Passenger's perception about city buses in the aftermath of COVID 19: Experience from Guwahati city, India

Effects of risky bus driving behaviors on motorcyclists' and car drivers' traffic safety perceptions in mixed traffic flow

OBJECTIVE

This study investigates traffic safety perceptions of motorcyclists and car drivers toward risky bus driving behaviors (RBDBs) in mixed traffic flow (MTF).

METHODS

The study identified 10 RBDBs and employed images in a unique questionnaire survey. Further, permutation tests were employed to compare perceptions of motorcyclists in scenarios involving bus-motorcycle-car flow and bus-motorcycle flow and to compare their perceptions to those of car drivers'. Moreover, heteroskedastic generalized ordered logit regression models were utilized to predict traffic safety perceptions of motorcyclists and car drivers toward RBDBs.

RESULTS

High-speed bus driving is perceived as the most dangerous situation, while continuous flashing of lights at vehicles in front is perceived as the least dangerous. The permutation test revealed that motorcyclists tend to perceive RBDBs as less dangerous in bus-motorcycle flow than in mixed flow with cars, while car drivers consider them safer than motorcyclists. The regression model revealed that among the RBDBs, bus moving at high speeds, abruptly overtaking, abruptly changing lanes, and suddenly pulling over at bus stops are perceived as the most dangerous by motorcyclists and car drivers. The study also discusses the relationships between the socio-demographic characteristics of motorcyclists/car drivers and their safety perception toward RBDBs.

CONCLUSIONS

These findings could inform the development of interventions to reduce RBDBs and improve traffic safety for motorcyclists and car drivers.

Bio-inspired artificial somatic index for reflecting the travel experience of passenger agents under a flexible transportation scenario

This work analyzes the implementation of an artificial mechanism inspired by a biological somatic marker that ables a passenger agent to both, react to changes in the service, as well as keep said reactions as a memory for future decisions. An artificial mental model was designed, and the passenger agent was implemented as an autonomous decision-making system, where both, the choice of the transport operator and the evaluation of the received service were fully delegated to the system. The evaluation of the service experience is not only based on rational aspects (such as the cost of the trip) but also on subjective aspects related to the satisfaction level derived from the passenger's experience. The experimental scenario considered 10,000 trip requests simulated within an artificial map that emulates characteristics that are usually present in a city, such as vehicular congestion, the unsafety of certain streets, or the benefits of an area with tourist interest. The results show that the option to travel under a transport operator with a touristic profile is a trend. Unlike current cases in the industry, this research work explores the scenario where the passenger can have as a client a trip profile with memory, differentiated from other clients, and can receive more than one trip proposal for the same trip request, according to the different conditions that the passenger is looking for.