A review of surrogate safety measures on road safety at unsignalized intersections in developing countries

In recent times, the assessment of unsignalized intersection safety has received significant research attention because of the complex and diverse traffic movements and driving behaviour at such locations. However, priority traffic regulations are not well followed in comparison to the unsignalized junctions, which leads to more conflicts. Additionally, the severity of conflicts increases with continuous traffic manoeuvres, including right-turns and through traffic, combined with different driving behaviours. Several studies have compared crash-based analysis to proactive traffic safety measures. Current research outcomes imply that surrogate safety measures (SSMs) have the potential to elucidate the sequence of events that result in collisions, their underlying causes, and their outcomes. Therefore, to further understand the appropriateness of SSMs, further study is required based on heterogeneity in traffic along with driver behaviour that incorporates turning vehicle factors. This study presents an all-inclusive evaluation of the recent advancements in SSMs and their practical implementation, with a particular emphasis on unsignalized intersections in developing nations. The findings of this investigation would be helpful in identifying the appropriate safety indicators for evaluating traffic safety at unsignalized intersections.

Overtaking risk modeling in two-lane two-way highway with heterogeneous traffic environment of a low-income country using naturalistic driving dataset

INTRODUCTION

Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evaluates safety risk in terms of nature and severity of probable conflicts during overtaking maneuvers on a bi-directional undivided two-lane highway in a heterogeneous traffic environment of a low-income country. Nature and severity of probable conflicts were defined with the application of surrogate safety proximity indicators in real-world naturalistic driving environment.

METHOD

A risk severity model for overtaking maneuver was developed to better understand the significant factors associated with the probability of conflict and its severity during overtaking maneuver using discrete choice modeling approaches. The relevance of three alternate discrete outcome frameworks, namely multinomial logit (ML), ordered probit (OP), and mixed logit (MXL) models are addressed. The best fitted model is identified and estimated. The impact of the significant attributes was also evaluated. The study collected data from a section of two-lane highway in Bangladesh using naturalistic driving from both observational and computer vision techniques. A total of 46 explanatory variables related to overtaking maneuver are assessed.

RESULTS

Speed differential between overtaking and overtaken vehicles have a significant impact on the probability of severe conflicts. Moreover, the presence of a bus as an overtaking vehicle was found to contribute significantly to the severity of conflicts.

CONCLUSIONS

The study makes substantial research contributions related to overtaking behavior and safety risk evaluation during overtaking in mixed traffic environment in low-income countries. The results can be used as a proactive tool for the evaluation of overtaking maneuvers and associated safety risk, and making policy decisions reducing safety risk during overtaking maneuver as well as overall safety, while acknowledging the limited resources and facilities in low-income countries.

Development of emission factors for motorcycles and shared auto-rickshaws using real-world driving cycle for a typical Indian city

Vehicular emission is one of the most important contributors of urban air pollution. To quantify the impact of traffic on urban air quality, it is necessary to quantify vehicular emission. In many cities of India, such as Dhanbad, shared auto-rickshaw is the pre-dominant mode of transportation. Indian Driving Cycle (IDC) and Modified Indian Driving Cycle (MIDC) are used for emission testing of motorcycles, shared auto-rickshaws and passenger cars in India for regulatory purposes. IDC used for motorcycles and shared auto-rickshaws does not recognize the difference in two vehicle classes in terms of driving pattern. In real world, shared auto-rickshaws, behave differently than motorcycles. To quantify the impact of shared auto-rickshaws on urban air quality accurately, emission factors (EFs) are required to derive from real-world driving cycles (DCs). In heterogeneous traffic, vehicles of one class affect the behavior of vehicles of other classes. To estimate the emissions from different vehicle classes accurately, EFs for motorcycles and passenger cars are also required to be revised. In this study, real-world DCs were developed for motorcycles, shared auto-rickshaws and passenger cars in Dhanbad. Developed DCs were used to calculate EFs for respective classes. Shared auto-rickshaws were found to have the highest deviation from EFs derived using IDC.