Measures for congestion on Expressway

We analyze the causes of traffic congestion and implement measures to alleviate and alleviate traffic congestion.

Changes in traffic congestion

Congestion loss time on Expressway ^{* 1} Has been on a downward trend since peaking in 1997, and has decreased to about 50% of its peak in 2008.

その後、2009年以降の休日特別割引（地方部5割引・上限1,000円等）による増加を経て、2014年以降は各種渋滞対策効果の発現により減少傾向が続いていました。

2017年以降、首都圏近郊のネットワーク整備に伴い当社管内の交通量が増加し、渋滞は再び増加していましたが、2020年は新型コロナウィルス感染症の影響等により大きく減少しました。

* 1: An index that indicates the degree of congestion. Calculated by multiplying the time lost due to traffic jam and the number of affected vehicles.

Image of transition of traffic congestion

Causes of traffic congestion

一年間に管内で発生する渋滞のうち約8割が交通集中によるものです。（2020年）

このうち渋滞発生箇所の内訳として、上り坂およびサグ部^※2が約6割と大部分を占めています。

※ 2: Out-bound from the hill In-bound is called a sag part a recess approaches the slope. For more information on traffic congestion mechanisms and traffic congestion countermeasures, Here

Image of traffic congestion factors — Causes of traffic congestion

Image of traffic congestion — Location of traffic congestion

Traffic congestion mitigation measures

In order to secure safe and smooth road traffic for our customers, we will implement both hardware and software measures to reduce traffic congestion.

Hardware measures
Soft measures

[Installation of additional lanes] [Extension of acceleration / deceleration lanes]

We are installing additional lanes and extending acceleration / deceleration lanes at major traffic congestion areas.

Extension of Kan-Etsu Expressway (Out-bound) Hanazono IC exit lane

[Development and dissemination of ETC]

Before the spread of ETC, the toll booth was the worst place where traffic jams occurred, but it is now almost eliminated.

Image of ETC usage rate / congestion loss time

[Traffic capacity Large pacemaker lights]

By blinking the light so that it moves in the direction of travel, it is effective in suppressing speed reduction and supporting speed recovery.

PML operation status near the aqua line (In-bound) aqua tunnel

[Providing speed recovery information through traffic congestion point signs, etc.]

Signs are installed at major traffic congestion points to promote conscious speed recovery.

Operation status of traffic jam point signs

Operation status of speed recovery display board

[Change of lane operation]

We are improving the lane operation so that it can respond to changes in traffic conditions.

Lane change status of Kan-Etsu Expressway (In-bound) Oizumi JCT

[Providing traffic congestion prediction information]

By avoiding traffic congestion, traffic demand will be dispersed, and you can expect a reduction in traffic congestion.

NEXCO EAST Official Congestion Forecaster Congestion Forecast & Outing Guide

Image image of traffic jam prediction on Expressway in the Kanto region during the Obon period in 2019

You can see the date and time of peak traffic at a glance! Image of traffic jam forecast guide Obonban

[Information provision using AI]

We are promoting technological development such as traffic jam prediction using AI, and are working to further improve prediction accuracy and convenience.

Long-term congestion forecast

NEXCO EAST and Grid Co., Ltd. have utilized AI to develop a technology that enables traffic forecasters to predict traffic congestion several months ahead. The traffic jam prediction model using AI learns past factor data that may greatly affect traffic jam occurrence, and predicts whether or not traffic jam will occur at a certain date and time in the future.

NEXCO EAST and Grid Succeeded in developing Japan's first Expressway company's first AI-based traffic congestion prediction technology during traffic congestion!
AI traffic jam prediction

Real-time demographics created by NTT Docomo, Inc. (hereinafter referred to as “docomo”) using the mechanism of the mobile phone network are combined with NEXCO EAST 's past traffic jams and technical knowledge about traffic flow, etc. We are conducting a verification test to predict traffic jams during the return time on some routes using "AI traffic jam prediction", which was developed using intelligence (AI) technology. In the experiment, information such as transit time every 30 minutes is distributed on the NEXCO EAST customer website “DraPla”.
Related Press Release