Md. Hadiuzzaman

Variable Speed Limit Control Design for Relieving Congestion Caused by Active Bottlenecks

AbstractVariable speed limit (VSL) can be used on freeways to manage traffic flow with the goal of improving capacity. To achieve this objective, it is necessary that both speed and density dynamics be represented accurately. In this study, to deeply understand the effectiveness of VSL control, an analytical model was developed to represent drivers’ response to updated speed limits and macroscopic speed dynamical change with respect to changeable speed limits. Specifically, to model the freeway links having VSL control, the fundamental diagram (FD) was replaced with the VSL control variable in the relaxation term of the METANET. This modification led to the speed control variable appearing linearly, which is preferable for online computation. The density dynamics are based on the cell transmission model (CTM), which is introduced to estimate the transition flow among successive links with some practical constraints. It also offers flexibility in designing active bottleneck in which there is a capacity dro...

Assessing Mobility and Safety Impacts of a Variable Speed Limit Control Strategy

With the recent advances in active transportation and demand management, variable speed limits (VSLs) have been identified as an active traffic management strategy for improving freeway mobility and safety. Several heuristic VSL strategies have been proposed and evaluated. This paper proposes a model predictive VSL control strategy and evaluates its safety and mobility impacts. The strategy uses second-order traffic flow models to predict the traffic state and to provide a speed for optimizing corridor operational performance. A sensitivity analysis of the VSL update frequency and the safety constraints for the VSL strategy was performed to determine the best scenario in terms of safety and mobility. A stretch of Whitemud Drive, an urban freeway corridor in Edmonton, Alberta, Canada, was selected as the study area. The proposed VSL strategy was implemented in the microsimulation platform with a special software module. A real-time collision prediction model was developed for the same study area by using a matched case-control logistic regression technique to estimate the collision probability for each scenario. The results indicated that the proposed VSL control strategy can improve safety by approximately 50% and mobility by approximately 30%. A VSL update frequency of 5 min and a maximum speed difference of 10 km/h between successive time steps yielded the best performances. This finding can be useful for field implementation of VSL control.

Capacity Analysis for Fixed-Time Signalized Intersection for Non-Lane Based Traffic Condition

Capacity analysis of signalized intersections basically consists of estimating saturation flow and delay. Pre-timed signals are most commonly used in developing countries. This research deals with development of saturation flow and delay models for pre-timed signalized intersections with reference to non-lane based traffic condition prevailing in Bangladesh. In order to account non-uniformity in the static and dynamic characteristics of the vehicles passenger car unit (PCU) values for each vehicle is found out using synchronous regression technique and a range of site-specific PCU values were obtained. From this study, it has been observed that unified PCU concept does not hold good for non-lane based traffic condition and it has been recommended that the analysis should be site specific for non-lane based traffic condition. The saturation flow for each study approach was calculated using the average PCU values and multiple linear regression techniques were then used to derive predictive saturation flow models. Field delay for each approach is calculated based on HCM 2000 guidelines. It has been observed that HCM 2000 delay model consistently over estimate delay at degree of saturation more than 1.0. It has been suggested from the analysis that theoretical incremental delay (due to random arrival and over saturated queues) in HCM 2000 delay model be reduced by 70 % to better reflect field conditions in capacity analysis for non lane based traffic condition.

Modeling Driver Compliance to VSL and Quantifying Impacts of Compliance Levels and Control Strategy on Mobility and Safety

Variable Speed Limits (VSL) aim to improve freeway mobility and safety by controlling collective behaviours of drivers who are coming from upstream and ramps. Thus, VSL benefits should be positively correlated with VSL compliance level (CL). Surprisingly, a number of heuristic VSL control strategies have shown that VSL with increased CLs can, in fact, increase travel time. However, it is yet to be analyzed whether or not that outcome is due to the control strategy design or the CL. Some recent studies have shown that, regardless of CL, a proactive optimal VSL control provides mobility benefits; however, no evidence was found to indicate which CL is most achievable in practice, nor was a description found for the distribution of speed of a given VSL. The objective of this paper is to quantify the relative contribution that CLs with a proactive optimal VSL control have on improving mobility and safety. In this study, several CL-to-VSL strategies were modeled after real-world driver behaviour. To quantify the impact of CLs only, speed distributions were altered with the static speed limit. Then, the benefits were quantified by implementing a proactive optimal VSL control strategy with the CLs. The simulation evaluation showed that both VSL mobility and safety benefits are positively correlated with increasing CLs. Specifically, the travel time, throughput, and collision probability are improved in the range of 5- 15%, 6-8%, and 50-60%, respectively. The study findings will help guide transportation agencies in deploying VSL control considering CL, so as to achieve maximum mobility and safety benefits.

Comparison of Queue Estimation Accuracy by Shockwave-based and Input-output-based Models

Accurate queue estimation of traffic congestion at recurrent freeway bottlenecks is an important part of developing effective traffic control strategies. Two traffic flow analytical techniques are always employed in studying queuing processes: shockwave analysis and input-output analysis. These two techniques have been taken as separate tools for estimating queue length (size) in a number of studies. Shockwave analysis is particularly well-suited to evaluating the space occupied by the queuing process in units of length, e.g. metre, kilometre etc. Input-output analysis is always employed for vertical queue size in terms of the number of queued vehicles; however, some studies argued that this method underestimated queue size. This paper highlights the reason in the literature for underestimation of queue length with input-out analysis. The objective of this study was to compare real-time queue estimation accuracy using two proposed models based on the two analytical techniques, after investigating the dynamic characteristic of traffic flow at the bottleneck in the freeway. The parameters were determined using discrete field data collected along an urban freeway corridor, Whitemud Drive (WMD), in Edmonton, Canada. This study illustrated that although the two proposed models estimate queue length in different ways, they are compatible and capable of yielding accurate estimates of real-time queue length upstream of the studied bottleneck.

Adaptive neuro-fuzzy approach for modeling equilibrium speed–density relationship

ABSTRACT This paper endeavors to model the equilibrium speed–density relationship using a new fuzzy logic-based approach. To capture the randomness in traffic flow dynamics, it develops a single-input Adaptive Neuro-Fuzzy Inference System (ANFIS) trained with a hybrid algorithm. Furthermore, it proposes a new Premise-Consequent Conjugate Effect (PCCE) relationship to estimate fundamental diagram (FD) parameters from the ANFIS model. Several options (i.e. optimal split of data into training and testing data, selection of suitable membership function) offered by ANFIS are then illustrated. An experiment is performed to determine the maximum achievable goodness of fit without the occurrence of overfitting phenomenon by changing the number of clusters. The calibrated ANFIS model is compared against traditional and advanced speed–density models for five different freeway locations. Results show that the proposed model outperforms other preceding models by attaining goodness-of-fit values within a range of 0.82–0.92. Finally, the proposed PCCE relationship shows the ANFIS models robustness in accurate estimation of FD parameters for all freeway locations.

Pixel-based heterogeneous traffic measurement considering shadow and illumination variation

This paper endeavors to develop a new background estimation model for foreground segmentation using traditional background subtraction technique. Particularly, incorporation of luminance- and pollution-controlling parameters enables the model to address illumination variation and tail backs from vehicles, respectively. To classify each foreground pixel, a new heuristic dynamic threshold-difference function is proposed for determining individual threshold. Moreover, newly presented Positive Negative Segmentation technique removes shadow considering its physical characteristics from the foreground. After shadow correction, impulse flow waves and aggregated pictorial speed are computed accordingly. Impulse flow waves are eventually rectified and cumulated into actual flow. Pictorial speed is converted into actual speed using calibration equation considering perspective error. To facilitate video-based traffic measurement, a user-friendly tool PARTS (Pixel-Based Heterogeneous Traffic Measurement) is developed which incorporates the whole system. The data collected at different roadway locations are compared with that generated by the tool. It shows 90 and 97% correlations in measuring flow and speed, respectively.

Determining the Most Suitable Pedestrian Level of Service Method for Dhaka City, Bangladesh, Through a Synthesis of Measurements

In this paper, five pedestrian level of service (PLOS) methods are outlined in brief with respect to their assets and their limitations: (a) the Australian method, (b) the Highway Capacity Manual 2010 method, (c) the trip quality method, (d) the Landis method, and (e) the Tan Dandan method. In this study, each method was implemented to consider its suitability for use in Dhaka City, Bangladesh, through the integration of objective measurement and subjective assessment. The objective measurement consisted of a determination of the PLOS of five study locations in Dhaka City and the adoption of field data on traffic, geometric, and environmental factors. The subjective assessment had its basis in a user perception rating by 50 individuals of the service quality of pedestrian facilities in the selected study areas. A separate survey of 415 individuals was conducted to identify the most favored of 25 service quality attributes extracted from the five PLOS methods. The perception ratings were scrutinized to identify any potential deviations that arose from participant age and gender. In the ratings, the Australian method prevailed over the other four methods with a score of 18. The trip quality method scored second best with 16 points. The separate survey substantiated the adequacy of the Australian method for use in Dhaka City and included seven of the eight most desired and popular PLOS attributes selected by the survey respondents. Future research should be devoted to the development of a new PLOS method that uses the factors identified in this paper.

Variable Speed Limit Control Strategy with Collision Probability Assessments Based on Traffic State Prediction

An increasing number of vehicles on roadways has made traffic safety a serious challenge for transportation engineers. For the mitigation of traffic safety concerns, a variety of active traffic control measures, such as the variable speed limit (VSL), have been intensively investigated and deployed. VSL is usually adopted to advise drivers of a lower speed limit that is more appropriate to a congested traffic condition and takes advantage of the homogeneous traffic flow effect. However, in earlier studies, because of the absence of traffic state prediction, the impact of applied VSL control was not quantitatively analyzed. In this study, a model predictive control framework was adopted for predicting and assessing future traffic states. Taking into consideration the impact of VSL control, the study used a macroscopic traffic flow model. The collision probabilities of the predicted traffic states were assessed with a precursor-based collision prediction model to determine the optimized control signal. With this design, the proposed algorithm controller provided a robust method for determining the VSL control plan to optimize safety performance over a traffic network. The proposed control algorithm was evaluated with a simulation study based on field data that was conducted to reproduce a major ring road in Edmonton, Alberta, Canada. The proposed algorithm was used to implement VSL control on the studied 11-km freeway stretch. The proposed algorithm control scenario was then compared with the uncontrolled scenario. The evaluation proved that the proposed VSL control algorithm could effectively reduce the probability for collisions in a congested traffic network without significantly compromising mobility.

A Comparative Study on Numerical Optimization Techniques for Model Predictive Variable Speed Limit Control

Freeway congestion is highly recognized as a worldwide traffic problem since traffic demand has grown steadily over the past decades. Active traffic and demand management (ATDM) methods, including Ramp Metering (RM), Variable Speed Limit (VSL), and Route Guidance (RG), can help delay or even avoid congestion. Currently, those measures have become predictive and integrated based on real-time data collection and facility coordination, e.g. Model Predictive Control (MPC)-based measures. In this generic approach, a second-order macroscopic traffic flow model is used for traffic state prediction and the control problem is formulated as a nonlinear optimization problem; whereas, successful field implementation requires a computationally simple and accurate optimization technique to make it feasible in practice. In previous applications of MPC, common optimization techniques are the decision tree and sequential quadratic programming (SQP). They both perform well, but limited research has been conducted to assess and compare their effectiveness and efficiency. To address this research gap, this study tested their performance by applying an MPC-based VSL control. Using geometric and traffic data from an authentic freeway corridor, this paper discussed the speed limit sequences, measures of effectiveness (MOEs), and computation time from micro-simulation tests. The results of this comparative study can guide future filed implementation as a reference.