Agent-based models have gained wide acceptance in transportation planning because with increasing computational power, large-scale people-centric mobility simulations are possible. Several modeling efforts have been reported in the literature on the demand side (with sophisticated activity-based models that focus on an individual’s day activity patterns) and on the supply side (with detailed representation of network dynamics through simulation-based dynamic traffic assignment models). This paper proposes an extension to a state-of-the-art integrated agent-based demand and supply model—SimMobility—for the design and evaluation of autonomous vehicle systems. SimMobility integrates various mobility-sensitive behavioral models in a multiple time-scale structure comprising three simulation levels: ( a) a long-term level that captures land use and economic activity, with special emphasis on accessibility; ( b) a midterm level that handles agents’ activities and travel patterns; and ( c) a short-term level that simulates movement of agents, operational systems, and decisions at a microscopic granularity. In that context, this paper proposes several extensions at the short-term and midterm levels to model and simulate autonomous vehicle systems and their effects on travel behavior. To showcase these features, the first-cut results of a hypothetical on-demand service with autonomous vehicles in a car-restricted zone of Singapore are presented. SimMobility was successfully used in an integrated manner to test and assess the performance of different autonomous vehicle fleet sizes and parking station configurations and to uncover changes in individual mobility patterns, specifically in regard to modal shares, routes, and destinations.

This paper consists of a study conducted to quantify the traffic congestion problem. Additionally, it describes the complete methodological process from data collection to cost per minute delay. Traffic congestion issues are frequently observed in large cities of the world where the road facilitiesoperate at capacity limits. To estimate the congestion cost,an arterial route of Karachi (A metropolitan city of Pakistan) was selected that has significant importance due to the industrial and port associated activity. The obtained results indicate that Pak Rs. 1 million are lost daily due to traffic congestion, which is extrapolated for whole Karachi. The amount is a composition of opportunity and fuel consumption costs caused due to excessive delays in congestion

With increasing urbanization, improved transportation technology and an expanding economy, additional roads and highways are built, in an effort to balance roadway capacity and demand. Knowledge of capacity of a road is essential in planning, design and operation of roads. To ascertain estimates of roadway capacity, Passenger Car Equivalent (PCE) factors are vital as they provide mechanism through which vehicles are converted into reference vehicle (i.e. Car). The paper discusses the case of Karachi (A metropolitan city of Pakistan) traffic environment where degree of heterogeneity is significantly high, and based on the collected data set from 12 different urban arterials of Karachi; presents the estimation of PCE factors from four different existing methods. Obtained PCE factors are then compared with each other and with those which are currently used in different traffic studies of Karachi. Significant differences are found among the values of PCE factors from each method

Objective: The probability of crash occurrence on horizontal curves is 1.5 to 4 times higher than that on tangent sections. A majority of these crashes are associated with human errors. Therefore, human behavior in curves needs to be corrected. Methodology: In this study, 2 different road marking treatments, optical circles and herringbone patterns, were used to influence driver behavior while entering a curve on a 2-lane rural road section. A driving simulator was used to perform the experiment. The simulated road sections are replicas of 2 real road sections in Flanders. Results: Both treatments were found to reduce speed before entering the curve. However, speed reduction was more gradual when optical circles were used. A herringbone pattern had more influence on lateral position than optical circles by forcing drivers to maintain a safe distance from opposing traffic in the adjacent lane. Conclusion: The study concluded that among other low-cost speed reduction methods, optical circles are effective tools to reduce speed and increase drivers’ attention. Moreover, a herringbone pattern can be used to reduce crashes on curves, mainly for head-on crashes where the main problem is inappropriate lateral position.