Why are powered two wheeler riders still fatally injured in road junction crashes? – A causation analysis

Introduction: Powered Two Wheeler (PTW) crashes continue to be a road safety concern with a plateauing of the number of associated fatalities. Method: Forty one UK fatal or serious injury crashes involving a PTW and another vehicle at a junction were examined. Crash causation was analysed using the Driver Reliability and Error Analysis Method (DREAMv3.2). Crashes were split into two groups: Group A, where the other vehicle was travelling in the opposite direction to the PTW and commenced a right turn across the PTW’s path; and Group B where the other vehicle turned right out of a side road (or entrance) across the PTW’s path. Results: Overall, the factor that led directly to the crash (phenotype) was most commonly ‘too high speed’ or ‘too late action’ for the motorcyclist and ‘too early action’ for the other driver. Missed or late observations were contributory factors for both PTW riders and other vehicle drivers. Some differences between groups were observed with the PTW riders in Group B more likely to have ‘insufficient skills’ and the other vehicle drivers in Group A more likely to have ‘attention allocation’ as a causation factor. For both groups the crashes occurred because the other vehicle failed to give way to the PTW with causation chains that suggest ‘looked but failed to see’ is still an issue in this type of crash. The excessive speed of the PTW contributed to some crashes. Conclusions: This analysis suggests that drivers failing to give way to PTW riders at junctions is still a problem. This may relate to the ‘looked but did not see’ phenomenon. Causation differences were observed between the examined groups. Practical considerations: The DREAM methodology is an effective tool in analysing crash data from police collision investigation reports. Different countermeasures may be necessary to prevent different types of junction crashes.     

An evaluation scheme for assessing the effectiveness of intersection movement assist (IMA) on improving traffic safety

Objective: Intersection movement assist (IMA) has been recognized as one of the prominent countermeasures to reduce angle crashes at intersections, which constitute 22% of total crashes in the United States. Utilizing vehicle-based sensors, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communications, IMA offers extended vision to provide early warning for an imminent crash. However, most of IMA-related research implements their methods and strategies only in simulations, test tracks, or driving simulator studies that have quite a few assumptions and limitations and hence the effectiveness evaluations reported may not be transferable or comparable.

Methods: This study seeks to develop a generalized evaluation scheme that can be used not only to assess the effectiveness of IMA on improving traffic safety at intersections but to facilitate comparisons across similar studies. The proposed evaluation scheme utilizes the concepts of traffic conflict in terms of time-to-collision (TTC) as a crash surrogate. This approach avoids the issue of having insufficient crash frequency data for system evaluation. To measure the effectiveness of IMA on reducing traffic conflicts, a relative risk is calculated for comparing the risk of with/without using the IMA. As a proof-of-concept study, this study applied the proposed evaluation scheme and reported the effectiveness of IMA on improving traffic safety in a field operation test (FOT). Seven test scenarios were conducted at 4 intersections, and a total of 40 participants were recruited to use the IMA for 6 months.

Results: It was estimated that IMA users have 26% fewer conflicts with TTC less than 5 s and have 15% fewer conflicts with TTC less than 4 s. However, the results vary across different sites and different definitions of conflicts in terms of TTC.

Conclusions: Overall, IMA is promising to effectively reduce angle crashes related to sight obstruction and has potential to reduce not only crash frequency but crash severity.     

A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.     

Drivers’ visual scanning behavior at signalized and unsignalized intersections: A naturalistic driving study in China

Introduction: Intersections are the most dangerous locations in urban traffic. The present study aims to investigate drivers’ visual scanning behavior at signalized and unsignalized intersections. Method: Naturalistic driving data at 318 green phase signalized intersections and 300 unsignalized ones were collected. Drivers’ glance allocations were manually categorized into 10 areas of interest (AOIs), based on which three feature subsets were extracted including glance allocation frequencies, durations and AOI transition probabilities. The extracted features at signalized and unsignalized intersections were compared. Features with statistical significances were integrated to characterize drivers’ scanning patterns using the hierarchical clustering method. Andrews Curve was adopted to visually illustrate the clustering results of high-dimensional data. Results: Results showed that drivers going straight across signalized intersections had more often glances at the left view mirror and longer fixation on the near left area. When turning left, drivers near signalized intersections had more frequent glances at the left view mirror, fixated much longer on the forward and rearview mirror area, and had higher transition probabilities from near left to far left. Compared with drivers’ scanning patterns in left turning maneuver at signalized intersections, drivers with higher situation awareness levels would divide more attention to the forward and right areas than at unsignalized intersections. Conclusions: This study revealed that intersection types made differences on drivers’ scanning behavior. Practical applications: These findings suggest that future applications in advanced driver assistance systems and driver training programs should recommend different scanning strategies to drivers at different types of intersections.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

基于Cadna/A软件的城市交通十字路口噪声预测研究

通过分析城市十字路口噪声源的特点,采用Cadna/A噪声模拟软件建立十字路口交通预测模型,对十字路口周边声场分布情况进行了模拟研究,研究发现在选定的十字路口,交通噪声对周边环境影响较大,面向道路一侧昼间最大噪声值为72.9dB(A),夜间最大噪声值为64.5dB(A),背向道路一侧昼间最大噪声值为65.4dB(A),夜间最大噪声值为57.2 dB(A),本次研究的成果对于交通规划、噪声评价都具有十分重要的现实意义。