Vehicle trajectory challenge in predictive active steering rollover prevention

High center of mass vehicles are likely to rollover in extreme maneuvers. Available works present control strategies to prevent rollover. In these works, however, other important parameters such as path trajectory tracking are not a main concern. In this paper conflicts between rollover prevention and trajectory tracking is investigated. Model predictive control (MPC) is adopted to predict and avoid rollover while tracking desired trajectory. For this regard a model based future error estimation is introduced. The control framework predicts both rollover and trajectory error simultaneously. It avoids rollover while tries to track the trajectory. Simulation results for two controllers with and without trajectory tracking are presented. The results indicate that the controllers effectively limit rollover as a hard constraint while the trajectory tracking controller also minimizes and recovers the path error.     

Consideration of different travel strategies and choice set sizes in transit path choice modelling

Transportation - Path choice modelling is typically conducted by considering a subset of paths, not the universal set of all feasible paths as this is computationally challenging. This study...     

Developing an activity-based trip generation model for small/medium size planning agencies

The primary shortcoming of traditional four-step models is that they cannot capture derived travel demand behaviors. However, travel demand modeling (TDM) is an essential input for urban transportation planning. TDM needs to be highly precise and accurate by integrating the accurate base year estimation along with suitable alternatives. Currently, activity-based models (ABMs) have been developed mostly for large metropolitan planning organizations (MPO), whereas smaller/medium-sized MPOs typically lack these models. The main reason for this disparity in ABM development is the complexity of the models and the cost and data requirements needed. We posit however that smaller MPOs could develop ABMs from traditional travel surveys. Therefore, the specific aim of this paper is to develop a probabilistic home-based destination activity trip generation model considering travel time behavior. Results show that the developed model can significantly capture the actual number of trip generations.     

A Quantitative Analysis of the Performance of Transportation Projects in Developing Countries

Abstract

This paper presents the results of a detailed quantitative analysis of performance metrics of a sample consisting of 89 transportation projects sponsored by the World Bank. The sample and a subset consisting of 65 projects were evaluated using the performance metrics of project cost, schedule and scope. The effect of project size (dollar value) and project duration on performance metrics was investigated. Also, the achievement of project goals and potential improvement in planning and estimating over time (the learning effect) was studied. It was found that, in general, in transportation projects sponsored by the World Bank, costs are overestimated and schedules are optimistic. The outcome with respect to cost seems counter‐intuitive because previous work by other researchers had shown a systematic underestimation of project costs. There is significant evidence that there are no efficient controls in place to predict or prevent schedule delays. The study also showed that during the past 15 years, no improvement (learning effect) was evident in project cost and duration estimation as the level of accuracy has not changed significantly. Further, it is observed that project duration did not affect the performance with respect to cost and delay.     

A structured flexible transit system for low demand areas

Public transit structure is traditionally designed to contain fixed bus routes and predetermined bus stations. This paper presents an alternative flexible-route transit system, in which each bus is allowed to travel across a predetermined area to serve passengers, while these bus service areas collectively form a hybrid “grand” structure that resembles hub-and-spoke and grid networks. We analyze the agency and user cost components of this proposed system in idealized square cities and seek the optimum network layout, service area of each bus, and bus headway, to minimize the total system cost. We compare the performance of the proposed transit system with those of comparable systems (e.g., fixed-route transit network and taxi service), and show how each system is advantageous under certain passenger demand levels. It is found out that under low-to-moderate demand levels, the proposed flexible-route system tends to have the lowest system cost.     

Developing a chaotic pattern of dynamic Hazmat routing problem

The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat). In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.     

Sensitivity analysis and optimisation of suspension bushing using Taguchi method and grey relational analysis

In this paper, a novel method is presented for investigating suspension bushing based on mechanical properties of the bushing, their effective directions, spring stiffness and damping coefficient of bushing. The vehicle vibration model and suspension geometry parameters are used to optimise the vehicle suspension based on multi-body dynamics simulation (ADAMS/CAR) initially. Several experiment tests based on ISO 4128 and ISO 7401 have been performed in one of main Iranian automaker (SAIPA) in order to verify the ADAMS/CAR model. The grey relational analysis based on using Taguchi L27 orthogonal array is used to obtain the optimum suspension. Then the bushing characteristics are optimised considering the indicated method. This method considers a combination of ride comfort and handling qualities of vehicle as objective functions simultaneously. The results of optimum suspension are compared with typical Renault Logan which declares the accuracy and efficiency of this method in optimising suspension bushing.     

Normal and risky driving patterns identification in clear and rainy weather on freeway segments using vehicle kinematics trajectories and time series cluster analysis

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.     

Analysis of thirty years evolution of urban growth,transport demand and supply,energy consumption,greenhouse and pollutants emissions in Greater Cairo

The objective of the paper is to analyze evolution of urbanization, transport demand and supply in Greater Cairo (GC) over the last three decades of the 20th century. This is in addition to investigating the impact of city growth on energy consumption and emissions from transport. It utilizes results of 1971, 1978, 1987, 1998 and 2001 travel demand surveys, undertaken during the corresponding GC transport studies; each was published a year or two later. No further transport studies have been carried out in GC over the past decade and in view of the current political situation, it is not envisaged that similar studies will be undertaken in the near future. The analysis includes the evolution of daily trips, trip purpose share, modal share and number of cars. More recent trends for 2006/2007 vehicle registration by type and size are given. The evolution of transport supply covers projects until early 2012. In parallel estimates of the evolution of energy consumption and cost, emissions of greenhouse gases (CO₂) and pollutants (CO, HC and NO_x) are given for 1971/2001. The adopted estimation methodology is summarized. Comparative analysis of relevant evolution indexes and trends of growth between 1971 and 2001, taking the former as base year, is given. Land use and transport policies and projects that in some cases helped, directly or indirectly, to reduce traffic congestion, or at least prevented an increase, are addressed, commenting on their outcomes. Thus, transferable experience are useful to sister cities benefiting from successes and avoiding drawbacks. The evolution of the impact of GC metro on energy consumption and cost, and GHG emissions is given for 1987/2001, assuming the scenario “metro did not exist”. More recent impact analysis is given for 2007/2008, as the data allowed estimating traffic volumes that would have been added to the congested metro corridors under the above scenario; and the related fuel consumption and cost and GHGs. The paper ends with conclusions on GC evolution, learned lessons and suggests repeating similar work in other mega cities of the developing countries. Further research is emphasized, e.g., modeling the relationship between land use, transport, energy and emissions; modeling emission factors by vehicle type; and studying fuel-subsidy-reduction scenarios and their socio-economic effects.     

A Multiple Criteria Decision‐Making Approach for Prioritizing Accident Hotspots in the Absence of Crash Data

Abstract

In an efficient transportation system, traffic safety is an important issue and it is influenced by many factors. In a country like Iran, until now safety improvements are mainly concentrated on road engineering activities, without much attention for vehicle technology or driving behaviour. One important aspect of road safety engineering activities is the so‐called treatment of hotspots or dangerous accident locations. Until recently, accident hotspots were identified and remedied by the esxperts’ personal judgements and a handful of statistics without taking into account other important factors such as geometric and traffic conditions of the road network. This paper therefore aims to define and identify the criteria for accident hotspots, then giving a value to each criterion in order to develop a model to prioritize accident hotspots when traffic accident data is not available. To do this, the ‘Delphi’ method has been adopted and a prioritization model is produced by the use of a ‘Multiple Criteria Decision‐Making’ method. The procedure is illustrated on a collection of 20 road sections in Iran. In addition, the model is validated against an existing database of road sections containing safe locations and hotspots. Finally, a sensitivity analysis is carried out on the proposed method.