This article presented a discussion on a research paper entitled “Queue Storage Design for Metered On-Ramps”, published by the International Journal of Transportation Science and Technology on March ...2013 (Volume 2, Issue 1, Pages 47–63). This discussion first summarized the contributions of the paper under discussion, and emphasized a critical insight presented by the paper under discussion that designing queue storage length as a percentage of peak hour on-ramp demand. Then, this article discussed the potential factors that may affect queue length estimation results, including different traffic flow arrival patterns between arterial-to-freeway ramps and freeway-to-freeway connectors, queue length as a function of demand-to-capacity ratio instead of on-ramp traffic volume, and errors caused by the stochastic nature of traffic flow when using field measured queues. Lastly, this article outlined methods to solve these limitations, and presented preliminary insights into the development of metered on-ramp queue storage length design guidelines considering the impacts of ramp geometric features and signal timing schemes of the upstream intersection.
Transportation sector contributes a significant proportion to the overall carbon emission. This paper aims at measuring the impact factors of the transportation sector’s carbon emission in China’s ...Yangtze River Delta Area (YRDA) so that mitigation strategies on promoting low-carbon transportation can be raised. The partial least squares method and an extended STIRPAT (stochastic impacts by regression on population, affluence, and technology) model were employed for quantifying the contributions of different impact factors that affect transportation carbon emission within the YRDA region for the period of 1995–2014. Results show that population size, GDP, civilian vehicle inventory, energy intensity, passenger transportation, freight turnover, and transport sector output are key factors inducing transportation carbon emission, while energy structure and transportation sector employees mitigate the overall transportation carbon emission. Such results provide valuable policy implications for preparing appropriate mitigation strategies, such as the optimization of energy structure, the development of energy efficient technologies, the improvement of public awareness, and the implementation of intelligent transportation management.
Connected vehicle (CV) technology aims to improve drivers’ situational awareness through audible and visual warnings displayed on a human–machine interface (HMI), thus reducing crashes caused by ...human error. This paper developed a driving simulator test bed to assess the readability and usefulness of the Wyoming CV applications. A total number of 26 professional drivers were recruited to participate in a driving-simulator study. Prior to driving the simulator, the participants were trained on both the concept of CV technology and the developed CV applications as well as the operation of the driving simulator. Three driving simulation scenarios were designed. For each scenario, participants drove two times: one with the HMI turned on and another one with the HMI turned off. After driving the simulator, a comprehensive revealed-preference survey was employed to collect the participants’ perceptions of CV technology and Wyoming CV applications. Results show that the Wyoming CV applications were most favored under poor-visibility driving conditions. Among the Wyoming CV applications, forward collision warning and rerouting applications were experienced as the most useful. Approximately 89% of the participants stated that the Wyoming CV applications provided them with improved road condition information and increased their experienced safety while driving; 65% of the participants stated the CV applications and the HMI did not introduce distraction from the primary task of driving. Finally, this paper concludes that the design of CV HMI needs to balance a trade-off between the readability of the warnings and drivers’ capability to safely recognize and timely respond to the received warnings.
Traffic signal coordination, which connects a series of signals along an arterial by various coordination methodologies, has been proven as one of the most cost-effective means for alleviating ...traffic congestion. Various metropolitan planning organizations (MPO) or transportation management centers (TMC) have included signal timing updates in their strategic plans. However, in practice, signal coordination is usually implemented when traffic volume is heavy (i.e., during peak hours). For the rest of the day, the free operation strategy is usually used to reduce the waiting time of uncoordinated phases. However, this free operation strategy may result in the loss of operational efficiency on the major street. Currently, implementing signal coordination during off-peak hours is rare in the U.S. since there is lack of an efficient method that considers traffic operations for both the major and the minor streets. Therefore, this research provides a novel method that balances the control delays between the major street and the minor street. The procedure is to optimize the splits of the major street while also using the reservice strategy in the signal controller for the minor street. Microsimulation modeling was employed to assess the performance of traffic signal coordination during off-peak periods. Results show that, under reasonable splits, the coordination effect on the major street can be achieved and protected with an acceptable delay to minor street traffic. The strategy can be immediately implemented to reduce travel time for major street traffic.
This paper investigated the actual truck acceleration capability at metered on-ramps. Truck acceleration performance data were collected through a video-based data collection method. A piecewise ...constant acceleration model was employed to capture truck acceleration characteristics. It was found that the existing acceleration length will affect truck drivers’ acceleration behavior. At the taper type ramp that has limited acceleration distance, acceleration profile indicated a decreasing trend with distance. While for the ramp with an auxiliary lane that has sufficient acceleration distance, it was found that the acceleration behavior is to have a high acceleration rate in the beginning, then acceleration rate decrease with speed increase, and high acceleration rate again as drivers approach the merging area. Field data show that the truck acceleration performance data documented in the ITE’s (Institute of Transportation Engineers) “Traffic Engineering Handbook” are much lower than the field collected data. Also, based on the regression analysis of speed versus distance profiles, it was found that the AASHTO’s (American Association of State Highway and Transportation Officials) Green Book acceleration length design guidance is insufficient to accommodate trucks at metered on-ramps. The required acceleration lengths for medium and heavy trucks are approximately 1.3 and 1.6times of the Green Book design guideline, respectively.
This paper presents an analytical framework for evaluating the performance of dedicated bus lanes. It assumes that under a designated travel demand, the traffic volume on a corridor changes with the ...modal shifts. The modal shift affects the operations of both bus traffic and car traffic and eventually, an equilibrium bus share ratio that maximizes the performance of the corridor will be reached. Microsimulation modelling is employed to assess the traffic operations under various demand levels and bus share ratios. The results show that converting a general lane into a bus lane significantly reduces bus delay. For car traffic, the overall trend is that delay increases after converting a general lane to a bus lane. In addition, delay decreases with the increase of bus share ratio. Nevertheless, when bus share ratio reaches 0.6 (demand less than 10,000 passengers per hour, pph; or 0.8 when demand increases up to 14,000 pph), there is no significant difference in delay between the two scenarios. The identified bus share ratios have the potential to direct the development of bus lane warrants. Finally, this research recommends that the Transportation Demand Management (TDM) strategies shall be developed to stimulate the modal shifts towards the identified optimal bus share ratio.
An offset T-intersection splits a conventional four leg intersection into two three-leg T-intersections to reduce the number of conflicts. While the safety benefits of offset T-intersections have ...been widely documented, the effects on operations are not well understood. To fix that, this paper employed microsimulation modeling to investigate the differences in operational performance between offset T-intersections and four-leg standard intersections under various traffic demands, intersection spacings, and signal timing schemes for three development types: superstore, hybrid gas station, and residential area. Queue length and delay were employed as measurements of effectiveness. Based on microsimulation modeling, we found that under most of the tested scenarios, offset T-intersections were superior to four-leg intersections in terms of reducing delay for the main street traffic. In addition, we found that the left–right (L-R) offset T-intersection configuration outperformed the right-left (R-L) offset configuration in terms of preventing main-street left turn queue spillback. Based on the simulation results, the paper provided practice-ready guidelines on selecting an optimum intersection configuration for each specific development type given the volume demands and known geometric constraints for a given site.
Ramp metering has been proven as an effective freeway management strategy; however, the impact of ramp metering on drivers' acceleration behavior has not been fully investigated. A better ...understanding of acceleration behavior changes with ramp metering is critical to the adequate design of ramp metering facilities. In this study, drivers' speed and acceleration data were collected at two representative metered ramps in Los Angeles, California. The speed and acceleration profiles under meter-on and meter-off scenarios were compared. Statistical results demonstrated that ramp metering affects drivers' acceleration behavior at ramp acceleration lane. It was found that at the metered ramp with short existing acceleration length, the average acceleration rate from ramp meter stop bar to 500 ft downstream under meter-on scenario (4.72 ft./s2) is approximately 40% higher than when meter-off (3.18 ft./s2). The design of acceleration lane length for metered on-ramps should therefore take into account the potential impacts of ramp metering on driver acceleration behavior.
•Ramp metering affects drivers' perceptions of the available acceleration lane length•Average acceleration rate when ramp meter-on is 40% higher than when ramp meter off•Ramp metering affects driver acceleration behavior and thus acceleration lane length design requirements•Need to develop dedicated acceleration lane length design guidelines for metered on-ramps
Urban traffic congestion and crashes have been considered by city planners as critical challenges to the economic development of the city. Traffic signal coordination, which connects a series of ...signals along an arterial by various coordination methodologies, has been proved as one of the most cost-effective means of reducing traffic congestion. In this regard, Metropolitan Planning Organizations (MPO) or Transportation Management Centers (TMC) have included signal timing coordination in their strategic plans. Nevertheless, concerns on the safety effects of traffic signal coordination have been continuously raised by both transportation agencies and the public. This is mainly because signal coordination may increase the travel speed along an arterial, which increases the risk and severity of traffic collisions. To date, there is neither solid evidence from the field to support the concern, nor theoretical-level models to analyze this issue. This research aims to investigate the effects of traffic signal coordination on the safety performance of urban arterials through microsimulation modeling of two traffic operational conditions: free signal operation and coordinated signals, respectively. Three urban arterials in Reno, Nevada were selected as the simulation testbed and were coded in the PTV VISSIM software. The simulated trajectory data were analyzed by the Surrogate Safety Assessment Model (SSAM) to estimate the number of traffic conflicts. Sensitivity analyses were conducted for various traffic demand levels. Results show that under unsaturated conditions, traffic signal coordination could reduce the number of conflicts in comparison with the free signal operation condition. However, under oversaturated conditions, no significant difference was found between coordinated and free signal operations. Findings from this research indicate that traffic signal coordination has the potential to reduce the risk of crashes on urban arterials under unsaturated conditions.
Enhancing traffic safety on freeways is the main goal for all transportation agencies. However, to achieve this goal, many analysis protocols of network screening models need to be improved through ...considering human factors while analyzing traffic data. This paper introduces one on the new analysis protocol of identifying and discriminating between normal and risky driving in clear and rainy weather. The introduced analysis protocol will consider the effect of human factors on updating the networking screening process of identifying hotspots of crash risk. This paper employs the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) data to investigate the behavior of normal and risky driving under both rainy and clear weather conditions. Near-crash events on freeways, which were used as Surrogate Measure of Safety (SMoS) for crash risk, were identified based on the changes in vehicle kinematics, including speed, longitudinal and lateral acceleration and deceleration rates, and yaw rates. Through a trajectory-level data analysis, there were significant differences in driving patterns between rainy and clear weather conditions; factors that affected crash risk mainly included driver reaction and response time, their evasive maneuvers such as changes in acceleration rates and yaw rates, and lane-changing maneuvers. A cluster analysis method was employed to classify driving patterns into two clusters: normal and risky driving condition patterns, respectively. Statistical results showed that risky driving patterns started on average one second earlier in rainy weather conditions than in clear weather conditions. Furthermore, risky driving patterns extended in average three seconds in rainy weather conditions, while it was two seconds in clear weather conditions. The identification of these patterns is considered as a primary step towards an automated development that would distinguish between different driving patterns in a Connected Vehicle CV environment using Basic Safety Messages (BSM) and to enhance the network screening analysis for increased crash risk hotspots.
•This study showed how driver compensates differently according to weather conditions to avoid crash event.•This study provided a discrimination threshold between normal and risky driving patterns in both rainy and clear weather conditions.•This study showed how the trajectory analysis helped in better discriminating driving patterns during a specific event.•The usage of an advanced machine learning classification method helped in detecting risky driving patterns more efficiently.•It was found that using a cluster analysis helped in detecting the risky driving pattern over the whole events.•The cluster analysis succeeded to provide results in the same context as the trajectory analysis.
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