Based on our research, the following outcomes have been achieved so far. The papers published on the research conducted at ATLAS are given below:
Authors: Afzal Ahmed, Mohammed Raza Mehdi, Muzammil Abbas, Tehniat Fatima
Published in: Arabian Journal for Science and Engineering
Traffic streams in most of the urban areas of developing countries are highly heterogeneous with poor lane discipline. Traffic simulation and optimization packages based on microscopic traffic flow models are popular for modeling traffic flow and optimizing traffic controls all around the globe. However, applying microsimulation packages to model undisciplined and heterogeneous traffic streams may not yield perfect results. Whereas, macroscopic models can be easily calibrated for such heterogeneous and undisciplined traffic streams. This research applies the calibrated Cell Transmission Model (CTM) based optimization tool to determine optimal signal plans and to evaluate the potential of reduction in control delay at signalized intersections. Most of the traffic signals in Karachi are the pre-timed with a constant signal plan throughout the day, despite significant changes in traffic dynamics within a day. This study evaluates the performance of existing signal timing plans at two different locations in Karachi. The selected locations include a segment of urban arterial with three consecutive signals in close proximity. The second location was a standalone signalized intersection. 12-hour traffic and delay data on typical working days were collected through video recording technique. The data collected from the field was simulated using CTM-based signal optimization software, DISCO. The optimization results show an improvement of 45% in the existing delay at the selected segment of Khayaban-e-Ittehad. The delay at KDA intersection can be reduced by 29% by optimizing signal plans. The study shows that optimum signal timings based on accurate data can reduce delays and improve traffic network performance.
Authors: Afzal Ahmed, Syed Ahsan Ali Naqvi, David Watling, Dong Ngoduy
Published In:Transportation Research Record (TRR)
The accurate depiction of the existing traffic state on a road network is essential in reducing congestion and delays at signalized intersections. The existing literature in the optimization of signal timings either utilizes prediction of traffic state from traffic flow models or limited real-time measurements available from sensors. Prediction of traffic state based on historic data cannot represent the dynamics of change in traffic demand or network capacity. Similarly, data obtained from limited point sensors in a network provides estimates which contain errors. A reliable estimate of existing traffic state is, therefore, necessary to obtain signal timings which are based on the existing condition of traffic on the network. This research proposes a framework which utilizes estimates of traffic flows and travel times based on real-time estimated traffic state for obtaining optimal signal timings. The prediction of traffic state from the cell transmission model (CTM) and measurements from traffic sensors are combined in the recursive algorithm of extended Kalman filter (EKF) to obtain a reliable estimate of existing traffic state. The estimate of traffic state obtained from the CTM-EKF model is utilized in the optimization of signal timings using genetic algorithm (GA) in the proposed CTM-EKF-GA framework. The proposed framework is applied to a synthetic signalized intersection and the results are compared with a model-based optimal solution and simulated reality. The optimal delay estimated by CTM-EKF-GA framework is only 0.6% higher than the perfect solution, whereas the delay estimated by CTM-GA model is 12.9% higher than the perfect solution.
Authors: Afzal Ahmed, Satish V. Ukkusuri, Shahrukh Raza Mirza, Ausaja Hassan
Published In:Transportation Research Record (TRR)
Traffic streams in many developing countries consist of various modes of transport, with high heterogeneity in driver behavior. Modeling these types of traffic streams, in which traffic rules (speed limit, lane discipline, etc.) are not strictly followed, is a complex task. A review of the existing literature shows that there is a lack of traffic flow models that model the behavior of heterogeneous and undisciplined traffic streams. Like other undisciplined traffic streams, there are no speed limits (hence no speed enforcement) on most of the roads in Karachi, Pakistan. Lane discipline is also not observed by drivers, which results in a varying number of traffic lanes on a road. Therefore, most of the existing traffic flow models/simulation packages developed for disciplined traffic streams cannot appropriately model traffic streams without lane discipline. This research proposes a width-based cell transmission model (WCTM) by developing a fundamental flow-density diagram whose parameters are a function of the road width. Extensive field data have been collected from a selected arterial in Karachi for development of the fundamental traffic flow diagram. The values of the computed parameters are significantly different than the values reported in the literature. The piecewise-linear flow-density relation is developed by optimally estimating the breakpoints. Results show that the quadrilateral and pentagonal-shaped fundamental diagrams fit better with the collected data in comparison with the triangular-shaped fundamental diagram. The proposed WCTM is applied to selected segments of an arterial and results show that the WCTM was able to accurately model different traffic conditions.
Authors: Afzal Ahmed, Mohammed Raza Mehdi, Dong Ngoduy, Muzammil Abbas
Published In:Travel Behavior and Society
Heterogeneous traffic in developing countries consists of motorbikes and cars as private vehicles along with various other modes of transport for public and commercial transport. Motorbikes and cars have distinct travel characteristics, having different travel times and owned by commuters from significantly different socioeconomic backgrounds. This study uses a probe motorbike and probe car to collect travel time data for numerous trips covering a total length of 2040 km, on the various roads of Karachi. This travel time data is used to evaluate the accuracy of the only publically available advanced traveler information tool, ‘Google Live Traffic’ (GLT). Results show that there is a significant difference in the accuracies of the information for these two distinct modes of private transport. The overall accuracy of travel times predicted by GLT is 80% (85% for cars and 71% for motorbikes). Trip parameters such as traffic condition and type of road had a statistically significant correlation with the accuracy of the information provided by GLT. The behavior of commuters towards the awareness and utilization of traveler information provided by GLT was evaluated by performing an econometric analysis of selected socioeconomic and demographic parameters. A detailed stated preference survey was conducted from 1200 randomly selected motorbikes riders and car drivers from various locations of Karachi, a metropolitan city with 14.9 million inhabitants from a variety of socioeconomic background. Econometric analysis shows that age, education, income, vehicle type, and occupation have a significant correlation with awareness among commuters, whereas gender is identified as an insignificant factor.