Influence of Spatial Placement of Variable Speed Limit Zones on Urban Motorway Traffic Control

Traffic control approaches, in particular Variable Speed Limit (VSL), are often studied as solutions to improve the level of service on urban motorways. However, the efficiency of VSL strongly depends on the spatiotemporal arrangement of VSL zones. It is crucial to determine the lengths and locations of VSL zones for best VSL efficiency before deployment in a real system, as the optimal length of the VSL zone and its distance from the bottleneck directly affects traffic dynamics and, thus, bottleneck control. Therefore, in this study, we perform the analysis of different VSL zones lengths and their positions by using a closed-loop Simple Proportional Speed Controller for VSL (SPSC-VSL). We evaluate the different VSL zone configurations and their impact on traffic flow control and vehicle emissions in a SUMO microscopic simulation on a high traffic demand scenario. The results support the observations of previous researchers on the significant dependence of VSL zone placement on VSL efficiency. Additionally, new data-based (traffic parameters and vehicle emissions) evidence of the performance of the SPSC-VSL design are provided regarding the best placement of consecutive VSL zones for motorway bottleneck control not analysed in previous research

Freeway lab: testing dynamic speed limits

This paper presents the Dynamic Speed Limit (DSL) experiment that took place in June 2013 on the last 13 km stretch of the B-23 freeway accessing the city of Barcelona (Spain). The DSL system installed on that freeway in addition to the high density of surveillance equipment available makes this stretch a suitable highway lab. The objective of the experiment was to construct a comprehensive database of traffic engineering variables on a freeway site when different speed limits apply. Special attention was paid to ensure similar demand conditions. The experiment included the modification of the speed limits on a freeway segment making use of dynamic signals. Detailed measurements of vehicle counts, speeds, occupancies, lane changing maneuvers and travel times were taken. These simultaneous measurements obtained from very different types of monitoring equipment have been grouped into a single database. These include measurements from inductive loop detectors, radar, ultrasound and passive infrared non-intrusive traffic detectors, TV cameras and license plate recognition devices. The potential of this multi-source database is huge. For instance, a preliminary analysis empirically proves that drivers’ compliance with dynamic speed limits is very limited, unless speed enforcement devices are present. In addition, it is also proved that lane changing rates increase together with the occupancy level of the freeway. This comprehensive DSL database, unique in its nature, is made publicly available to the whole research community [Link], [1] in order to use up all its information. The present paper aims to present in detail this DSL experiment and its results and to contribute in the dissemination of the resulting database. This will facilitate its analysis to any interested researcher, and would lead to a better understanding of the causes and effects of DSL strategies on freeways.Postprint (published version

Work Zone Simulator Analysis: Driver Performance and Acceptance of Alternate Merge Sign Configurations

Improving work zone road safety is an issue of great interest due to the high number of crashes observed in work zones. Departments of Transportation (DOTs) use a variety of methods to inform drivers of upcoming work zones. One method used by DOTs is work zone signage configuration. It is necessary to evaluate the efficiency of different configurations, by law, before implementation of new signage designs that deviate from national standards. This research presents a driving simulator based study, funded by the Missouri Department of Transportation (MoDOT) that evaluates a driver’s response to work zone sign configurations. This study has compared the Conventional Lane Merge (CLM) configurations against MoDOT’s alternate configurations. Study participants within target populations, chosen to represent a range of Missouri drivers, have attempted four work zone configurations, as part of a driving simulator experience. The test scenarios simulated both right and left work zone lane closures for both the CLM and MoDOT alternatives. Travel time was measured against demographic characteristics of test driver populations. Statistical data analysis was used to investigate the effectiveness of different configurations employed in the study. The results of this study were compared to results from a previous MoDOT to compare result of field and simulation study about MoDOT’s alternate configurations

In-depth research into rural road crashes

This report was produced under an agreement between Transport SA and the Road Accident Research Unit formed in the late 1990s. Due to various delays in the publication of this report, Transport SA has since become the Department for Transport, Energy and Infrastructure and the Road Accident Research Unit has become the Centre for Automotive Safety Research. The report describes a series of 236 rural road crashes investigated between 1 March 1998 and 29 February 2000 in South Australia. Investigations began with immediate attendance at the scene of the crash. The information collected for each crash included: photographs of the crash scene and vehicles involved, video record of the crash scene and vehicles in selected cases, examination of the road environment, a site plan of the crash scene and vehicle movements in the crash, examination and measurements of the vehicles involved, interviews with crash participants, interviews with witnesses, interviews with police, information on the official police report, information from Coroner’s reports, and injury data for the injured crash participants. The report provides an overall statistical summary of the sample of crashes investigated, followed by a detailed examination of the road infrastructure issues contributing to the crashes. This is done on the basis of crash type, with separate sections concerned with single vehicle crashes, midblock crashes and crashes at intersections. A section is also provided that examines the role of roadside hazards in the crashes.Baldock MRJ, Kloeden CN and McLean A

Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones

This research project used the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study(NDS) to improve highway safety by using statistical descriptions of normal driving behavior to identify abnormal driving behaviors in work zones. SHRP2 data used in these analyses included 50 safety-critical events (SCEs) from work zones and 444 baseline events selected on a matched case-control design.Principal components analysis (PCA) was used to summarize kinematic data into “normal” and “abnormal”driving. Each second of driving is described by one point in three-dimensional principal component (PC) space;an ellipse containing the bulk of baseline points is considered “normal” driving. Driving segments without-of-ellipse points have a higher probability of being an SCE. Matched case-control analysis indicates that thespecific individual and traffic flow made approximately equal contributions to predicting out-of-ellipse driving.Structural Topics Modeling (STM) was used to analyze complex categorical data obtained from annotated videos.The STM method finds “words” representing categorical data variables that occur together in many events and describes these associations as “topics.” STM then associates topics with either baselines or SCEs. The STM produced 10 topics: 3 associated with SCEs, 5 associated with baselines, and 2 that were neutral. Distractionoccurs in both baselines and SCEs.Both approaches identify the role of individual drivers in producing situations where SCEs might arise. A countermeasure could use the PC calculation to indicate impending issues or specific drivers who may havehigher crash risk, but not to employ significant interventions such as automatically braking a vehicle without-of-ellipse driving patterns. STM results suggest communication to drivers or placing compliant vehicles in thetraffic stream would be effective. Finally, driver distraction in work zones should be discouraged

Assessing driver’s ability to estimate compliance rates to in-car, advisory driver support

\u3cp\u3ePurpose: In-car support systems focus increasingly on improving traffic flow and throughput. Advisory systems allow for fast market penetration, advising drivers how to drive in order to improve general flow. By following the advice, drivers cannot create a beneficial effect by themselves but rely on other road users to comply as well. Drivers who sense a low compliance among other road users may be discouraged to use the system themselves. The present experiment investigated whether drivers are able to distinguish between various compliance rates to Connected Cruise Control (CCC), an advisory driver support system that gives headway, speed and lane advice to improve throughput on motorways. Method: Forty-two participants estimated the compliance of other road users to CCC in a driving simulator. Actual system compliance was varied between 10, 50 and 90 %. Half of the participants received detailed information about the advice and the manifestation of compliant behaviour in traffic. Results: Compliance estimates showed no effect of actual compliance rates. Overall compliance ratings were higher for participants who had not received additional information about the system. Difference scores between compliance estimate and actual compliance indicate that additional information did not improve estimation accuracy, neither did it increase participants' confidence with their estimate. Conclusions: When actual compliance is low, drivers still show high compliance estimates which can have beneficial effect on system acceptance. Additional information does not improve compliance estimates.\u3c/p\u3

Determining Major Causes of Highway Work Zone Accidents in Kansas, Phase II

The work zones on the United States highway system have created an inevitable disruption on regular traffic flows and resulted in traffic safety problems. Understanding the characteristics and major causes of highway work zone crashes is a critical step towards developing effective safety countermeasures in highway work zones. In 2004, the Kansas Department of Transportation (KDOT) initiated a project (K-TRAN Project No. KU-05-01) to study the fatal crashes in Kansas highway work zones between 1992 and 2004. The study results including crash characteristics and major crash contributing factors were published in Bai and Li (2006). Built on the previous success, KDOT sponsored this research project (K-TRAN Project No. KU-06-01) to further study the injury crashes during the same period in Kansas highway work zones. The primary objectives of this study were to investigate the characteristics of the injury crashes, to identify risk factors that contributed to the injury crashes, and to compare characteristics between fatal and injury crashes in highway work zones. Frequency analysis was utilized to discover the basic characteristics reflected by single-variable frequencies as well as the complicated characteristics based on cross-categorized frequencies. The variable combinations used for analyzing cross-categorized frequencies were identified through independence test methods such as Pearson Chi-Square Test and Likelihood-Ratio Chi-Square Test. The characteristic comparison between fatal and injury crashes further helps to document the general characteristics of both fatal and injury crashes and to discover the unique factors that characterize different severities. The researchers found significant characteristics of Kansas highway work zone injury crashes and summarized them in six categories. The researchers also discovered noteworthy characteristic differences between work zone fatal and injury crashes and concluded the important factors that could have increased the severity of work zone crashes. Potential safety improvements were recommended accordingly and future research were suggested. The significant insights from this study are valuable for the design of safer highway work zones and for the development of safety countermeasures that have potential not only in reducing the number of crashes but also in mitigating the crash severity

The Effects of Work Zone Configurations on Physiological and Subjective Workload

There is a dearth of research on the effect of driving through work zones on physiological and subjective workload of drivers. The objectives of this research were to (a) study the effect of work zones and traffic density on physiological measures of workload, subjective workload and performance variables (b) study the relationship between physiological measures of workload, subjective workload and performance variables. Conventional lane merge (CLM), joint lane merge (JLM) and a road without a work zone (control) were modeled with high and low traffic density by using a full-size driving simulator. 13 female and 17 male students volunteered to participate in this study. Data regarding physiological measures of workload through heart rate variability measures (RMSSD, LF, HF and LF/HF ratio) were collected by using a heart monitoring watch. NASA-TLX was used to measure subjective workload. Variability in steering, braking and speed were used as performance variables. Results showed that the driving scenarios and traffic density did not affect physiological measures of workload. In terms of subjective workload, CLM and JLM did not differ significantly from each other. However, with respect to mental demand, temporal demand, effort and total workload, CLM was significantly more demanding than the control group. Total workload for driving in high traffic density was 27.2% more than that of in low traffic density. No significant differences were observed in brake variability between different scenarios. However, CLM and JLM had significantly higher speed variability than the control group but they were not significantly different from each other. Steer variability and brake variability were higher in high traffic density. In conclusion, results showed that when it comes to using driving simulators, physiological measures of workload show no sensitivity to changes in the work zone but subjective and performance variables are influenced and can be used to compare different work zone configurations