Shiska Wahyu Widyaningrum, Silvia Afida Fahmi, Ali Fadillah, Daffa Ramadhan Eka Budiyanto, Ahmad Basuki

Analisis Titik Lokasi Kecelakaan di Ruas Jalan Tol Palimanan – Kanci

Introduction

Analisis titik lokasi kecelakaan di ruas jalan tol palimanan – kanci . Analisis titik kecelakaan di Tol Palimanan-Kanci (2022-2024) mengidentifikasi 11 lokasi rawan, terutama KM 210-211 (A) & KM 195-196 (B). Temukan penyebab & mitigasi.

Abstract

Traffic accidents on toll roads, including the Palimanan – Kanci (Palikanci) Toll Road, are a major concern due to high vehicle volume and other factors such as driver fatigue, weather conditions, and compliance with traffic regulations. This study aims to identify accident-prone locations and formulate mitigation measures. The research employs a quantitative analysis method using both primary and secondary data. Based on accident location identification for the Palimanan – Kanci Toll Road from 2022 to 2024, using the Equivalent Accident Number (EAN) and Upper Control Limit (UCL) methods per 1 km, 11 accident-prone locations were identified. However, two locations had the highest accident rates: Lane A at KM 210 – 211 and Lane B at KM 195 – 196. The most common cause of accidents was driver inattention and drowsiness, with the predominant accident type being rear-end collisions. The result of this study can serve as a reference for mitigation efforts to reduce accidents on the Palimanan – Kanci Toll Road.

Review

This paper, "Analisis Titik Lokasi Kecelakaan di Ruas Jalan Tol Palimanan – Kanci," addresses a critical and highly relevant issue concerning traffic safety on toll roads, specifically the Palikanci Toll Road in Indonesia. The study's primary objective is to systematically identify accident-prone locations and subsequently propose mitigation strategies, a crucial endeavor given the significant vehicle volume and contributing factors such as driver fatigue and non-compliance with regulations. Utilizing a quantitative analysis approach based on both primary and secondary data, the research sets out to provide actionable insights into improving road safety. The methodology employed, leveraging the Equivalent Accident Number (EAN) and Upper Control Limit (UCL) methods per 1 km for data spanning 2022 to 2024, successfully identified 11 accident-prone locations along the Palimanan – Kanci Toll Road. Among these, two segments, Lane A at KM 210 – 211 and Lane B at KM 195 – 196, were pinpointed as having the highest accident rates, offering a focused target for intervention. Crucially, the abstract highlights that driver inattention and drowsiness were the most common causes, primarily leading to rear-end collisions. These findings provide a clear and concise understanding of *where* and *why* accidents are most frequently occurring on this specific toll segment, demonstrating a rigorous application of accident analysis techniques. The practical utility of this study is substantial, serving as a valuable reference for road management authorities and policymakers in developing targeted mitigation efforts to reduce accident rates on the Palikanci Toll Road. By precisely identifying high-risk locations and predominant accident types and causes, the research offers a strong empirical foundation for implementing specific interventions such as enhanced signage, driver awareness campaigns, improved rest facilities, or enforcement strategies. While the abstract focuses on identification, future research could potentially expand to evaluate the effectiveness and cost-benefit of proposed mitigation measures, or compare these findings with accident patterns on other Indonesian toll roads to identify broader trends and best practices. Overall, this paper makes a significant and timely contribution to traffic safety literature and practice.

Full Text

Comments

You need to be logged in to post a comment.