SWOV Catalogus

343758

Development of a queue warning system utilizing ATM infrastructure system development and field testing.
20170423 ST [electronic version only]
Hourdos, J. Liu, Z. Dirks, P. Liu, H.X. Huang, S. Sun, W. & Xiao, L.
St. Paul, Minnesota, Minnesota Department of Transportation, Research Services & Library, 2017, 73 p., 81 ref.; MN/RC 2017-20

Samenvatting In 2014, the Minnesota Department of Public Safety (DPS) reported 15,648 crashes occurred on Minnesota freeways. These crashes accounted for the death of 38 people and the injury of 5,031 people (3). Rear-end crashes are a typical type of crash on freeways. Although, rear-end crashes can happen any time there is a disturbance, research has shown (4) that there are traffic conditions that are associated with collisions, specifically rear-end collisions. Prior studies have shown that such crash prone traffic Conditions (CPCs) can be detected over other traffic conditions encountered on freeway traffic. The research described in this report aimed to develop and field test two queue warning systems using different philosophies in regard to rear-end collision safety. The first system’s philosophy, follows the premise that freeway rear-end collisions tend to occur in extended stop-and-go traffic or at end-of-queue locations (29). Such unconditional queue warning systems usually provide warning messages in an unselective manner, i.e., react to all the queues based on the assumption that all propagating queues are dangerous and drivers should be warned. Conditions on I-35W southbound in Minneapolis, MN, support this hypothesis, and it is there where the first system prototype was developed and deployed. This system was developed by a research team lead by Dr. Henry Liu at the University of Michigan. The second queue warning system is based on the hypothesis that not all congestion events are dangerous but there are certain traffic conditions that are crash prone regardless of whether they result in standing queues or not. Such CPCs can be isolated, fast moving shockwaves, involving only a small number of vehicles in the deceleration-stop-acceleration cycle. For such conditions, a much more dense detection infrastructure is needed. One location where such conditions have been identified and result in more than 100 crashes per year is the westbound section of I-94 in downtown Minneapolis. In this location, the Minnesota Traffic Observatory has had a permanent Field Lab since 2002. Based on the framework proposed by Dr. Hourdos (4), this effort approaches the topic from the quantification of traffic flow to the multi-layer system design along with different approaches including traffic assessment modeling and the development of control algorithms. This approach utilizes individual vehicle measurements including individual vehicle speeds and time headways, as the major type of data for the system operation. The prototype of a CPC detection-based queue warning system was developed by a research team lead by Dr. John Hourdos at the University of Minnesota. The I-94 CPC Queue Warning system follows a three-layer design. The crash probability layer collects real-time individual vehicle measurements and processes them to remove noise. The filtered data then pass to the crash-probability model to assess the likelihood of a crash. This crash likelihood along with additional traffic information, such as speeds and headways, are passed to the second layer, the algorithm layer. In this layer, the algorithm decides if a warning message should be generated by comparing the crash probability with preset thresholds and real-time traffic conditions. A decision of whether to raise or drop the alarm is being generated and passed to the third layer, system control, in which requirements from policy makers are applied to modify the result before delivering it to the message sign in the field. Specifically, as part of the terms for the deployment of the system, two overrides were included and the preexisting MnDOT signs’ refresh rate was kept. Two sets of Intelligent Lane Control Signs (ILCSs) are used to communicate the warnings to the drivers. The overrides are intended to limit possible overexposure of drivers to the warning by what was, at the time of implementation, an unproven system and consist of a time override and a congestion override. The time override prevents the sign from being turned on, regardless of the alarm status before noon or after 8 p.m. The congestion override also prevents the sign from being turned on when five consecutive 30- second average speed measurements at the loop detector near the farthest upstream sign are below 25 mph. This override is intended to reduce driver overexposure to the warning by not displaying a warning when drivers are already travelling slowly. The rate at which the sign is updated is a result of the sign being part of the MnDOT Twin Cities metro-wide network. Initial activation can vary from a few seconds to one minute, depending on the synchronization between the independent queue warning system and the traffic operations system that controls the signs. This delay amplifies short gaps in the alarm activation. To obtain the ground truth on which the I-94 system was evaluated, event observations were collected during a three-month evaluation period (from June 2016 to August 2016). This involved manual reduction of video from multiple cameras recording crashes and near-crashes, as well as the exact times the sign changed states. Data from 55 weekdays with sufficient video footage in this period were used to establish ground truth. Some weekdays were excluded due to corrupted video files or equipment maintenance. Based on the ground truth established, detection rates under different system conditions were calculated. To assess the performance of the system, the detection rate of all conflict events between 3rd Ave and Chicago Ave during the three-month evaluation period was calculated separately for the control algorithm and for the system as a whole. The detection rate was calculated for just the crashes, near crashes, and both events combined. To find the actual number of conflict events, all the events observed during the evaluation period were tabulated and sorted based on whether the drivers involved were warned or not warned about crash-prone conditions before the event, and if not, separated by the reason for such failure. The control algorithm is far more successful at raising the alarm for events than the system as a whole. The noon to 8 p.m. group illustrated the effect of the congestion override, a subject that was raised as a concern to MnDOT. A 2013 study recorded crashes that occurred between MN 65 and Portland Ave. These results are compared to the 2016 events that occurred in the same region. Based on the comparison of the two periods, there was a 22% decrease in crashes and a 54% decrease in near crashes in that zone following the implementation of the I-94 CPC Queue Warning system. MnDOT is considering the results from the I-94 CPC Queue Warning system promising and is considering an extended evaluation to look at the long-term effects of the system on crash rates. The I-35W SB Queue Warning system developed by Dr. Liu utilizes data collected from five sets of Systematic Monitoring of Arterial Road Traffic Signal (SMART-Signal) systems installed on MnDOT detector cabinets. The SMART-Signal system collects and archives high-resolution vehicle-detector actuation events. Each event contains the timestamp and occupancy time of one vehicle as well as the ID of the corresponding detector. The difference between the arrival times of consecutive vehicles gives the headway for these two vehicles and taking the occupancy time out of the headway gives the gap between these two vehicles. Based on the real-time data collected from detectors, the Michigan Queue Warning Algorithm (MQWA) can “see” a queue when it travels to the position of a detector. Although traffic states from detectors upstream and downstream of the queue occurrence position give some implication of the jam, it is risky to predict the occurrence of queue before it reaches a detector because such prediction easily generates false alarms. Therefore, instead of capturing the exact occurrence time and location of every stopped queue, the MQWA works to monitor the queue once it is seen by detectors. For those queues starting from in-between positions and propagating to detectors, lags in response arise but the MQWA provides a more robust solution than capturing the exact occurrence time and location of every stopped queue. For queues not propagating to detectors, the MQWA omits them because of their limited influence in space and time. Instances of the MQWA can run locally in any freeway segment between two detectors, estimating the length and duration of a queue once it is detected by the downstream detector. Moreover, considering the difference of traffic states across lanes (e.g., lanes to different directions of a diverge junction), one instance of the MQWA can run for each lane. The MQWA has limited capability of prediction about the time when a queue will be formed or cleared at any position in this segment, or the queue length in this segment at any time in the near future. The MQWA was implemented on a 2,218-foot-long I-35W SB segment between 50th and 60th Streets in South Minneapolis. The system was tested in the field for three weeks, showing the queue warning message “SLOW TRAFFIC AHEAD” to travelers when a queue was estimated at downstream locations. Before that, the system had also been running for three weeks without actually showing messages. The high-resolution data from loop detectors, the queue warning system log files archiving the start time, duration and location of triggered messages (including those not shown on the ILCS before field test), and videos from MnDOT cameras were used to evaluate the queue warning system. Based on the before and after data collected, the mean value and standard deviation of speed was calculated for each detector and for each message, and then a hypothesis testing was carried out to see whether there was a significant change before and after the deployment of the system. Based on this evaluation methodology the following conclusions were drawn: 1. In general, travelers on I-35W did respond to the queue-warning message “SLOW TRAFFIC AHEAD” and the traffic conditions with and without messages showed statistically significant differences. 2. The MQWA was able to smooth traffic by reducing the speed variance at downstream locations and speed difference between upstream and downstream locations, and therefore reduced the risk of rear-end crash and potentially improved mobility. 3. It took travelers some time from seeing the messages to taking actions such as slowing down their vehicles. Consequently, queue warning messages had little to do with the traffic conditions near the ILCS gantry (50th Street) but had an evident impact on the traffic at downstream locations (Diamond Lake Road). 4. The standard deviation of speed at the bifurcation location was increased when the traffic condition farther downstream locations on TH-62 was continuously congested. This might be because the traffic state in this case was more influenced by the downstream congestion rather than the upstream arrival, which made the queue warning message not very effective. 5. There was no significant difference between the effect of warning message in the morning peak and that in the evening peak. At the time of the writing of this report, both queue warning systems were still in operation. Starting in April 2018, the I-94 WB segment where the CPC Queue Warning system was operating will be under construction for three years. MnDOT has expressed the desire to implement two instances of the CPC Queue Warning upstream of the construction zone to alleviate concerns of rear-end collisions generated from congestion shockwaves due to capacity reduction in the work zone. (Author/publisher)
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