Toward an integrated traffic law enforcement and network management in connected vehicle environment: Conceptual model and survey study of public acceptance

Abstract

The increasing number of traffic accidents and their associated traffic congestion have prompted the development of innovative technologies to curb such problems. This paper proposes a novel score-based traffic law-enforcement and network management system (SLEM) that is based on connected vehicles (CV) technology. SLEM assigns a score to each driver which reflects her/his driving performance and compliance with traffic laws. The proposed system adopts a rewarding mechanism that rewards high-performing drivers and penalizes low-performing drivers who fail to obey the laws. The reward mechanism is in the form of a route guidance strategy that restricts low-score drivers from accessing certain roadway sections and time periods that are strategically selected in order to achieve an optimal traffic pattern in the network in which high-score drivers experience less congestion and a higher level of safety. A nationwide survey study was conducted to measure public acceptance of the proposed system. Another survey targeted a focused group of traffic operation and safety professionals. Based on the results of these surveys, a set of logistic regression models were developed to examine the sensitivity of public acceptance to policy and behavioral variables. The results showed that about 65.7 percent of the public and about 60.0 percent of professionals who participated in this study support the real-world implementation of SLEM.

Keywords: Connected vehicle; Driver performance monitoring; Traffic law enforcement; Transportation demand management.