Safety issue of vehicular platoons remains a critical challenge and is still open for investigation. In this study, the authors propose an accurate simulation model for vehicular platoons, taking into consideration of the kinematics and dynamics aspects of the platoon and its physical constraints. A hybrid controller formed by two different longitudinal and lateral proportional–integral–derivative controllers and two operation modes at the same time is developed and simulated using Webots. By this study, the aim is to deeply study the performance of the platoon and reveal its weakness in real scenarios. The latter includes normal/degraded operating modes, different speeds, full brake scenarios and various global positioning system accuracies. Results show the efficiency of the platoon controller even in the predefined degraded mode.

The efficiency and scalability of geographical routing depend on the accuracy of location information of vehicles. Each vehicle determines its location using global positioning system (GPS) or other positioning systems. Related literature in geographical routing implicitly assumes accurate location information. However, this assumption is unrealistic considering the accuracy limitation of GPS and obstruction of signals by road side environments. The inaccurate location information results in performance degradation of geographical routing protocols in vehicular environments. In this context, this study proposes a location error resilient geographical routing (LER-GR) protocol. Rayleigh distribution-based error calculation technique is utilised for assessing error in the location of neighbouring vehicles. Kalman filter-based location prediction and correction technique is developed to predict the location of the neighbouring vehicles. The next forwarding vehicle is selected based on the least error in location information. Simulations are carried out to evaluate the performance of LER-GR in realistic environments, considering junction-based as well as real map-based road networks. The comparative performance evaluation attests the location error resilient capability of LER-GR in a vehicular environment.

An optimisation model for network progression coordinated control under the signal design mode of split phasing in unsaturated traffic conditions was proposed in this study. Considering the characteristics of the cyclical variation relationship between the bidirectional progression coordinated control effect and intersection spacing, a cosine function of the time difference between the actual green centre point and the ideal green centre point was defined as the evaluation index. The constraints of the common signal cycle, phase time, and phase sequence were introduced in the model, and the phase time allocation was discussed in this study. The model enables the phase time and phase sequence of each intersection to be freely valued within the solution space, and realises the comprehensive optimisation of the phase time, as well as common signal cycle, phase sequence, and offset. The case study demonstrates that the scheme optimised by this model can provide significant progression coordinated control effects for all the through movements on each artery. This method is effective when applied to network progression coordinated control.

We analyse the characteristics of early adopters of two intelligent vehicle safety systems, emergency braking and speed alert. Car users’ experiences with the two systems and the characteristics of early adopters of the systems were studied with an online survey organised in five European countries: Czech Republic, Finland, Germany, the Netherlands, and Spain. All of the studied variables related to the user – gender, age, kilometres driven annually and monthly household income – had a statistically significant relationship with using emergency braking. Gender, kilometres driven annually and monthly household income had a statistically significant relationship with using speed alert. For both systems, male drivers were more likely to be the first users of the systems. In general, the share of users having experienced the systems also increased with annual kilometrage and monthly household income. Younger, 18- to 44-year-old drivers were found more likely to have used emergency braking than older, 65- to 74-year-old drivers. The results, however, suggest that respondents’ annual kilometrage and monthly household income may be more strongly associated with using the systems than with age.

In this study, a new method is proposed for analysing the non-linear dynamics and stability in lane changes on highways by large buses. Unlike most of the literature associated with a simulated linear dynamic model for large buses, a verified 4DOF mechanical model with non-linear tire based on vehicle test is used in the lane-change simulation, including sinusoidal steering and steer returning. According to Jacobian matrix eigenvalues of the vehicle model, bifurcations of steady steering, sinusoidal steering and steer returning with disturbance on highways are investigated using a numerical method. The numerical simulation results reveal that Hopf bifurcations are identified in steady and sinusoidal steering conditions, which translates into an oscillatory behaviour leading to instability. Various equilibrium forms of stability are found, as well as saddle and Hopf bifurcations with disturbance ζ variety. The derived knowledge of the bifurcations set is hugely important to fully understand the actual dynamic motions of vehicles when lane changing on an even surface. It is a valuable reference for safety design of large buses to improve the traffic safety of driver–vehicle–road closed-loop system.

Since the geodetic height data is as rough as in metres collected by the consumer grade global positioning system (GPS) receiver, it is difficult to accurately estimating the road grade. In this study, the research attempted to develop a simple and practical approach to quantify the road grade. First, the characteristics of the raw GPS data was analysed, and a data cleaning and correction method was designed to improve the data quality. Then the study developed a method for calculating the road grade by dividing GPS points into pools. It was shown that the average difference between the road grade generated by the study and by the field measurement is only 0.1%. Finally, the study analysed the precision of the fuel consumption estimation when the road grade was taken into consideration. The results showed that the precision increased by 11.8, 10.0 or 2.8%, respectively, when the road grade was positive, negative or both.

Navigation in constrained areas such as ports or dense urban environments is often exposed to global navigation satellite system (GNSS) satellites masking caused by the infrastructures. In this case, the GNSS positioning is inaccurate or unavailable and proprioceptive sensors are generally used to temporarily localise the vehicle on a map. However, the drift of these sensors rapidly causes the navigation system to fail. In this study, the navigation is computed using magnetometer and GNSS observations defined in an absolute reference frame. The heading measurements are coupled with a digital map of the road network in order to localise the vehicle in a map matching process. The contribution of this study is the proposition of a particle filter that fuses the position and direction observations to estimate the vehicle position. In this context, when the GNSS signal is masked, the observations of direction are used to compute the vehicle position. The proposed filter is defined in both circular and linear domains in order to take into account the nature of the observations. The proposed approach is assessed on real and synthetic data.

Inappropriate speed in negotiating curves is the primary cause of rollovers and sideslips. In this study, the authors proposed an improved curve speed model considering driving styles, as well as vehicle and road factors. On the basis of a vehicle–road interaction model, the driver behaviour factor was introduced to quantify driving styles of curve speed choices. Firstly, the fuzzy synthetic evaluation method was utilised to classify the driving styles of 30 professional drivers into three different types (i.e. cautious, moderate and aggressive). Secondly, the classification results using fuzzy synthetic evaluation were compared to and verified with the K-means clustering method resulting over 60% the similarities. Finally, the proposed curve speed model was built and compared with four existing models. The authors’ model has the following promising advantages: (i) it reflects the speed preferences of three different types of drivers on the premise of driving safety on curves; and (ii) it shows a stationary speed transition when the road adhesion coefficient exceeds 0.8, which indicates that rollover, instead of sideslip, becomes the primary cause for lateral instability crashes on curves. Therefore, this proposed curve speed model could be applied in a curve speed warning system to improve both driving safety and comfort.

As randomly occurring events, traffic accidents pose serious challenges to the collection of comprehensive data to understand how travellers respond to them and to quantify their impacts. The advent of mobile phones, with their wide spatial/temporal coverage and ubiquitous presence in metro areas, offers a new source of data to conduct such studies. In this study, the collision accident of Metro Line 10 in Shanghai, China on 27 September 2011 is carefully investigated based on data derived from anonymous mobile phone records. The evacuation process of the accident is studied, followed by an analysis of the impact of this accident on commuting in the city. After analysing 7 billion of mobile phone records for an 11-day period, the authors find that the evacuation follows a two-stage pattern. They then identify the commuters of Line 10 and study their commuting patterns in the day of accident and also in the subsequent days. They find that most of Line 10 commuters still preferred to use metro to complete their travels during the disruption period of Line 10, and returned to their typical commuting patterns immediately after Line 10 resumed service.

Karachi (Pakistan) has recently been subject to violent incidents targeted primarily at civilians. These incidents are problematic for commuters who use the public bus system and who often fail to reach their work organisations due to consequent bus strikes. This series of events leads to considerable financial losses for the transport industry. This study proposes and implements safe and fast around the road (SAFAR) which is an intelligent transport Android application developed in collaboration with the local transport authority of Karachi. SAFAR provides run-time information to bus commuters regarding recent violent activities farther up from the current location of the commuters on their route. SAFAR employs live Twitter feeds to classify the manner, location, and casualty information of the violence. The authors investigate SAFAR's performance offline with three named entity recognition (NER) approaches, namely, supervised, dictionary-based, and integrated (hybrid), and show that the integrated approach has the best performance with a precision of 85%. Furthermore, SAFAR recommends alternate routes to commuters if violence is detected farther up through the A-star (A*) algorithm. An online evaluation of SAFAR with 50 real users gave a precision of ∼85% to identify violence locations. Finally, a subjective evaluation showed that SAFAR's performance is satisfactory.