show a reduction in RLR frequency (−7.8, −45.5, and −52.4%, respectively), but only increasing the yellow signal interval duration results in a reduced total number of conflicts (−11.3%; a surrogate safety measure of possible RLR-related crashes). An RLR camera makes the greatest reduction (−60.9%) in crossing conflicts (a surrogate safety measure of possible angle crashes), whereas increasing the yellow signal interval duration results in only a 12.8% reduction of rear-end conflicts (a surrogate safety measure of possible rear-end crash). Conclusions: Although increasing the yellow signal interval duration is advantageous because this reduces the total conflicts (a possibility of total RLR-related crashes), each countermeasure shows different effects by RLR-related conflict types that can be referred to when making a decision. Given that each intersection has different RLR crash issues, evaluated countermeasures are directly applicable to enhance the cost and time effectiveness, according to the situation of the target intersection. In addition, the proposed methodology is replicable at any site that has a dearth of crash data and/or comparison sites in order to test any other countermeasures (both engineering and enforcement countermeasures) for RLR crashes.